# HG changeset patch
# User computational-metabolomics
# Date 1613558973 0
# Node ID a338f73190552a5c3ffbd99c797e1fa1ac2c9380
"planemo upload for repository https://github.com/computational-metabolomics/dimspy-galaxy commit 80069808371b58f45da0c8133c27d67ac1a5b448"
diff -r 000000000000 -r a338f7319055 README.rst
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/README.rst Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,82 @@
+Galaxy tool wrappers for DIMSpy
+===============================
+|Build Status (last commit)| |Build Status (weekly global test)| |galaxy-eu| |Git| |Bioconda| |License|
+
+Galaxy tool wrappers for Python package DIMSpy: data processing of direct-infusion mass spectrometry (DIMS)-based metabolomics and lipidomics data
+
+Source code: https://github.com/computational-metabolomics/dimspy
+
+PyPI (The Python Package Index): https://pypi.org/project/dimspy
+
+
+Version
+--------
+v2.0.0+Galaxy0 (`DIMSpy v2.0.0 `_)
+
+
+Galaxy
+-------
+`Galaxy `_ is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses.
+
+
+Credits
+-------
+
+**Authors and contributors**
+ - Ralf J. M. Weber (r.j.weber@bham.ac.uk) - `University of Birmingham (UK) `__
+ - Thomas N. Lawson (t.n.lawson@bham.ac.uk) - `University of Birmingham (UK) `__
+ - Martin R. Jones (martin.jones@eawag.ch) - `Eawag (Switzerland) `_
+
+
+**DIMSpy acknowledges support from the following funders:**
+ - BBSRC, grant number BB/M019985/1
+ - European Commission's H2020 programme, grant agreement number 654241
+ - Wellcome Trust, grant number 202952/Z/16/Z
+
+
+Bugs
+----
+Please report any bugs that you find `here `_.
+Or fork the repository on `GitHub `_
+and create a pull request (PR). We welcome all contributions, and we
+will help you to make the PR if you are new to `git`.
+
+
+Changes
+-------
+v2.0.0+galaxy0
+ - First release (Python 3-based version `DIMSpy `_)
+
+v1.4.0+galaxy0
+ - Final release (Python 2-based version `DIMSpy `_)
+
+
+Licenses
+-------
+DIMSpy and Galaxy tools are released under the GNU General Public License v3.0 (see `LICENSE file `_)
+
+**Third-party licenses and copyright**
+
+RawFileReader reading tool. Copyright © 2016 by Thermo Fisher Scientific, Inc. All rights reserved. See `RawFileReaderLicense `_ for licensing information.
+Using DIMSpy software for processing Thermo Fisher Scientific *.raw files implies the acceptance of the RawFileReader license terms.
+Anyone receiving RawFileReader as part of a larger software distribution (in the current context, as part of DIMSpy) is considered an "end user" under
+section 3.3 of the RawFileReader License, and is not granted rights to redistribute RawFileReader.
+
+
+.. |Build Status (last commit)| image:: https://github.com/computational-metabolomics/dimspy-galaxy/workflows/Galaxy%20Tool%20Linting%20and%20Tests%20for%20push%20and%20PR/badge.svg
+ :target: https://github.com/computational-metabolomics/dimspy-galaxy/actions?query=workflow%3A%22Galaxy+Tool+Linting+and+Tests+for+push+and+PR%22
+
+.. |Build Status (weekly global test)| image:: https://github.com/computational-metabolomics/dimspy-galaxy/workflows/Weekly%20global%20Tool%20Linting%20and%20Tests/badge.svg
+ :target: https://github.com/computational-metabolomics/dimspy-galaxy/actions?query=workflow%3A%22Weekly+global+Tool+Linting+and+Tests%22
+
+.. |Git| image:: https://img.shields.io/badge/repository-GitHub-blue.svg?style=flat&maxAge=3600
+ :target: https://github.com/computational-metabolomics/dimspy
+
+.. |galaxy-eu| image:: https://img.shields.io/badge/usegalaxy-.eu-brightgreen?logo=data:image/png;base64,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
+ :target: http://usegalaxy.eu
+
+.. |Bioconda| image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat&maxAge=3600
+ :target: http://bioconda.github.io/recipes/dimspy/README.html
+
+.. |License| image:: https://img.shields.io/badge/License-GPL%20v3-blue.svg
+ :target: https://www.gnu.org/licenses/gpl-3.0.html
diff -r 000000000000 -r a338f7319055 RawFileReaderLicense.md
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/RawFileReaderLicense.md Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,51 @@
+**SOFTWARE LICENSE AGREEMENT ("License") FOR RawFileReader**
+
+These License terms are an agreement between you and Thermo Finnigan LLC ("Licensor"). They apply to Licensor's MSFileReader software program ("Software"), which includes documentation and any media on which you received it. These terms also apply to any updates or supplements for this Software, unless other terms accompany those items, in which case those terms apply. **If you use this Software, you accept this License. If you do not accept this License, you are prohibited from using this software. If you comply with these License terms, you have the rights set forth below.**
+
+1. Rights Granted:
+
+1.1. You may install and use this Software on any of your computing devices.
+
+1.2. You may distribute this Software to others, but only in combination with other software components and/or programs that you provide and subject to the distribution requirements and restrictions below.
+
+2. Use Restrictions:
+
+2.1. You may not decompile, disassemble, reverse engineer, use reflection or modify this Software.
+
+3. Distribution Requirements:
+
+If you distribute this Software to others, you agree to:
+
+3.1. Indemnify, defend and hold harmless the Licensor from any claims, including attorneys' fees, related to the distribution or use of this Software;
+
+3.2. Display the following text in your software's "About" box: " **RawFileReader reading tool. Copyright © 2016 by Thermo Fisher Scientific, Inc. All rights reserved**.";
+
+3.3. Require your end users to agree to a license agreement that prohibits them from redistributing this Software to others.
+
+4. Distribution Restrictions:
+
+4.1. You may not use the Licensor's trademarks in a way that suggests your software components and/or programs are provided by or are endorsed by the Licensor; and
+
+4.2. You may not commercially exploit this Software or products that incorporate this Software without the prior written consent of Licensor. Commercial exploitation includes, but is not limited to, charging a purchase price, license fee, maintenance fee, or subscription fee; or licensing, transferring or redistributing the Software in exchange for consideration of any kind.
+
+4.3. Your rights to this Software do not include any license, right, power or authority to subject this Software in whole or in part to any of the terms of an Excluded License. "Excluded License" means any license that requires as a condition of use, modification and/or distribution of software subject to the Excluded License, that such software or other software combined and/or distributed with such software be (a) disclosed or distributed in source code form; or (b) licensed for the purpose of making derivative works. Without limiting the foregoing obligation, you are specifically prohibited from distributing this Software with any software that is subject to the General Public License (GPL) or similar license in a manner that would create a combined work.
+
+5. Additional Terms Applicable to Software:
+
+5.1. This Software is licensed, not sold. This License only gives you some rights to use this Software; the Licensor reserves all other rights. Unless applicable law gives you more rights despite this limitation, you may use this Software only as expressly permitted in this License.
+
+5.2. Licensor has no obligation to fix, update, supplement or support this Software.
+
+5.3. This Software is not designed, manufactured or intended for any use requiring fail-safe performance in which the failure of this Software could lead to death, serious personal injury or severe physical and environmental damage ("High Risk Activities"), such as the operation of aircraft, medical or nuclear facilities. You agree not to use, or license the use of, this Software in connection with any High Risk Activities.
+
+5.4. Your rights under this License terminate automatically if you breach this License in any way. Termination of this License will not affect any of your obligations or liabilities arising prior to termination. The following sections of this License shall survive termination: 2.1, 3.1, 3.2, 3.3, 4.1, 4.2, 4.3, 5.1, 5.2, 5.3, 5.5, 5.6, 5.7, 5.8, and 5.9.
+
+5.5. This Software is subject to United States export laws and regulations. You agree to comply with all domestic and international export laws and regulations that apply to this Software. These laws include restrictions on destinations, end users and end use.
+
+5.6. This License shall be construed and controlled by the laws of the State of California, U.S.A., without regard to conflicts of law. You consent to the jurisdiction of the state and federal courts situated in the State of California in any action arising under this License. The application of the U.N. Convention on Contracts for the International Sale of Goods to this License is hereby expressly excluded. If any provision of this License shall be deemed unenforceable or contrary to law, the rest of this License shall remain in full effect and interpreted in an enforceable manner that most nearly captures the intent of the original language.
+
+5.7. THIS SOFTWARE IS LICENSED "AS IS". YOU BEAR ALL RISKS OF USING IT. LICENSOR GIVES NO AND DISCLAIMS ALL EXPRESS AND IMPLIED WARRANTIES, REPRESENTATIONS OR GUARANTEES. YOU MAY HAVE ADDITIONAL CONSUMER RIGHTS UNDER YOUR LOCAL LAWS WHICH THIS LICENSE CANNOT CHANGE. TO THE EXTENT PERMITTED UNDER YOUR LOCAL LAWS, LICENSOR EXCLUDES THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT.
+
+5.8. LICENSOR'S TOTAL LIABILITY TO YOU FOR DIRECT DAMAGES ARISING UNDER THIS LICENSE IS LIMITED TO U.S. $1.00. YOU CANNOT RECOVER ANY OTHER DAMAGES, INCLUDING CONSEQUENTIAL, LOST PROFITS, SPECIAL, INDIRECT OR INCIDENTAL DAMAGES, EVEN IF LICENSOR IS EXPRESSLY MADE AWARE OF THE POSSIBILITY THEREOF OR IS NEGLIGENT. THIS LIMITATION APPLIES TO ANYTHING RELATED TO THIS SOFTWARE, SERVICES, CONTENT (INCLUDING CODE) ON THIRD PARTY INTERNET SITES, OR THIRD PARTY PROGRAMS, AND CLAIMS FOR BREACH OF CONTRACT, BREACH OF WARRANTY, GUARANTEE OR CONDITION, STRICT LIABILITY, NEGLIGENCE, OR OTHER TORT TO THE EXTENT PERMITTED BY APPLICABLE LAW.
+
+5.9. Use, duplication or disclosure of this Software by the U.S. Government is subject to the restricted rights applicable to commercial computer software (under FAR 52.227019 and DFARS 252.227-7013 or parallel regulations). The manufacturer for this purpose is Thermo Finnigan LLC, 355 River Oaks Parkway, San Jose, California 95134, U.S.A.
diff -r 000000000000 -r a338f7319055 macros.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,311 @@
+
+ 2.0.0
+ 0
+
+
+
+ dimspy
+
+
+
+
+
+ dimspy hdf5-pm-to-txt
+ --input '$hdf5_file_out'
+ --output '$matrix_file_out'
+ --delimiter $delimiter
+ --attribute_name $hdf5_to_txt.matrix_attr
+ --representation-samples $hdf5_to_txt.representation_samples
+
+
+
+ dimspy hdf5-pm-to-txt
+ --input '$hdf5_file_out'
+ --output '$matrix_comprehensive_file_out'
+ --delimiter $delimiter
+ --comprehensive
+ --attribute_name $hdf5_to_txt.matrix_attr
+ --representation-samples $hdf5_to_txt.representation_samples
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ hdf5_to_txt["standard"] is True
+
+
+ hdf5_to_txt["comprehensive"] is True
+
+
+
+
+
+ 10.1038/nprot.2016.156
+ 10.1038/sdata.2014.12
+ 10.1021/ac062446p
+ 10.1021/ac2001803
+
+
+
+
+
+
+
+
+
+ - **mz** - the mass-to-charge ratio of the extracted mass spectral peak
+
+ - **intensity** - the intensity of the extracted mass spectral peak
+
+ - **snr** - the signal-to-noise ratio of the extracted peak, which is defined as the ratio of the peak’s intensity value to that of the background noise intensity value
+
+ - **present** - a numeric value greater than 0 that indicates the total number of scans at least one peak was detected in a given file
+
+ - **fraction** - a proportion ranging from 0 to 1 that indicates the total number of times a peak was detected in a given scan event type, divided by the total number of occurrences of that scan event type recorded in a given file.
+
+ - **purity** - a numeric value ranging from 0 to 1 that indicates the proportion of scans, for a given scan event type, that contained a single mass spectral peak following hierarchical clustering. A purity score less-than 1 indicates that in some proportion of scans, multiple peaks within a single scan were grouped together during the hierarchical clustering process.
+
+ - **occurrence** - a numeric value greater than 0 that indicates the total number of peaks that were observed across scans within the user-defined ppm error tolerance.
+
+ - **snr_flag** - a boolean value indicating whether to keep (“1”) or discard (“0”) a peak according to its signal-to-noise ratio value.
+
+ - **fraction_flag** - a boolean value indicating whether a peak should be kept or discarded according to the ratio of the number of scans in which it was detected, to the the number of scans in which it was not detected.
+
+ - **flags** - a boolean value indicating whether a peak should be retained or discarded based upon both its ‘snr_flag’ and ‘fraction_flag’ boolean values (if either is set to ‘0’ i.e. discard peak, then the ‘flags’ boolean should also be 0).
+
+
+
+
+
+
+**Example of an processed and filtered peaklist**:
+
+
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| mz | intensity | snr | present | fraction | rsd | occurrence | purity | snr_flag | fraction_flag | flags |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 90.44000 | 4744.0 | 3.06 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 97.07380 | 5423.6 | 3.52 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 99.04180 | 4105.8 | 3.60 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 99.49800 | 4775.7 | 3.05 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 99.95020 | 5657.8 | 3.63 | 1 | 0.063 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 100.40660 | 5489.5 | 3.57 | 3 | 0.188 | 14.51 | 3 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 100.8672 | 4841.18 | 3.27 | 7 | 0.4375 | 16.36 | 7 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.0027 | 9047.79 | 5.99 | 16 | 1 | 21.53 | 19 | 0.8125 | 1 | 1 | 1 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.0033 | 271893.9 | 182 | 16 | 1 | 4.17 | 16 | 1 | 1 | 1 | 1 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.0038 | 8738.03 | 5.9 | 14 | 0.875 | 9.71 | 14 | 1 | 1 | 1 | 1 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.004 | 5166.67 | 3.5 | 5 | 0.3125 | 18.02 | 6 | 0.8 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.0599 | 5894.69 | 3.88 | 2 | 0.125 | 15.06 | 2 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+| 101.2728 | 6846.28 | 4.44 | 1 | 0.0625 | nan | 1 | 1 | 1 | 0 | 0 |
++-----------+-----------+------+---------+----------+-------+------------+--------+----------+---------------+-------+
+
+
+
+
+
+**Show options for additional output(s)** (OPTIONAL):
+
+- **Standard output** (default = **No**) - boolean toggle where selection of:
+
+ - **No** - prevent the export of a .txt formatted peak matrix to the active Galaxy history.
+
+ - **Yes** - export a .txt formatted peak matrix to the active Galaxy history that includes only those peaks from the input peak intensity matrix that passed the filtering procedure.
+
+- **Comprehensive output** (default = "No") - boolean toggle where selection of:
+
+ - **No** - prevents export of a .txt formatted comprehensive peak matrix.
+
+ - **Yes** - exports a .txt formatted comprehensive peak matrix to the active Galaxy history that contains the m/z, missing values and other metrics associated with all peaks included in the input peak intensity matrix, including the metric defined by the "The peak matrix should contain intensity | m/z | SNR values" parameter.
+
+- **Should rows or columns represent the samples?** (default = **rows**) - binary toggle where selection of:
+
+ - **rows** - sample information is presented in the rows and m/z values (for aligned mass spectral peaks) in the columns of any output peak matrix.
+
+ - **columns** - sample information is presented in the columns and m/z values (for aligned mass spectral peaks) in the rows of any output peak matrix.
+
+- **The peak matrix should contain intensity | m/z | SNR values** - use this option to define which peak metric is inserted in to the cells of any optionally-output peak matrix:
+
+ - **Intensity** - writes the absolute peak intensity to the cells of the peak matrix
+
+ - **m/z** - writes the mass-to-charge ratio to the cells of the peak matrix
+
+ - **signal-to-noise ratio (SNR)** - writes the signal-to-noise ratio to the cells of the peak matrix
+
+
+
+
+
+**Default output** - a HDF5 file containing the aligned peak intensity matrix.
+
+|
+
+**Optional outputs** - the metric recorded in any optionally output peak matrix/matrices is defined using the parameter "The peak matrix should contain intensity | m/z | SNR values". By default, study samples are listed row-wise, while mass-to-charge ratios of the aligned mass spectral peaks are presented in columns (to adjust, users must adjust the "Should rows or columns represent samples" toggle to “columns”).
+
+
+- **Standard output** - an aligned peak matrix in tab-delimited format (“.” as decimal and NA for missing values).
+
+ **Example of a standard peak intensity matrix**:
+
+ +------------+----------+----------+----------+----------+---------+
+ | mz | 96.04216 | 99.08062 | 100.0759 | 100.8672 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | QC_1 | 0 | 0 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Blank_1 | 3342.626 | 0 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Control_10 | 0 | 0 | 45432.2 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Sample_2 | 0 | 3423.3 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Control_5 | 0 | 0 | 49759 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Control_10 | 0 | | 39890.5 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Sample_20 | 0 | 14563.7 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Sample_2 | 0 | 34676.4 | 0 | 0 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | Sample_14 | 0 | 13134.9 | 0 | 521.4 | ... |
+ +------------+----------+----------+----------+----------+---------+
+ | ... | ... | ... | ... | ... | ... |
+ +------------+----------+----------+----------+----------+---------+
+
+ |
+
+- **Comprehensive output** - an aligned peak matrix, as described for the "standard output" (above), including all metadata from the "Process Scans" Filelist/samplelist and the following additional mass spectral peak metrics:
+
+ - **present** - a positive integer value (0 value total number of study samples in the filelist / samplelist) that indicates the total number of study samples in which a peak was detected with the specified mass-to-charge ratio, plus or minus the user-defined ppm error tolerance.
+
+ - **occurrence** - a positive integer value indicating the number of peaks that were grouped together during the alignment procedure and thus, that were used to calculate the average mass-to-charge ratio indicated for the aligned peak. A value greater than given in the “Present” metric indicates that one or more peaklists contained more-than one mass spectral peak with the specified mass-to-charge, plus or minus the user-defined ppm error tolerance.
+
+ - **purity** - a proportion ranging from 0 to 1 that indicates the number of scans in which only a single peak was detected during the peaklist alignment process. If the value in the “occurrence” metric is greater than the “present” metric, purity will be 1. A purity 1 means that in at least one peaklist there was more-than one mass spectral peak with the specified mass-to-charge, plus or minus the user-defined ppm error tolerance.
+
+ - **rsd_all** - a numeric value indicating the percent relative standard deviation (otherwise termed the percent coefficient of variation) of peak intensities for peaks aligned together using the Align Samples tool. If fewer than 2 peaks were aligned across samples, then the rsd_all column will be filled in with ‘nan’
+
+ - **blank_flag** (may be absent if "Blank filter” tool was not applied) - a boolean value where 0 = reject peak, 1 = accept peak. A peak is accepted during blank filtering if a user-defined minimum proportion of study samples had peak intensity values greater-than the product of the average of “reference” sample peak intensities and the “min_fold_change” parameter.
+
+ - **fraction_flag** (may be absent if "Sample filter” tool was not applied)- a boolean value where 0 = reject peak, 1 = accept peak. If greater-than a user-defined minimum fraction of samples (whether checked across ALL experimental classes, or within ANY of the individual experimental classes) had recorded intensity values for a given peak, then this peak is accepted, i.e. it is considered in downstream processing procedures, while rejected peaks are not.
+
+ - **flags** - a boolean value indicating whether a peak should be included (“1”) or excluded (“0”) from downstream processing procedures. Exclusion of a peak occurs if the thresholds for “relative standard deviation” and/or “minimum number of technical replicates a peak has to be present in” were not met.
+
+ |
+
+ **Example of a comprehensive peak intensity matrix**:
+
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | mz | missing values | tags_batch | tags_replicates | tags_replicate | tags_injectionOrder | tags_classLabel | tags_untyped | 96.04216 | 99.08062 | 100.0759 | 100.8672 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | present* | | | | | | | | 1 | 4 | 3 | 1 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | occurrence* | | | | | | | | 1 | 4 | 4 | 1 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | purity* | | | | | | | | 1 | 1 | 1 | 1 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | rsd_all* | | | | | | | | nan | nan | 10.98 | nan | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | flags* | | | | | | | | 1 | 1 | 1 | 1 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | QC_1 | 2901 | 1 | 2_3_4 | 2 | 2 | QC | | 0 | 0 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Blank_1 | 2948 | 1 | 1_2_4 | 1 | 5 | Blank | | 3342.626 | 0 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Control_10 | 2921 | 1 | 2_3_4 | 2 | 10 | Control | | 0 | 0 | 45432.2 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Sample_2 | 2819 | 1 | 1_2_4 | 1 | 13 | Exposed | | 0 | 3423.3 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Control_5 | 2877 | 1 | 2_3_4 | 2 | 18 | Control | | 0 | 0 | 49759 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Control_10 | 2856 | 1 | 1_2_3 | 1 | 21 | Control | | 0 | | 39890.5 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Sample_20 | 2855 | 1 | 1_2_4 | 1 | 25 | Exposed | | 0 | 14563.7 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Sample_2 | 2814 | 1 | 1_2_4 | 1 | 29 | Exposed | | 0 | 34676.4 | 0 | 0 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | Sample_14 | 2870 | 1 | 1_2_3 | 1 | 33 | Exposed | | 0 | 13134.9 | 0 | 521.4 | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+ | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
+ +-------------+----------------+------------+-----------------+----------------+---------------------+-----------------+--------------+----------+----------+----------+----------+---------+
+
+
+
+
+
+Github respository (source code)
+--------------------------------
+
+Galaxy Tool Wrappers: https://github.com/computational-metabolomics/dimspy-galaxy/
+DIMSpy package: https://github.com/computational-metabolomics/dimspy/
+
+
+Developers and contributors
+---------------------------
+
+- Ralf Weber (r.j.weber@bham.ac.uk) - University of Birmingham (UK)
+- Martin R. Jones (m.r.jones.1@bham.ac.uk) - University of Birmingham (UK)
+- Thomas Lawson (tnl495@bham.ac.uk) - University of Birmingham (UK)
+
+
+
+
+License
+-------
+DIMSpy is released under the GNU General Public License v3.0 (see `LICENSE file`_)
+
+.. _`LICENSE file`: https://github.com/computational-metabolomics/dimspy-galaxy/blob/master/LICENSE
+
+
+
+
+
diff -r 000000000000 -r a338f7319055 sample_filter.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/sample_filter.xml Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,155 @@
+
+ Remove peaks that fail to appear in x-out-of-n (biological) samples
+
+ macros.xml
+
+
+
+
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+ [A-Za-z0-9_\- ]*
+
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+
+-------------
+Sample Filter
+-------------
+
+..
+
+----------------------------------------------
+
+Description
+-----------
+
+Standard DIMS processing workflow: Process Scans -> [Replicate Filter] -> Align Samples -> Blank Filter -> **Sample Filter** -> [Missing values sample filter] -> Pre-processing -> Statistics
+
+|
+
+There are many and varied reasons why a peak may not have been detected in all study samples, including: due to having an intensity (concentration) close to the signal-to-noise limit of the system; due to having been present in only one of the study classes (e.g. a drug administered to the ‘treatment’ class samples); due to ion suppression/enhancement effects in the mass spectrometer source region; etc. The Sample Filter tool allows users to remove peaks from the input peak intensity matrix that were detected in fewer-than a user-defined minimum number of study samples.
+
+------------------------------------
+
+Parameters
+-----------
+
+**Peak Intensity Matrix (HDF5 file)** (REQUIRED) - a HDF5 file containing the peak intensity matrix to undergo sample filtering.
+
+
+**Apply sample filter within each sample class** (REQUIRED; default **No**)
+
+ - **No** - check across ALL classes simultaneously whether greater-than the user-defined “Minimum fraction” of samples contained an intensity value for a specific mass spectral peak.
+
+ - **Yes** - check within EACH class separately whether greater-than the user-defined “Minimum fraction” of samples contained an intensity value for a specific mass spectral peak.
+
+ **IMPORTANT**: if in ANY class a peak is detected in greater-than the user-defined minimum fraction of samples, then the peak is retained in the output peak matrix. For classes in which this condition is not met, the peak intensity recorded for that peak (if any) will still be presented in the output peak matrix. If no peak intensity was recorded in a sample, then a ‘0’ is inserted in to the peak matrix.
+
+
+**Minimum fraction** (REQUIRED, default 0.5) - a numeric value between 0 and 1 indicating the proportion of study samples in which a peak must have a recorded intensity value in order for it to be retained in the output peak intensity matrix; e.g. 0.5 means that at least 50% of samples (whether assessed across all classes, or within each class individually) must have a recorded intensity value for a specific peak in order for it to be retained in the output peak matrix.
+
+|
+
+@help_options_addtional_output@
+
+-------------------------------
+
+
+Output file(s)
+--------------
+
+**IMPORTANT** - in all outputs except for the (optional) comprehensive output, if fewer-than the user-defined “Minimum fraction” of samples (whether assessed within a class, or across all classes) had a recorded intensity value (either within or across classes) for a given peak, then that peak will be removed from the output peak matrix. Note that when assessing within classes, only one class needs to have recorded intensity values in greater-than the "Minimum fraction" of samples in order for the peak to be retained in the output peak matrix.
+
+@help_outputs_matrix@
+
+-------------------------------------
+
+@github_developers_contributors@
+@license@
+
+
+
+
diff -r 000000000000 -r a338f7319055 test-data/MTBLS79_mzml_triplicates.zip
Binary file test-data/MTBLS79_mzml_triplicates.zip has changed
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep01_262.mzML
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep01_262.mzML Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,159 @@
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diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep01_262.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep01_262.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,499 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
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+101.75228905305326 26659.798828125 11.385289945622 1 0.1 nan 1.0 1.0 1 0 0
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+101.7624155187057 29687.05078125 11.821908038163564 1 0.1 nan 1.0 1.0 1 0 0
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep01_262_2_263_3_264.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep01_262_2_263_3_264.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,436 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep01_262_scan5.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep01_262_scan5.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,16 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep02_263.mzML
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep02_263.mzML Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,159 @@
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diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep02_263.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep02_263.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,511 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep02_263_scan5.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep02_263_scan5.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,16 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep03_264.mzML
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep03_264.mzML Wed Feb 17 10:49:33 2021 +0000
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diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep03_264.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep03_264.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,521 @@
+mz intensity snr present fraction rsd occurrence purity snr_flag fraction_flag flags
+98.99549972462908 85420.5765625 31.750861261289685 10 1.0 7.050841681521291 10.0 1.0 1 1 1
+101.75139691957963 28253.28515625 10.128283736810419 1 0.1 nan 1.0 1.0 1 0 0
+101.75644790222432 26853.529296875 10.266568872091154 1 0.1 nan 1.0 1.0 1 0 0
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC17_rep03_264_scan5.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC17_rep03_264_scan5.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,16 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC18_rep01_280.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC18_rep01_280.txt Wed Feb 17 10:49:33 2021 +0000
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC18_rep02_281.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC18_rep02_281.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,502 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_QC18_rep03_282.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_QC18_rep03_282.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,516 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/batch04_S01_average.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_S01_average.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,238 @@
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diff -r 000000000000 -r a338f7319055 test-data/batch04_S01_rep01_247_2_248_3_249.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/batch04_S01_rep01_247_2_248_3_249.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,238 @@
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diff -r 000000000000 -r a338f7319055 test-data/batch_04_QC18_mzml_triplicate.zip
Binary file test-data/batch_04_QC18_mzml_triplicate.zip has changed
diff -r 000000000000 -r a338f7319055 test-data/filelist_merge.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/filelist_merge.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,14 @@
+filename classLabel
+batch04_B02_rep01_301.mzML blank
+batch04_B02_rep02_302.mzML blank
+batch04_B02_rep03_303.mzML blank
+batch04_S01_rep01_247.mzML sample
+batch04_S01_rep02_248.mzML sample
+batch04_S01_rep03_249.mzML sample
+batch04_QC17_rep01_262.mzML QC
+batch04_QC17_rep02_263.mzML QC
+batch04_QC17_rep03_264.mzML QC
+batch04_QC18_rep01_280.mzML QC
+batch04_QC18_rep02_281.mzML QC
+batch04_QC18_rep03_282.mzML QC
+
diff -r 000000000000 -r a338f7319055 test-data/filelist_multilist_merge.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/filelist_multilist_merge.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,14 @@
+filename classLabel multilist
+batch04_B02_rep01_301.mzML blank 1
+batch04_B02_rep02_302.mzML blank 2
+batch04_B02_rep03_303.mzML blank 3
+batch04_S01_rep01_247.mzML sample 1
+batch04_S01_rep02_248.mzML sample 2
+batch04_S01_rep03_249.mzML sample 3
+batch04_QC17_rep01_262.mzML QC 1
+batch04_QC17_rep02_263.mzML QC 2
+batch04_QC17_rep03_264.mzML QC 3
+batch04_QC18_rep01_280.mzML QC 1
+batch04_QC18_rep02_281.mzML QC 2
+batch04_QC18_rep03_282.mzML QC 3
+
diff -r 000000000000 -r a338f7319055 test-data/filelist_mzml_QC17_triplicate.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/filelist_mzml_QC17_triplicate.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,5 @@
+filename replicate injectionOrder classLabel
+batch04_QC17_rep01_262.mzML 1 1 QC
+batch04_QC17_rep02_263.mzML 2 2 QC
+batch04_QC17_rep03_264.mzML 3 3 QC
+
diff -r 000000000000 -r a338f7319055 test-data/filelist_mzml_triplicates.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/filelist_mzml_triplicates.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,10 @@
+filename replicate injectionOrder classLabel
+batch04_B02_rep01_301.mzML 1 1 blank
+batch04_B02_rep02_302.mzML 2 2 blank
+batch04_B02_rep03_303.mzML 3 3 blank
+batch04_QC17_rep01_262.mzML 1 4 QC
+batch04_QC17_rep02_263.mzML 2 5 QC
+batch04_QC17_rep03_264.mzML 3 6 QC
+batch04_S01_rep01_247.mzML 1 7 sample
+batch04_S01_rep02_248.mzML 2 8 sample
+batch04_S01_rep03_249.mzML 3 9 sample
diff -r 000000000000 -r a338f7319055 test-data/merged_01.h5
Binary file test-data/merged_01.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/merged_02.h5
Binary file test-data/merged_02.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/merged_peaklist_001.h5
Binary file test-data/merged_peaklist_001.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/merged_peaklist_002.h5
Binary file test-data/merged_peaklist_002.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/merged_peaklist_003.h5
Binary file test-data/merged_peaklist_003.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_compr.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,10 @@
+mz missing values tags_classLabel tags_injectionOrder tags_replicates tags_untyped 95.08548671366543 96.04772304614822 97.06475291143175 97.10113840655873 98.99549986905885 99.08040117675267 101.00311801679446 101.05928426198216 101.0596673366772 101.77730040746692 101.78152400621897 102.12768606337795 102.97022355467323 103.03895120603583 103.07531883392421 104.10697250871583 105.00323419476476 105.09096431099911 107.07023024629058 107.08506232821624 107.08548831437565 109.10070305258999 109.10113731393284 111.08040236020433 111.11678604513918 112.0523012825977 113.05966680810211 113.09605148446333 114.0656779694334 114.06617048671613 114.09130290870944 115.03655729951394 115.07531829295569 115.11170521576067 116.07059901131294 116.98538214067723 116.9858715396252 117.05458339511324 117.09096864546488 118.08625365345154 119.08548531097144 120.98026726080117 120.98078653145228 121.00756219037551 121.06475400897882 123.01384531619902 123.05528891325828 123.11678819867741 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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_rmbs.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_rmbs.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,3 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_sf.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_sf_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_compr.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,11 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_sf_mv.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_mv.txt Wed Feb 17 10:49:33 2021 +0000
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_sf_mz.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_mz.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,238 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_sf_mz_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_mz_compr.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,899 @@
+mz present occurrence purity rsd_all blank_flag fraction_flag flags batch04_B02_rep01_301_2_302_3_303 batch04_QC17_rep01_262_2_263_3_264 batch04_S01_rep01_247_2_248_3_249
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+tags_classLabel blank QC sample
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_sf_within.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_within.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_bf_sf_within_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_bf_sf_within_compr.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,11 @@
+mz missing values tags_classLabel tags_injectionOrder tags_replicates tags_untyped 95.08548671366543 96.04772304614822 97.06475291143175 97.10113840655873 98.99549986905885 99.08040117675267 101.00311801679446 101.05928426198216 101.0596673366772 101.77730040746692 101.78152400621897 102.12768606337795 102.97022355467323 103.03895120603583 103.07531883392421 104.10697250871583 105.00323419476476 105.09096431099911 107.07023024629058 107.08506232821624 107.08548831437565 109.10070305258999 109.10113731393284 111.08040236020433 111.11678604513918 112.0523012825977 113.05966680810211 113.09605148446333 114.0656779694334 114.06617048671613 114.09130290870944 115.03655729951394 115.07531829295569 115.11170521576067 116.07059901131294 116.98538214067723 116.9858715396252 117.05458339511324 117.09096864546488 118.08625365345154 119.08548531097144 120.98026726080117 120.98078653145228 121.00756219037551 121.06475400897882 123.01384531619902 123.05528891325828 123.11678819867741 125.09548780155255 125.09605194748934 126.02194046816585 127.07532173447218 127.1117069981453 128.01084347694388 128.9948583362488 129.0903690076088 129.09097473553064 129.1273586022858 130.04922229380833 130.04986346789644 130.96451343575268 130.96513835756699 131.00983680839596 131.01051782481363 131.01894203525586 131.0702338830525 131.08548230101493 131.10661539918152 132.0745839879842 132.07500896236533 132.07556731753854 132.07610171670933 132.0766713483165 132.07720201005225 132.07799263513687 132.07837141790137 132.10124611045205 132.1018996975201 133.03457229481913 133.07312446652128 133.07380170847904 133.0789356579601 133.0794604946883 133.08011868699037 133.0806325278412 133.08524413399564 133.08588550957293 133.10050676518392 133.1011382507312 133.10527854592175 134.08099694564683 134.98683023336855 134.9964654207409 135.00286241434378 135.04402406228044 135.0792587339056 135.0797642293996 135.08038937946233 135.08097731962135 135.10088471794992 135.10153264587888 135.11613711794416 135.11678774782516 136.02150869861154 136.0469134701327 136.04742938193328 136.04811988277154 136.048697165222 136.0617659761462 136.0732517440144 136.08309630854197 136.08376192455026 136.940051854972 137.0294917608891 137.04506528555623 137.04577373894426 137.05659619286334 137.05726951049343 137.0589975559219 137.05967204232803 137.0948763722287 137.09539173301715 137.0960439007621 137.09663306703905 137.13244449575197 138.0913091821492 138.09941324144916 139.01560398968905 139.03653081073642 139.07291703612574 139.07463028495252 139.07532277465492 139.1110142138031 139.11170166416403 140.06692190472472 140.06747897881434 140.06819156030778 140.06875104166429 140.10695446252456 140.11506128362907 141.01585576661338 141.0521813800635 141.0715773757244 141.0878527167564 141.0885671085662 141.0902522618091 141.0909714445372 141.12735582539725 142.04743079559282 142.08622855924887 142.121881521859 142.1226040881495 142.1589920317392 142.94808537976732 143.00152580523707 143.08549356768336 143.1058868199526 143.10662483511956 143.98808368089487 144.08073350438687 144.10194219545554 144.98078943693872 145.04709214169574 145.10113599751404 145.12226168373772 146.11676431769024 146.11759354325272 146.1652125485029 146.99644084011834 147.07502609852781 147.07563402950387 147.07638149555612 147.07697997497814 147.0804077670755 147.112840745938 147.11679177127465 148.0024702963197 148.00308251585744 148.0038954129085 148.00452924670458 148.05902067458499 148.05962887799512 148.06046302920743 148.06110403907616 148.07981277810393 149.00247867555012 149.0225030436225 149.02328111272345 149.0448279122383 149.05967220572037 149.0638190453584 149.0960626602322 149.13244318446394 149.9997203272059 150.97595539245253 150.9768404643809 152.0221073526694 152.10695283820064 155.1066359153751 156.0412939880601 156.04209741077133 156.07674102643728 156.9897546182436 157.0454855961151 158.04024735191265 158.11753228639975 158.92198927219363 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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_mz.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_mz.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
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136.04812093283704 136.0486955276427 136.06175750188422 0.0 0.0 0.0 136.94004677782198 137.02949002900405 0.0 137.04577473555756 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 139.01560364456034 0.0 0.0 0.0 0.0 0.0 0.0 140.0669118704211 140.06747044897395 140.06820455625683 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 143.98808368089487 0.0 144.10194941905073 0.0 0.0 0.0 0.0 146.1167543627198 146.11759887328355 146.16521618928047 0.0 147.07501113605804 147.07562708474265 147.07636971827742 147.07697997497814 0.0 147.1128399220405 0.0 148.00246577828193 148.00308312433035 148.0038891702255 148.00453267624084 0.0 148.05962011184417 148.06046993648133 148.06110676707368 148.07981483158198 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 149.9997203272059 0.0 150.97684144108686 152.02210799662342 0.0 0.0 156.0412996437415 156.0421089601182 156.0767392276215 0.0 0.0 0.0 0.0 0.0 0.0 0.0 160.13320066714098 161.1284350589857 162.11069874197918 162.1115906443373 162.11234446784073 162.1130929112713 163.04514324690285 163.11484293430556 163.11582752022173 0.0 163.9760560140987 163.97686063441287 163.97777218073108 165.9736231097783 165.97593708784072 166.0862501270108 166.95072992851127 167.02172914498223 0.0 168.00576552039087 169.05837132707654 0.0 170.03162747934323 170.03260705367896 0.0 171.03600037123493 0.0 172.03075231265188 0.0 0.0 0.0 172.9846922843733 173.08084215876522 0.0 0.0 0.0 174.89594697042367 175.00168153698675 175.11896632541269 0.0 176.1029793883548 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 189.05239982742702 0.0 0.0 0.0 191.0400921847951 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 198.08493473483387 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 200.06700826337234 200.06834860559334 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 201.9323467146585 201.9337167817752 202.06651402919402 0.0 202.18018014023934 203.04008387277452 203.0512185957033 203.0526021670748 203.13904504958114 203.93184674777362 0.0 204.05601762329783 204.120741566778 204.12148789656462 204.12280776222028 204.12396941225447 205.05574486785596 0.0 0.0 0.0 205.12499796370346 205.12637072905179 205.15471137433576 0.0 0.0 206.05532193953783 206.12731699075212 207.0142799915133 207.0782258221575 0.0 0.0 0.0 0.0 207.98855046600153 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 210.08734755994155 210.08912563022986 0.0 0.0 0.0 0.0 0.0 210.9405883054582 0.0 210.98528316948537 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 214.05884903026265 0.0 0.0 0.0 0.0 0.0 215.06963425232274 0.0 0.0 0.0 0.0 0.0 0.0 218.1371356767124 218.13862571715347 218.1863402623181 0.0 219.0265951490137 219.14208654281651 0.0 0.0 222.02926194394072 0.0 0.0 0.0 222.98823084037602 0.0 0.0 0.0 0.0 227.1136372461145 0.0 0.0 229.1527805982205 229.15442275925454 0.0 230.1577883249707 0.0 232.15117655827143 232.15236139292725 232.15402602639816 0.0 233.15743904434476 235.06599791857175 0.0 0.0 238.0227446802619 0.0 0.0 241.12923187651447 0.0 242.07862840068944 242.11501335602307 0.0 0.0 0.0 0.0 0.0 0.0 245.13541658769466 245.1473345213128 245.1492732018194 0.0 0.0 246.15266268311177 246.16971505486742 0.0 0.0 0.0 247.24174217081634 248.14696731398237 248.148952839009 248.24510119483702 249.04524738526797 249.15325558774194 249.1554207063209 0.0 250.15878931674868 250.2138458476493 0.0 0.0 0.0 0.0 0.0 254.24753326494292 0.0 0.0 0.0 0.0 256.26317958753344 257.0419139321537 257.09112629299176 0.0 258.1098239570058 0.0 260.1853244867776 260.1965738713715 261.18868393078566 0.0 262.1282166171292 262.1646019698369 0.0 263.1459264531529 0.0 263.23664759543817 264.1721290979646 0.0 0.0 0.0 265.25003882680784 265.25225151138676 0.0 266.18775857224824 266.2556259793633 0.0 0.0 268.2631741074675 269.08772033011047 270.1098748881985 0.0 270.2788078853484 0.0 0.0 273.00566459900386 0.0 0.0 276.1802051997431 276.2294225610304 0.0 278.2450813519694 0.0 0.0 0.0 0.0 0.0 280.26313938561856 282.27632566767767 282.27875092122616 283.2821301630493 284.2944222576764 0.0 292.2033262311349 0.0 0.0 292.2606964002585 293.07137052046807 293.20667661588726 0.0 296.06599500778003 0.0 0.0 0.0 0.0 298.99289845851814 0.0 0.0 302.24239992914687 302.2454280929497 303.2487892501851 0.0 304.26075274414154 304.263413946466 0.0 305.2644117807417 306.21939353573833 0.0 306.26778558943306 0.0 0.0 0.0 307.04384865040396 0.0 308.0472780289569 308.0910943142905 0.0 308.2350224938003 309.0420613310678 310.0470257457027 0.0 0.0 0.0 0.0 0.0 0.0 0.0 316.20374815544324 0.0 316.32098996611785 317.1149878024951 318.21366995453485 318.21589535772273 318.2192200979607 0.0 318.2403385631764 319.2227529716699 0.0 0.0 320.21755434431265 320.22487153331144 0.0 320.2291348247542 320.2311115977232 320.23451919578343 320.2416268032767 0.0 320.2556857870354 320.97481123196434 0.0 321.2321970806676 321.2347868527714 321.2381769471039 0.0 0.0 322.2295227083509 322.23311964048435 322.2417378764105 322.2506879777181 0.0 323.23650546383163 0.0 326.9483861937062 0.0 328.0672501323285 0.0 0.0 0.0 0.0 0.0 0.0 0.0 332.0289134980641 0.0 0.0 0.0 334.2142735427018 0.0 334.2506696267976 334.2716164983125 0.0 0.0 336.2299292681668 0.0 336.948764624161 0.0 0.0 338.34173442780923 0.0 0.0 0.0 0.0 346.0470335782493 348.0704273629934 0.0 348.26637952643017 0.0 350.2540394700982 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 366.2038362161277 0.0 0.0 0.0 0.0 368.21938688223435 0.0 369.222845410467 0.0 0.0 370.0520506537512 0.0 370.2479629378005 0.0 371.3264526648029 372.2062494036983 372.24504693544145 372.3298569118878 0.0 374.2033355741846 0.0 0.0 376.2972328224594 377.30065753811886 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 384.2063233850069 0.0 385.31698932349127 386.0258741253333 386.2217689656134 0.0 0.0 0.0 387.22526202834104 0.0 387.3326381875434 0.0 388.21898304617207 389.2223587330244 0.0 0.0 0.0 393.3584268881766 394.2798175006623 0.0 395.33763366285575 0.0 396.308075518498 396.3410534271202 0.0 398.0202978887236 398.0328740641803 0.0 0.0 0.0 399.3577676972736 400.15720349699797 0.0 0.0 407.29346831002545 408.0078972418228 408.0205250147521 408.30808549442844 408.95103763826097 0.0 0.0 409.1618234250104 0.0 0.0 0.0 0.0 411.3326457168191 413.3482741972096 413.37340390336794 414.00682861920313 0.0 415.1568683229497 416.0842807338833 423.9817656573423 424.2818661060397 0.0 425.13529841809196 425.28529256698977 426.1388817985159 0.0 427.1338610703677 427.14290164258955 0.0 429.26274668178 435.06117265216034 435.33008376546667 435.98863850091516 0.0 0.0 443.23352041929456 0.0 445.24898581222004 445.9889561299008 446.2525112584176 0.0 450.3297354540204 451.96253208177745 453.06889642925677 453.1126019762791 0.0 0.0 454.0400532097235 0.0 457.04299694940715 461.33279594351643 0.0 461.96280983072137 0.0 467.23109072037784 0.0 0.0 469.05531506382346 0.0 0.0 469.4106702512512 470.01388502294685 0.0 471.0611088180543 471.13283571055706 0.0 0.0 473.0169960599658 0.0 0.0 0.0 476.2274137358063 0.0 0.0 479.33526094547426 0.0 0.0 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557.5019742949225 558.5053410737896 559.151249619171 559.5173862514131 561.5358083653088 563.551216499463 564.5547901082322 569.3454648973423 569.3635084067344 570.3673574121484 571.3618418833228
\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_mz_compr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_mz_compr.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,9 @@
+mz missing values tags_classLabel tags_injectionOrder tags_replicates tags_untyped 95.08548671366543 96.04772304614822 97.06475291143175 97.10113840655873 98.99549986905885 99.08040117675267 101.00311801679446 101.05928426198216 101.0596673366772 101.77730040746692 101.78152400621897 102.12768606337795 102.97022355467323 103.03895120603583 103.07531883392421 104.10697250871583 105.00323419476476 105.09096431099911 107.07023024629058 107.08506232821624 107.08548831437565 109.10070305258999 109.10113731393284 111.08040236020433 111.11678604513918 112.0523012825977 113.05966680810211 113.09605148446333 114.0656779694334 114.06617048671613 114.09130290870944 115.03655729951394 115.07531829295569 115.11170521576067 116.07059901131294 116.98538214067723 116.9858715396252 117.05458339511324 117.09096864546488 118.08625365345154 119.08548531097144 120.98026726080117 120.98078653145228 121.00756219037551 121.06475400897882 123.01384531619902 123.05528891325828 123.11678819867741 125.09548780155255 125.09605194748934 126.02194046816585 127.07532173447218 127.1117069981453 128.01084347694388 128.9948583362488 129.0903690076088 129.09097473553064 129.1273586022858 130.04922229380833 130.04986346789644 130.96451343575268 130.96513835756699 131.00983680839596 131.01051782481363 131.01894203525586 131.0702338830525 131.08548230101493 131.10661539918152 132.0745839879842 132.07500896236533 132.07556731753854 132.07610171670933 132.0766713483165 132.07720201005225 132.07799263513687 132.07837141790137 132.10124611045205 132.1018996975201 133.03457229481913 133.07312446652128 133.07380170847904 133.0789356579601 133.0794604946883 133.08011868699037 133.0806325278412 133.08524413399564 133.08588550957293 133.10050676518392 133.1011382507312 133.10527854592175 134.08099694564683 134.98683023336855 134.9964654207409 135.00286241434378 135.04402406228044 135.0792587339056 135.0797642293996 135.08038937946233 135.08097731962135 135.10088471794992 135.10153264587888 135.11613711794416 135.11678774782516 136.02150869861154 136.0469134701327 136.04742938193328 136.04811988277154 136.048697165222 136.0617659761462 136.0732517440144 136.08309630854197 136.08376192455026 136.940051854972 137.0294917608891 137.04506528555623 137.04577373894426 137.05659619286334 137.05726951049343 137.0589975559219 137.05967204232803 137.0948763722287 137.09539173301715 137.0960439007621 137.09663306703905 137.13244449575197 138.0913091821492 138.09941324144916 139.01560398968905 139.03653081073642 139.07291703612574 139.07463028495252 139.07532277465492 139.1110142138031 139.11170166416403 140.06692190472472 140.06747897881434 140.06819156030778 140.06875104166429 140.10695446252456 140.11506128362907 141.01585576661338 141.0521813800635 141.0715773757244 141.0878527167564 141.0885671085662 141.0902522618091 141.0909714445372 141.12735582539725 142.04743079559282 142.08622855924887 142.121881521859 142.1226040881495 142.1589920317392 142.94808537976732 143.00152580523707 143.08549356768336 143.1058868199526 143.10662483511956 143.98808368089487 144.08073350438687 144.10194219545554 144.98078943693872 145.04709214169574 145.10113599751404 145.12226168373772 146.11676431769024 146.11759354325272 146.1652125485029 146.99644084011834 147.07502609852781 147.07563402950387 147.07638149555612 147.07697997497814 147.0804077670755 147.112840745938 147.11679177127465 148.0024702963197 148.00308251585744 148.0038954129085 148.00452924670458 148.05902067458499 148.05962887799512 148.06046302920743 148.06110403907616 148.07981277810393 149.00247867555012 149.0225030436225 149.02328111272345 149.0448279122383 149.05967220572037 149.0638190453584 149.0960626602322 149.13244318446394 149.9997203272059 150.97595539245253 150.9768404643809 152.0221073526694 152.10695283820064 155.1066359153751 156.0412939880601 156.04209741077133 156.07674102643728 156.9897546182436 157.0454855961151 158.04024735191265 158.11753228639975 158.92198927219363 159.02772080130654 159.0651657616573 160.13319875054125 161.1284325416102 162.1106902196877 162.1115906443373 162.1123778574673 162.11308929466574 163.04513656325977 163.11485420595486 163.11582209439445 163.148118188048 163.9760560140987 163.97686568906175 163.97778010152314 165.9736231097783 165.9759371118122 166.08625181766183 166.9507285970917 167.02172703394848 167.10423518134192 168.00575923053145 169.05836902892332 169.12230235493337 170.03162710920424 170.0326087503044 170.11754239200607 171.03600037123493 171.10155642964003 172.0307500097432 172.1313914114654 172.13218998678823 172.13305836138966 172.9846879753075 173.08084075767584 173.13246540751302 173.13653634602073 174.11245406853564 174.89594473006088 175.00168001762995 175.11896354134905 175.14811485632126 176.10297922906722 177.1346086110464 179.12846513500673 180.0994850334914 181.06478125644023 183.13554233391793 184.09440397948592 186.14884519970414 187.1259281943036 188.1260274070556 188.12698201715224 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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_as_t.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_as_t.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,894 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_hdf5_to_txt_comprehensive_snr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_hdf5_to_txt_comprehensive_snr.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,11 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_hdf5_to_txt_intensity.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_hdf5_to_txt_intensity.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,899 @@
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+missing values 231 0 0
+tags_classLabel blank QC sample
+tags_injectionOrder 1 4 7
+tags_replicates 1-2-3 1-2-3 1-2-3
+tags_untyped
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diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_hdf5_to_txt_mz.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_hdf5_to_txt_mz.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
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\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/peak_matrix_hdf5_to_txt_snr.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/peak_matrix_hdf5_to_txt_snr.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
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+batch04_B02_rep01_301_2_302_3_303 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 12.60837692196508 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 44.93377179525178 0.0 0.0 0.0 0.0 12.19187833737835 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.025673583884664 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 16.727173635562497 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 31.878940430074564 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
+batch04_QC17_rep01_262_2_263_3_264 32.573341821331226 12.674073234517186 55.15727399878813 118.26436471569718 14.353887375744868 16.566616310344337 19.39186021893004 12.923387183392036 49.95670081319196 17.019293955731964 10.87904044859295 24.14295647947566 125.78863774690673 593.8966048738445 6010.633363042784 676.6942716492396 15.267210136093972 32.51502689562823 112.15127674048351 11.315037281624518 40.90882057391183 13.203674202475915 45.22950171144896 170.185849631688 14.186053126780786 18.503271657412146 30.89221144559383 29.230069940654705 198.17396355528481 15.925626394073797 22.841442323509423 47.673496392606474 15.90171239242386 88.64862826222804 34.3456576496118 23.32643643001239 70.1028425275383 481.53386896330625 21.881660084683812 24.418174881541308 140.60462163064707 12.413469577956905 34.286104120249796 124.29424020105152 869.1556285603853 23.004971834541397 15.49280356164614 42.08883263207985 258.64835265152595 18.593440774959888 43.12373261146928 268.9111981199981 19.275975846770482 31.412046614417758 70.20140446134444 36.605038033690526 34.746220583805155 290.0872487599088 14.875571494316793 33.703026615321015 16.37167090022506 29.411337860791388 1432.1239188052848 124.12365428438896 11.857710782598286 10.736783521118785 83.15477233359606 24.561500934017587 219.23650938531702 16.29409688252885 24.84338524577289 46.98790511089472 55.78800158298344 25.00118041279252 36.52872178937652 19.055970304806966 191.34204717658486 13.166640992374175 14.32500563959885 31.937844787618996 21.849210661250577 62.08304850395276 51.1769416569665 33.71113195043209 27.90228489749656 26.812643697570966 178.55820628779898 71.1101541350646 13.420867885247375 28.01289952154019 68.85060252579207 43.31205719227848 299.87126810633544 11.61306880834865 18.252461234999654 212.5721728441788 3194.861046053233 236.73664556643928 25.948464008499503 35.581296445444956 232.4617784572249 22.45275971726797 17.752485623682617 45.8804359907972 15.37942427561591 11.296385580182083 18.777720526627174 13.24093591350723 17.1865827620597 58.00633514371375 33.23012543402658 386.2798881440405 55.67001944518939 59.900528129884236 33.896493902047794 30.070859149215675 31.677324600515306 12.213930348409024 30.773612741976816 264.2535363538986 32.38706326065843 15.931261643728151 65.41399449027368 594.9284246559323 65.1887991887477 13.975208754586538 32.66666117506551 19.582933407798354 53.290183398151186 12.141836286292266 28.859476597225477 29.60862346312771 306.49565017458673 33.41935271643711 70.58338022712768 11.371905495459659 114.78296632581258 26.761089806100614 42.223349183044625 439.58506510570686 36.845182180194 15.868262855859347 20.58121126372009 59.36561245252003 13.050477695721042 29.085421338216218 32.27904166314857 38.983425440110516 30.98060933744976 14.698999226690857 11.7665588301951 11.332588053652222 25.870441472915832 68.27078272148016 18.248318612674662 11.233670503311659 376.4523934448496 37.53497928885321 53.217449535311886 26.34588882622621 14.129639822845123 18.99322619604263 24.385229554024786 12.048537141710357 175.71331792035585 30.58671147726447 11.442915308574975 1583.390584062315 46.712263993145825 17.678314620265738 261.3713217527722 88.07458645427783 20.69780008149513 18.616018949928208 15.425560331068077 15.764531599338108 12.438246334440889 58.643657093963775 53.845843425657876 36.97771312467952 22.65537695284087 17.777702097054473 23.783698278603683 49.72307085481615 24.42572426223563 34.73194961309841 210.11931529807043 44.97364437521372 73.18709461554697 70.12096847656072 14.809717822697777 15.899744087260553 16.632395050278493 12.532506742345788 13.019645219258411 13.972854431697504 11.57807313849385 220.15874649699643 659.6319943861866 42.745221085755965 140.777823571936 38.814635916085805 12.793183816678695 25.079531360037024 22.40377799442697 14.913564699104903 20.674442033139794 11.03167771150202 41.289113645851614 24.116321649808167 19.200925045981922 13.017973793636887 17.822667673835223 16.72543992003803 14.235814859294871 16.404845971600537 32.46633172138655 67.7453118489758 18.824535034044313 18.302016935200836 14.473907460383149 329.8209437923821 99.93863476058662 121.38962462905863 38.02127770104127 41.791725686618406 2824.652263720525 85.1884699938419 19.439610469587155 884.7102996182779 207.73339056150982 109.00121920548766 53.24978023564191 19.035632043933415 14.866557870963199 154.7408318971431 42.938331617576985
+batch04_S01_rep01_247_2_248_3_249 29.145804446154347 11.403257356162111 26.671321816272354 65.91472721557282 12.836481344761841 12.589077627524283 18.174340947535672 12.503269485340411 39.24309334626613 17.524176897031357 14.55250874417292 33.702422128429816 172.92629507894276 783.0955480760176 7890.742288561613 908.0847163397217 19.80037708341843 31.007337461395068 106.32318791039548 14.163165916988133 48.508016460110696 15.46594197170891 57.00207791406385 220.00847934187422 20.265189887912243 23.64314762466461 15.73938622044489 22.474819764854853 153.8046490125126 12.902672684596872 13.529289950527245 35.18005005483794 17.803237013058293 22.91072216920635 29.072511801888158 10.435581029054788 26.001983006564117 162.1758993249092 20.523978854006582 11.734970488934207 68.04667417044196 15.209997366072061 35.70823481568423 141.61804148226892 995.5159480566981 15.360056761719074 19.626739294854946 54.80574407550248 332.4198233912416 27.57146068694726 23.082504376575656 132.4055492901498 11.352536889069903 34.19246759587594 52.709599633192404 32.6931251553414 16.732183143852165 129.39223683334504 12.735173804314831 37.664226924806435 20.178098052354798 32.63022033422411 1650.12475841556 144.59618318393495 11.819937252289463 11.459531719137752 95.46652178986943 45.98850818681185 392.4324624347464 28.685306330470123 19.66277923411009 45.57751242122212 65.03369856223578 27.663583323038484 34.45283078135637 26.24089257798373 259.14730100803024 16.993272580010395 24.579201187435473 45.057380086635504 19.769360109557685 12.091783154572036 29.63671646056521 64.42305757073076 28.296074014644727 23.609207062634766 155.1323669617276 117.52891526562009 12.774927068360968 14.761445762695951 67.41343877441024 26.656919047591074 177.0126155010977 17.569721569882333 11.817399598394326 223.0044571955293 3526.0382083293966 263.4147490754906 22.028991460975703 41.00222805238901 249.86976272590354 11.42237162300078 18.59791776995712 35.34156945436025 14.238011877702322 11.289302661995595 20.939675362480823 11.52938652876898 14.148670284636568 113.37395153991798 30.49617058273766 358.7286777554346 41.224347513824036 44.238918822376824 30.905327105476847 18.246005079669917 32.321157990536726 11.764751030543003 17.96943139409716 161.90416918265475 19.544153742229074 16.42734118048151 70.83017548262067 646.9591141860177 71.68063879447885 11.671268297746115 49.64731982379532 37.00565159265913 42.83286034871188 11.52932426628371 22.962090677201655 27.44859289176055 290.6535913733465 31.68773047161383 62.67680088531491 11.468196944790535 121.15358078229941 19.171553035559757 23.262259705804468 223.97304645610822 19.119746382461162 13.010191891585634 12.533160144732772 84.52665085186352 11.999358657595645 23.38385451885196 21.708123951976614 54.443280861491054 32.58749038238159 27.284490940069862 13.252732897966391 14.525702481993328 23.3838038584064 20.32707051546949 14.538039938005511 16.828676369044985 220.24146495745495 22.09430838853324 30.024820758808584 16.170785108828955 15.862493269798813 42.28732580139026 13.52399702995943 51.33591276439305 395.2946071417642 68.84312568682064 28.643986350999295 3630.999610028613 31.991042660590484 55.450056633369876 546.0755933641905 182.0840733025534 41.59250978520138 31.80990575010578 32.195811531274494 11.590697418912091 11.395825193240068 45.26159311145779 58.49763388576406 33.46273357461692 12.998941237893646 13.038885147447058 13.509903069259614 21.08013837227028 18.311317666309577 89.9265129734 106.53471945494805 23.37536311599015 76.69939647108087 200.49225230573367 47.78644233041623 66.62160077707276 24.940088941581887 11.386196899968327 42.54436534925234 15.237082099161327 13.63603576582579 93.23941825083688 650.3651900055743 18.777507029959892 138.035814562545 38.08176346730567 12.20169222371279 131.63761137189343 39.203173988624656 14.97075981434991 25.978261386245816 19.270181242818552 21.128630855630842 54.76136776189306 15.192120491000578 16.121940831468994 12.98590780483278 13.687328272431008 22.461615744812274 24.53821393065536 16.372367422051937 55.74055916007458 16.286049449096613 12.412335455408789 11.25626577802412 552.476527126291 247.71627501660913 153.7884429505165 46.70596168901866 37.75444408713959 2497.7825988364466 82.13199686979547 17.502397199854265 777.6885047154927 181.7680519611231 95.84847856691711 46.76710816318723 14.433467449312426 11.59975438288337 306.0211220254601 83.72515304002712
\ No newline at end of file
diff -r 000000000000 -r a338f7319055 test-data/pls.h5
Binary file test-data/pls.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pls_QC18.h5
Binary file test-data/pls_QC18.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pls_rf.h5
Binary file test-data/pls_rf.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pls_scan5.h5
Binary file test-data/pls_scan5.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pm_as.h5
Binary file test-data/pm_as.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pm_as_bf.h5
Binary file test-data/pm_as_bf.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pm_as_bf_rmbs.h5
Binary file test-data/pm_as_bf_rmbs.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pm_as_bf_sf.h5
Binary file test-data/pm_as_bf_sf.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pm_as_bf_sf_mv.h5
Binary file test-data/pm_as_bf_sf_mv.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/pm_as_bf_sf_within.h5
Binary file test-data/pm_as_bf_sf_within.h5 has changed
diff -r 000000000000 -r a338f7319055 test-data/report_pls_01.xt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_01.xt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,73 @@
+filename event scans peaks median_rsd
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 125 8.164744871334845
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [140.00-240.00] 10 118 7.9168945392902135
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 66 7.686071240864687
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 59 7.357182338903599
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 38 7.810733023874823
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 31 7.113040692029466
+batch04_B02_rep01_301.mzML FTMS + p ESI w SIM ms [490.00-590.00] 14 45 6.300051388534287
+batch04_B02_rep01_301.mzML SIM-Stitch NA 482 7.768584373738055
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 128 8.076009915741135
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [140.00-240.00] 10 125 8.038649267793415
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 65 7.448888733736318
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 61 6.296572607068351
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 47 7.012719313185922
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 31 7.350041999095771
+batch04_B02_rep02_302.mzML FTMS + p ESI w SIM ms [490.00-590.00] 14 43 7.375664473847967
+batch04_B02_rep02_302.mzML SIM-Stitch NA 500 7.687154590676263
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 123 9.169351544578852
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [140.00-240.00] 10 118 7.554443758914416
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [210.00-310.00] 15 66 7.783516194269935
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 57 6.270569975489961
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 44 8.203805443231127
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 32 8.263278003056694
+batch04_B02_rep03_303.mzML FTMS + p ESI w SIM ms [490.00-590.00] 14 45 8.21592686599179
+batch04_B02_rep03_303.mzML SIM-Stitch NA 485 8.035526771916881
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 79 7.031966967936938
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 80 7.7676656135167175
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 61 8.153633358875439
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 54 6.064659199205902
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 38 6.249704967143267
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 19 7.423632652950013
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 38 7.08865209918093
+batch04_QC17_rep01_262.mzML SIM-Stitch NA 369 7.1854609699699745
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 77 7.679712527427614
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 76 7.4095987002251995
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 61 8.070077166892615
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [280.00-380.00] 15 53 6.56434715809076
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 43 6.0120617575086035
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 19 6.894796224726954
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 41 6.823399230382235
+batch04_QC17_rep02_263.mzML SIM-Stitch NA 370 7.3215340368881066
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 76 7.066844757552882
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 77 7.708127247443593
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 62 7.273819325368941
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 56 6.85168250470795
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 44 8.136951844903859
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 22 9.043103879106212
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 44 8.17119973043174
+batch04_QC17_rep03_264.mzML SIM-Stitch NA 381 7.638539899322612
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 67 6.94493393729959
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [140.00-240.00] 12 74 7.565621413380442
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 63 7.250184527315313
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [280.00-380.00] 15 51 6.834026481611651
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 46 6.8631168803092875
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 30 7.5643366272894745
+batch04_S01_rep01_247.mzML FTMS + p ESI w SIM ms [490.00-590.00] 14 47 7.383285889388576
+batch04_S01_rep01_247.mzML SIM-Stitch NA 378 7.204818271465472
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 68 7.6140232663257965
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 74 6.913828093334823
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [210.00-310.00] 15 63 7.810206749993205
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 52 6.671167067945765
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 49 7.47235757298909
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 29 9.180929326732146
+batch04_S01_rep02_248.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 50 7.4974332114539
+batch04_S01_rep02_248.mzML SIM-Stitch NA 385 7.447728173693162
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 70 8.140596594185261
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 72 6.7023463423858916
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 60 8.312209996466285
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [280.00-380.00] 15 51 6.643019115940489
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 48 6.599696065499092
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 30 7.38454762189305
+batch04_S01_rep03_249.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 50 9.086547438353602
+batch04_S01_rep03_249.mzML SIM-Stitch NA 381 7.563062708333447
diff -r 000000000000 -r a338f7319055 test-data/report_pls_02.xt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_02.xt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,25 @@
+filename event scans peaks median_rsd
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 62 9.106795765105987
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 66 8.376338250469699
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 30 13.860951930094206
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 43 11.995016644120462
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [350.00-450.00] 13 32 10.18681141686221
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 15 11.232655948051354
+batch04_QC18_rep01_280.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 24 14.164121165835418
+batch04_QC18_rep01_280.mzML SIM-Stitch NA 272 10.833932763925075
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 56 10.02227469296428
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 47 16.50748950248718
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 47 10.323122529981012
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 46 7.969584657178587
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 30 8.390974309393076
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [420.00-520.00] 12 16 9.67349503755467
+batch04_QC18_rep02_281.mzML FTMS + p ESI w SIM ms [490.00-590.00] 12 27 9.466647675517853
+batch04_QC18_rep02_281.mzML SIM-Stitch NA 269 10.06252290827951
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [70.00-170.00] 10 69 7.52328763290241
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [140.00-240.00] 11 71 7.905522565392167
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [210.00-310.00] 14 50 7.010930764188746
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [280.00-380.00] 14 49 7.247286414579351
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [350.00-450.00] 14 39 8.26255528557101
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [420.00-520.00] 13 20 8.483947267451931
+batch04_QC18_rep03_282.mzML FTMS + p ESI w SIM ms [490.00-590.00] 13 41 5.4612510154689105
+batch04_QC18_rep03_282.mzML SIM-Stitch NA 339 7.428907429907003
diff -r 000000000000 -r a338f7319055 test-data/report_pls_rf_01.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_rf_01.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
+name peaks peaks_3oo3 median_rsd_3oo3
+batch04_B02_rep01_301_2_302_3_303 487 421 12.335333490423352
+batch04_QC17_rep01_262_2_263_3_264 364 321 7.908538366075825
+batch04_S01_rep01_247_2_248_3_249 383 331 5.344215585775828
diff -r 000000000000 -r a338f7319055 test-data/report_pls_rf_02.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_rf_02.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,2 @@
+name peaks peaks_3oo3 median_rsd_3oo3
+batch04_QC17_rep01_262_2_263_3_264 15 15 8.602469347435797
diff -r 000000000000 -r a338f7319055 test-data/report_pls_scan5.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/report_pls_scan5.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
+filename event scans peaks median_rsd
+batch04_QC17_rep01_262.mzML FTMS + p ESI w SIM ms [70.00-170.00] 1 15 nan
+batch04_QC17_rep02_263.mzML FTMS + p ESI w SIM ms [70.00-170.00] 1 15 nan
+batch04_QC17_rep03_264.mzML FTMS + p ESI w SIM ms [70.00-170.00] 1 15 nan
diff -r 000000000000 -r a338f7319055 test-data/sample_list_after_bf.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/sample_list_after_bf.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,3 @@
+filename injectionOrder replicates classLabel
+batch04_QC17_rep01_262_2_263_3_264 4 1-2-3 QC
+batch04_S01_rep01_247_2_248_3_249 7 1-2-3 sample
diff -r 000000000000 -r a338f7319055 test-data/sample_list_after_mv_filter.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/sample_list_after_mv_filter.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,3 @@
+filename injectionOrder replicates classLabel
+batch04_QC17_rep01_262_2_263_3_264 4 1-2-3 QC
+batch04_S01_rep01_247_2_248_3_249 7 1-2-3 sample
diff -r 000000000000 -r a338f7319055 test-data/samplelist_1.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/samplelist_1.txt Wed Feb 17 10:49:33 2021 +0000
@@ -0,0 +1,4 @@
+filename injectionOrder replicates classLabel
+batch04_B02_rep01_301_2_302_3_303 1 1-2-3 blank
+batch04_QC17_rep01_262_2_263_3_264 4 1-2-3 QC
+batch04_S01_rep01_247_2_248_3_249 7 1-2-3 sample