Mercurial > repos > eschen42 > w4mclassfilter
changeset 12:518cc205f289 draft
planemo upload for repository https://github.com/HegemanLab/w4mclassfilter_galaxy_wrapper/tree/master commit aaa20ca94614124d11723bb906dee91636144d05
| author | eschen42 |
|---|---|
| date | Fri, 02 Mar 2018 08:29:53 -0500 |
| parents | ba427b16556a |
| children | b24ca78a425b |
| files | README w4mclassfilter.xml w4mclassfilter_wrapper.R |
| diffstat | 3 files changed, 246 insertions(+), 112 deletions(-) [+] |
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--- a/README Mon Jan 15 13:36:02 2018 -0500 +++ b/README Fri Mar 02 08:29:53 2018 -0500 @@ -1,7 +1,8 @@ Galaxy Wrapper for the w4mclassfilter R Package +<https://doi.org/10.5281/zenodo.1034793> -This is a planemo <http://planemo.readthedocs.io/en/latest/> -oriented galaxy-tool-wrapper <https://docs.galaxyproject.org/en/latest/dev/schema.htm> +This is a Galaxy tool-wrapper <https://docs.galaxyproject.org/en/latest/dev/schema.htm> to wrap the w4mclassfilter R package <https://github.com/HegemanLab/w4mclassfilter> for use with the Workflow4Metabolomics <http://workflow4metabolomics.org/> -flavor of Galaxy <https://galaxyproject.org/> +flavor of Galaxy <https://galaxyproject.org/>. +The tool is built with Planemo <http://planemo.readthedocs.io/en/latest/>.
--- a/w4mclassfilter.xml Mon Jan 15 13:36:02 2018 -0500 +++ b/w4mclassfilter.xml Fri Mar 02 08:29:53 2018 -0500 @@ -1,11 +1,13 @@ -<tool id="w4mclassfilter" name="Sample_Subset" version="0.98.6"> - <description>Filter W4M data by sample class</description> +<tool id="w4mclassfilter" name="W4m Data Subset" version="0.98.8"> + <description>Filter W4m data by values or metadata</description> + + <!-- Here is the hyphenation standard that I *try* to apply consistently in my documentation: http://www.sandranoonan.com/dont-let-hyphenation-drive-crazy/ --> <requirements> - <!-- <requirement type="package" version="6.2">readline</requirement> --> + <!-- <requirement type="package" version="6.2">readline</requirement> --> <requirement type="package" version="3.4.1">r-base</requirement> <requirement type="package" version="1.1_4">r-batch</requirement> - <requirement type="package" version="0.98.6">w4mclassfilter</requirement> + <requirement type="package" version="0.98.7">w4mclassfilter</requirement> </requirements> <stdio> @@ -22,8 +24,9 @@ inclusive '$inclusive' wildcards '$wildcards' classnameColumn '$classnameColumn' - samplenameColumn '$samplenameColumn' + samplenameColumn 'sampleMetadata' variable_range_filter '$variableRangeFilter' + transformation '$transformation' dataMatrix_out '$dataMatrix_out' sampleMetadata_out '$sampleMetadata_out' variableMetadata_out '$variableMetadata_out' @@ -33,12 +36,23 @@ <param name="dataMatrix_in" label="Data matrix file" type="data" format="tabular" help="variable x sample, decimal: '.', missing: NA, mode: numerical, separator: tab" /> <param name="sampleMetadata_in" label="Sample metadata file" type="data" format="tabular" help="sample x metadata columns, separator: tab" /> <param name="variableMetadata_in" label="Variable metadata file" type="data" format="tabular" help="variable x metadata columns, separator: tab" /> - <param name="samplenameColumn" label="Column that names the sample" type="text" value = "sampleMetadata" help="name of the column in the sample metadata file that has the name of the sample - defaults to 'sampleMetadata'" /> - <param name="classnameColumn" label="Column that names the sample-class" type="text" value = "class" help="name of the column in sample metadata that has the values to be tested against the 'classes' input parameter - defaults to 'class'" /> - <param name="sampleclassNames" label="Names of sample classes" type="text" value = "" help="comma-separated names (or comma-less regular expressions to match names) of sample-classes to filter in or out; defaults to no names"> + <param name="classnameColumn" label="Column that names the sample-class" type="text" value = "class" help="name of the column in sample metadata that has the values to be tested against the 'Names of sample-classes' input parameter - defaults to 'class'"> <sanitizer> <valid initial="string.letters"> <add preset="string.digits"/> + <add value="-" /> <!-- dash, hyphen --> + <add value="." /> <!-- dot, period --> + <add value="_" /> <!-- underscore --> + </valid> + </sanitizer> + </param> + <param name="sampleclassNames" label="Names of sample-classes" type="text" value = "" help="comma-separated names (or regular expressions to match names) of sample-classes to filter in or out; defaults to no names"> + <sanitizer> + <valid initial="string.letters"> + <add preset="string.digits"/> + <add value="{" /> <!-- l-cube, left-curly-bracket --> + <add value="|" /> <!-- pipe --> + <add value="}" /> <!-- r-cube, right-curly-bracket --> <add value="$" /> <!-- dollar, dollar-sign --> <add value="(" /> <!-- left-paren --> <add value=")" /> <!-- right-paren --> @@ -53,38 +67,42 @@ <add value="\" /> <!-- whack, backslash --> <add value="]" /> <!-- r-squib, right-squre-bracket --> <add value="^" /> <!-- hat, caret --> - <add value="{" /> <!-- l-cube, left-curly-bracket --> - <add value="|" /> <!-- pipe --> - <add value="}" /> <!-- r-cube, right-curly-bracket --> + <add value="_" /> <!-- underscore --> </valid> </sanitizer> </param> - <param name="wildcards" label="Use wild-cards or regular-expressions" type="select" help="wild-cards (the default) - use '*' and '?' to match class names; regular-expressions - use comma-less regular expressions to match class names"> + <param name="wildcards" label="Use 'wild cards' or 'regular expressions'" type="select" help="'wild-cards' (the default) - use '*' and '?' to match class names; 'regular-expressions' - use regular expressions to match class names"> <option value="TRUE" selected="true">wild-cards</option> <option value="FALSE">regular-expressions</option> </param> - <param name="inclusive" label="Include named classes" type="select" help="filter-in - include only the named sample classes; filter-out (the default) - exclude only the named sample classes"> + <param name="inclusive" label="Exclude/include named classes" type="select" help="'filter-out' (the default) - exclude only the named sample-classes; 'filter-in' - include only the named sample-classes"> <option value="TRUE">filter-in</option> <option value="FALSE" selected="true">filter-out</option> </param> - <param name="variableRangeFilter" label="Variable range-filters" type="text" value = "" help="comma-separated filters, each specified as 'variableMetadataColumnName:min:max'; default is no filters. (See help below.)"> + <param name="variableRangeFilter" label="Variable-range filters" type="text" value = "" help="comma-separated filters, each specified as 'variableMetadataColumnName:min:max'; default is no filters. (See help below.)"> <sanitizer> <valid initial="string.letters"> <add preset="string.digits"/> <add value="," /> <!-- comma --> + <add value="-" /> <!-- dash, hyphen --> + <add value="." /> <!-- dot, period --> <add value=":" /> <!-- colon --> - <add value="." /> <!-- dot, period --> + <add value="_" /> <!-- underscore --> </valid> </sanitizer> </param> + <param name="transformation" label="Data-transformation" type="select" help="'none' (the default) - do not transform data; 'log10' - log base 10 of data; in both cases, negative and missing values are imputed to zero"> + <option value="none" selected="true">none</option> + <option value="log10">log10</option> + </param> </inputs> <outputs> - <data name="dataMatrix_out" label="${tool.name}_${dataMatrix_in.name}" format="tabular" ></data> - <data name="sampleMetadata_out" label="${tool.name}_${sampleMetadata_in.name}" format="tabular" ></data> - <data name="variableMetadata_out" label="${tool.name}_${variableMetadata_in.name}" format="tabular" ></data> + <data name="dataMatrix_out" label="${dataMatrix_in.name}.subset" format="tabular" ></data> + <data name="sampleMetadata_out" label="${sampleMetadata_in.name}.subset" format="tabular" ></data> + <data name="variableMetadata_out" label="${variableMetadata_in.name}.subset" format="tabular" ></data> </outputs> <tests> @@ -92,10 +110,63 @@ <param name="dataMatrix_in" value="input_dataMatrix.tsv"/> <param name="sampleMetadata_in" value="input_sampleMetadata.tsv"/> <param name="variableMetadata_in" value="input_variableMetadata.tsv"/> + <param name="classnameColumn" value="gender"/> + <param name="sampleclassNames" value="M"/> + <param name="wildcards" value="FALSE"/> + <param name="inclusive" value="filter-in"/> + <param name="variableRangeFilter" value="FEATMAX:6.30103:,mz:200:,rt::800"/> + <param name="transformation" value="log10"/> + <output name="sampleMetadata_out"> + <assert_contents> + <not_has_text text="HU_028" /> + <not_has_text text="HU_051" /> + <not_has_text text="HU_060" /> + <not_has_text text="HU_110" /> + <not_has_text text="HU_149" /> + <not_has_text text="HU_152" /> + <not_has_text text="HU_175" /> + <not_has_text text="HU_178" /> + <not_has_text text="HU_185" /> + <not_has_text text="HU_204" /> + <not_has_text text="HU_208" /> + <has_text text="HU_017" /> + <has_text text="HU_034" /> + <has_text text="HU_078" /> + <has_text text="HU_091" /> + <has_text text="HU_093" /> + <has_text text="HU_099" /> + <has_text text="HU_130" /> + <has_text text="HU_134" /> + <has_text text="HU_138" /> + </assert_contents> + </output> + <output name="variableMetadata_out"> + <assert_contents> + <not_has_text text="HMDB00191" /> + <has_text text="HMDB00208" /> + <not_has_text text="HMDB00251" /> + <not_has_text text="HMDB00299" /> + <not_has_text text="HMDB00512" /> + <not_has_text text="HMDB00518" /> + <not_has_text text="HMDB00715" /> + <not_has_text text="HMDB00822" /> + <has_text text="HMDB01032" /> + <has_text text="HMDB01101.1" /> + <not_has_text text="HMDB03193" /> + <not_has_text text="HMDB04824" /> + <not_has_text text="HMDB10348" /> + <has_text text="HMDB13189" /> + <not_has_text text="HMDB59717" /> + </assert_contents> + </output> + </test> + <test> + <param name="dataMatrix_in" value="input_dataMatrix.tsv"/> + <param name="sampleMetadata_in" value="input_sampleMetadata.tsv"/> + <param name="variableMetadata_in" value="input_variableMetadata.tsv"/> <param name="classnameColumn" value="class"/> <param name="sampleclassNames" value=""/> <param name="wildcards" value="FALSE"/> - <param name="samplenameColumn" value="sampleMetadata"/> <param name="inclusive" value="filter-out"/> <param name="variableRangeFilter" value="FEATMAX:2e6:,mz:200:,rt::800"/> <output name="sampleMetadata_out"> @@ -148,7 +219,6 @@ <param name="variableMetadata_in" value="input_variableMetadata.tsv"/> <param name="classnameColumn" value="gender"/> <param name="sampleclassNames" value="M"/> - <param name="samplenameColumn" value="sampleMetadata"/> <param name="inclusive" value="filter-in"/> <output name="dataMatrix_out"> <assert_contents> @@ -198,7 +268,6 @@ <param name="classnameColumn" value="gender"/> <param name="sampleclassNames" value="*"/> <param name="wildcards" value="TRUE"/> - <param name="samplenameColumn" value="sampleMetadata"/> <param name="inclusive" value="filter-in"/> <output name="sampleMetadata_out"> <assert_contents> @@ -232,7 +301,6 @@ <param name="classnameColumn" value="gender"/> <param name="sampleclassNames" value="M"/> <param name="wildcards" value="FALSE"/> - <param name="samplenameColumn" value="sampleMetadata"/> <param name="inclusive" value="filter-in"/> <output name="sampleMetadata_out"> <assert_contents> @@ -266,7 +334,6 @@ <param name="classnameColumn" value="gender"/> <param name="sampleclassNames" value="M"/> <param name="wildcards" value="FALSE"/> - <param name="samplenameColumn" value="sampleMetadata"/> <param name="inclusive" value="filter-in"/> <output name="variableMetadata_out"> <assert_contents> @@ -296,7 +363,6 @@ <param name="classnameColumn" value="gender"/> <param name="sampleclassNames" value="M"/> <param name="wildcards" value="FALSE"/> - <param name="samplenameColumn" value="sampleMetadata"/> <param name="inclusive" value="filter-in"/> <output name="variableMetadata_out"> <assert_contents> @@ -326,7 +392,6 @@ <param name="classnameColumn" value="gender"/> <param name="sampleclassNames" value="[Mm],[fF]"/> <param name="wildcards" value="FALSE"/> - <param name="samplenameColumn" value="sampleMetadata"/> <param name="inclusive" value="filter-in"/> <output name="sampleMetadata_out"> <assert_contents> @@ -360,7 +425,6 @@ <param name="classnameColumn" value=""/> <param name="sampleclassNames" value="M"/> <param name="wildcards" value="FALSE"/> - <param name="samplenameColumn" value="sampleMetadata"/> <param name="inclusive" value="filter-in"/> <output name="sampleMetadata_out"> <assert_contents> @@ -401,7 +465,7 @@ **R package** -The *w4mclassfilter* package is available from the Hegeman lab github repository (https://github.com/HegemanLab/w4mclassfilter/releases). +The *w4mclassfilter* package (which is used by the W4m Data Subset tool) is available from the Hegeman lab github repository (https://github.com/HegemanLab/w4mclassfilter/releases). ----------------------------------------------------------------------------------------------------------------------------------------- @@ -412,44 +476,67 @@ --------------------------------------------------- -============================================== -Filter Workflow4Metabolomics data matrix files -============================================== +=========================================================== +"W4m Data Subset" - Filter Workflow4Metabolomics data files +=========================================================== + +---------- +Motivation +---------- + +GC-MS and LC-MS experiments seek to resolve as features chemicals that have distinct chromatographic retention-time ("rt") and (after ionization) mass-to-charge ratio ("m/z" or "mz"). +(If the MS protocol includes fragmentation, several features may result for each chemical.) +Data for a sample are collected as MS intensities, each of which is associated with a position on a 2D plane with dimensions of rt and m/z. +Ideally, features would be sufficiently reproducible among sample-runs to distinguish features that are commmon among samples from those that differ. + +The chromatographic retention-time for a chemical can vary from one chromatography run to the next. +Workflow4Metabolomics (W4m, [Giacomoni *et al.*, 2014, Guitton *et al.* 2017]) is a "flavor" of Galaxy that uses the XCMS preprocessing tools for "retention-time correction" to align features among samples. +Features may be better aligned if pooled samples and blanks are included. + +Multivariate statistical techniques may be used to discover clusters of similar samples (Th]]>é<![CDATA[venot *et al.*, 2015). +However, once retention-time alignment of features has been achieved among samples in GC-MS and LC-MS datasets: + +- The presence of pools and blanks may confound identification and separation of clusters. +- Multivariate statistical algorithms may be impacted by missing values or dimensions that have zero variance. ----------- Description ----------- -Filter a set of retention-corrected W4M files (dataMatrix, sampleMetadata, variableMetadata) by sample-class +The **W4m Data Subset** tool **selects subsets of samples, features, or data values** for further analysis. + +- The tool takes as input the data matrix, sample metadata, and variable metadata datasets produced by W4m's XCMS [Smith *et al.*, 2006] and CAMERA [Kuhl *et al.*, 2012] tools. +- The tool produces the same trio of output datasets, modified as follows. + +This tool can perform several operations to reduce the number samples or features to be analyzed (although **this should be done only in a statistically sound manner** consistent with the nature of the experiment): + +- Samples may be eliminated by filtering on a designated “sample class” column in sampleMetadata. +- Features may be eliminated by specifying minimum or maximum value (or both) allowable in columns of variableMetadata. +- Features may be eliminated by “range of row-maximum for each feature”, i.e., by specifying minimum or maximum intensity (or both) allowable in each row of the dataMatrix (i.e., for the feature across all samples). + +This tool also performs several operations to address several data issues that may impede downstream statistical analysis: + +- Missing values in dataMatrix are imputed to zero. +- The values in the dataMatrix may be log-transformed if desired. +- Samples that are missing from either sampleMetadata or dataMatrix are eliminated. +- Features that are missing from either variableMetadata or dataMatrix are eliminated. +- Features and samples that have zero variance are eliminated. +- Samples and features are sorted alphabetically in rows and columns of dataMatrix and in rows of variableMetadata and sampleMetadata. +- The names of the first columns of variableMetadata and sampleMetadata are set respectively to "variableMetadata" and "sampleMetadata". + +This tool may be applied several times sequentially, which may be useful for: + +- analyzing subsets of samples for progressively smaller sets of treatment-levels, or +- choosing subsets of samples based on criteria in several columns of the sampleMetadata table. ----------------- Workflow Position ----------------- -- Upstream tool category: Preprocessing -- Downstream tool categories: Normalisation, Statistical Analysis, Quality Control, Filter and Sort - ----------- -Motivation ----------- +This tool can be used at any point downstream of Preprocessing. -GC-MS1 and LC-MS1 experiments seek to resolve chemicals as features that have distinct chromatographic behavior and (after ionization) mass-to-charge ratio. -Data for a sample are collected as MS intensities, each of which is associated with a position on a 2D plane with dimensions of m/z ratio and chromatographic retention time. -Ideally, features would be sufficiently reproducible from sample-run to sample-run to identify features that are commmon among samples and those that differ. -However, the chromatographic retention time for a chemical can vary from one run to another. -In the Workflow4Metabolomics (W4M, [Giacomoni *et al.*, 2014, Guitton *et al.* 2017]) "flavor" of Galaxy, the XCMS [Smith *et al.*, 2006] preprocessing tools provide for "retention time correction" to align features among samples, but features may be better aligned if pooled samples and blanks are included. - -Multivariate statistical techniques may be used to discover clusters of similar samples, and sometimes it is desirable to apply clustering iteratively to smaller and smaller subsets of samples until observable separation of clusters is no longer significant. -Once feature-alignment has been achieved among samples in GC-MS and LC-MS datasets, however, the presence of pools and blanks may confound identification and separation of clusters. -Multivariate statistical algorithms also may be impacted by missing values or dimensions that have zero variance (Thévenot *et al.*, 2015). - -The w4mclassfilter tool provides a way to choose subsets of samples for further analysis. -The tool takes as input the data matrix, sample metadata, and variable metadata Galaxy datasets produced by W4M and produces the same trio of datasets with data only for the selected samples. -The tool uses a "sample-class" column in the sample metadata as the basis for including or eliminating samples for further analysis. -Class-values to be considered are provided by the user as a comma-separated list. -The user also provides an indication whether the list specifies classes to be included in further analysis ("filter-in") or rather to be excluded from it ("filter-out"). -Next, missing and negative intensites for features of the remaining samples are imputed to zero. -Finally, samples or features with zero variance are eliminated. +- Possible upstream tool categories: Preprocessing, Quality Control, Statistical Analysis, Filter and Sort +- Possible downstream tool categories: Normalisation, Statistical Analysis, Quality Control, Filter and Sort ----------- Input files @@ -471,7 +558,7 @@ ---------- Data matrix file - | variable x sample **dataMatrix** (tabular separated values) file of the numeric data matrix, with . as decimal, and NA for missing values; the table must not contain metadata apart from row and column names; the row and column names must be identical to the rownames of the sample and variable metadata, respectively (see below) + | variable x sample **dataMatrix** (tabular separated values) file of the numeric data matrix, with . as decimal, and NA for missing values; the table must not contain metadata apart from row and column names; the row and column names must be identical, respectively, to the rownames of the sample metadata file and variable metadata file | Sample metadata file @@ -482,57 +569,57 @@ | variable x metadata **variableMetadata** (tabular separated values) file of the numeric and/or character variable metadata, with . as decimal and NA for missing values | -Column that names the sample (default = '``sampleMetadata``') - | name of the column in sample metadata that has the name of the sample +Column that names the sample-class (default = '``class``') + | name of the column in **sampleMetadata** that has the values to be tested against the '``Names of sample-classes``' input parameter | -Column that names the sample-class (default = '``class``') - | name of the column in sample metadata that has the values to be tested against the '``classes``' input parameter +Names of sample-classes (default = no names) + | comma-separated names (or regular expressions to match names) of sample-classes to include or exclude | -Names of sample classes (default = no names) - | comma-separated names of sample classes to include or exclude +'Wild cards' or 'regular expressions' (default = '``wild-cards``') + | '``wild-cards``' - use wild cards to match names of sample-classes (see the 'Wild card patterns to match class-names' section below) + | '``regular-expressions``' - use regular expressions to match the named sample-classes (see the 'Regular expression patterns to match class-names' section below) | -Wild-cards (default = '``wild-cards``') - | '``wild-cards``' - use wild-cards to match names of sample classes (see 'Wild card patterns to match class-names' below) - | '``regular-expressions``' - exclude only the named sample classes (see 'Regular expression patterns to match class-names' below) - | - -Include named classes (default = '``filter-out``') - | '``filter-in``' - include only the named sample classes - | '``filter-out``' - exclude only the named sample classes +Exclude/include named classes (default = '``filter-out``') + | '``filter-in``' - include only the named sample-classes + | '``filter-out``' - exclude only the named sample-classes | Variable-range filters (default = no filters) - | comma-separated names of variable-range filters (see 'Variable-range filters' below) + | comma-separated names of variable-range filters (see the 'Variable-range filters' section below) | +Data-transformation (default = '``none``') + | '``none``' - do not transform data matrix values + | '``log10``' - take the log base 10 of the values in the data matrix + | In both cases, negative and missing values are imputed to zero. + | ------------ Output files ------------ - sampleMetadata - | (tabular separated values) file identical to the **sampleMetadata** file given as an input argument, excepting lacking rows for samples (xC-MS features) that have been filtered out (by the sample-class filter or because of zero variance) + | (tabular separated values) file identical to the **sampleMetadata** file given as an input argument, excepting lacking rows for samples that have been filtered out (by the sample-class filter, or because of zero variance, or because they were missing in the input data matrix) | variableMetadata - | (tabular separated values) file identical to the **variableMetadata** file given as an input argument, excepting lacking rows for variables (xC-MS features) that have been filtered out (because of zero variance) + | (tabular separated values) file identical to the **variableMetadata** file given as an input argument, excepting lacking rows for variables (xC-MS features) that have been filtered out (by the variable-range filter, or because of zero variance, or because they were missing in the input data matrix) | dataMatrix - | (tabular separated values) file identical to the **dataMatrix** file given as an input argument, excepting lacking rows for variables (xC-MS features) that have been filtered out (because of zero variance) and columns that have been filtered out (by the sample-class filter or because of zero variance) + | (tabular separated values) file identical to the **dataMatrix** file given as an input argument, excepting lacking rows and columns for variables and samples that have been filtered out, respectively | ---------------------------------------- -Wild card patterns to match class-names ---------------------------------------- +----------------------------------------- +'Wild card' patterns to match class-names +----------------------------------------- -Beginning with v0.98.2, w4mclassfilter supports use of R "wild card" patterns to select class-names. +W4m Data Subset supports use of R "wild card" patterns to select class-names. - use '``?``' to match a single character - use '``*``' to match zero or more characters @@ -544,11 +631,11 @@ - '``*.sample``' matches '``my.sample``' and '``my.own.sample``' - '``*.sampl``' matches neither '``my.sample``' nor '``my.own.sample``' ------------------------------------------------- -Regular expression patterns to match class-names ------------------------------------------------- +-------------------------------------------------- +'Regular expression' patterns to match class-names +-------------------------------------------------- -Beginning with v0.98.2, w4mclassfilter supports use of R "regular expression" patterns to select class-names. +W4m Data Subset supports use of R "regular expression" patterns to select class-names. R uses POSIX 1003.2 standard regular expressions, which allow precise pattern-matching and are exhaustively defined at: http://pubs.opengroup.org/onlinepubs/9699919799/basedefs/V1_chap09.html @@ -640,14 +727,12 @@ +------------------------------------+-----------------+ | Input Parameter | Value | +====================================+=================+ -| Names of sample classes | M | +| Names of sample-classes | M | +------------------------------------+-----------------+ | Include named classes | filter-in | +------------------------------------+-----------------+ | Column that names the sample-class | gender | +------------------------------------+-----------------+ -| Column that names the sample | sampleMetadata | -+------------------------------------+-----------------+ **Expected outputs** @@ -675,14 +760,12 @@ +------------------------------------+-------------------------------+ | Input Parameter | Value | +====================================+===============================+ -| Names of sample classes | (Leave this field empty.) | +| Names of sample-classes | (Leave this field empty.) | +------------------------------------+-------------------------------+ | Include named classes | filter-out | +------------------------------------+-------------------------------+ | Column that names the sample-class | class | +------------------------------------+-------------------------------+ -| Column that names the sample | sampleMetadata | -+------------------------------------+-------------------------------+ | Variable range-filters | FEATMAX:2e6:,mz:200:,rt::800 | +------------------------------------+-------------------------------+ @@ -704,66 +787,91 @@ NEWS ---- +Changes in version 0.98.8 +========================= + +New features + +- The tool now appears in Galaxy with a new, more representative name: "W4m Data Subset". (Earlier versions of this tool appeared in Galaxy with the name "Sample Subset".) +- Option was added to log-transform data matrix values. +- Output datasets are named in conformance with the W4m convention of appending the name of each preprocessing tool to the input dataset name. +- Superflous "Column that names the sample" input parameter was eliminated. +- Some documentation was updated or clarified. + +Internal modifications + +- None + +Changes in version 0.98.7 +========================= + +New features + +- First column of output variableMetadata (that has feature names) now is always named "variableMetadata". +- First column of output sampleMetadata now (that has sample names) now is always named "sampleMetadata". + +Internal modifications + +- Now uses w4mclassfilter R package v0.98.7. + Changes in version 0.98.6 ========================= New features -* Added support for filtering out features whose attributes fall outside specified ranges. +- Added support for filtering out features whose attributes fall outside specified ranges. For more detail, see "Variable-range filters" above. Internal modifications -* Now uses w4mclassfilter R package v0.98.6. -* Now sorts sample names and feature names in output files because some statistical tools expect the same order in `dataMatrix` row and column names as in the corresponding metadata files. +- Now uses w4mclassfilter R package v0.98.6. +- Now sorts sample names and feature names in output files because some statistical tools expect the same order in `dataMatrix` row and column names as in the corresponding metadata files. Changes in version 0.98.3 ========================= Internal modifications -* Improved input handling. -* Now uses w4mclassfilter R package v0.98.3, although that version has no functional implications for this tool. -* Improved reference-list. +- Improved input handling. +- Now uses w4mclassfilter R package v0.98.3, although that version has no functional implications for this tool. +- Improved reference-list. Changes in version 0.98.2 ========================= New features -* Added support for R-flavored regular expression pattern-matching when selecting names of sample-classes. -* Empty classes argument or zero-length class_column result in no samples filtered out. +- Added support for R-flavored regular expression pattern-matching when selecting names of sample-classes. +- Empty classes argument or zero-length class_column result in no samples filtered out. Internal modifications -* Support and tests for new features. +- Support and tests for new features. Changes in version 0.98.1 ========================= -First release - Wrap the w4mclassfilter R package that implements filtering of W4M data matrix, variable metadata, and sample metadata by class of sample. +First release - Wrap the w4mclassfilter R package that implements filtering of W4m data matrix, variable metadata, and sample metadata by class of sample. New features -* *dataMatrix* *is* modified by the tool, so it *does* appear as an output file -* *sampleMetadata* *is* modified by the tool, so it *does* appear as an output file -* *variableMetadata* *is* modified by the tool, so it *does* appear as an output file - -Internal modifications - -* N/A +- Output *dataMatrix* is input dataMatrix as modified by the tool +- Output *sampleMetadata* is input sampleMetadata as modified by the tool +- Output *variableMetadata* is input variableMetadata as modified by the tool ]]></help> <citations> - <!-- Giacomoni_2014 W4M 2.5 --> + <!-- Giacomoni_2014 W4m 2.5 --> <citation type="doi">10.1093/bioinformatics/btu813</citation> - <!-- Guitton_2017 W4M 3.0 --> + <!-- Guitton_2017 W4m 3.0 --> <citation type="doi">10.1016/j.biocel.2017.07.002</citation> + <!-- Kuhl_2012 CAMERA --> + <citation type="doi">10.1021/ac202450g</citation> <!-- Smith_2006 XCMS --> <citation type="doi">10.1021/ac051437y</citation> - <!-- Th_venot_2015 Urinary metabolome statistics --> + <!-- Thevenot_2015 Urinary metabolome statistics --> <citation type="doi">10.1021/acs.jproteome.5b00354</citation> </citations> <!-- - vim:noet:sw=4:ts=4 + vim:noet:sw=2:ts=2 --> </tool>
--- a/w4mclassfilter_wrapper.R Mon Jan 15 13:36:02 2018 -0500 +++ b/w4mclassfilter_wrapper.R Fri Mar 02 08:29:53 2018 -0500 @@ -82,6 +82,7 @@ # other parameters +transformation <- as.character(argVc["transformation"]) wildcards <- as.logical(argVc["wildcards"]) sampleclassNames <- as.character(argVc["sampleclassNames"]) sampleclassNames <- strsplit(x = sampleclassNames, split = ",", fixed = TRUE)[[1]] @@ -96,6 +97,29 @@ variable_range_filter <- as.character(argVc["variable_range_filter"]) variable_range_filter <- strsplit(x = variable_range_filter, split = ",", fixed = TRUE)[[1]] +## ----------------------------- +## Transformation and imputation +## ----------------------------- +my_w4m_filter_imputation <- if (transformation == "log10") { + function(m) { + suppressWarnings( + # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step + m <- log10(m) + ) + # replace NaN values with zero + m[is.nan(m)] <- 0 + # replace NA values with zero + m[is.na(m)] <- 0 + # replace negative values with zero, if applicable (It should never be applicable!) + m[m<0] <- 0 + # return matrix as the result + return (m) + } +} else { + # use the method from the w4mclassfilter class + w4m_filter_imputation +} + ##------------------------------ ## Computation ##------------------------------ @@ -113,6 +137,7 @@ , samplename_column = samplenameColumn , variable_range_filter = variable_range_filter , failure_action = my_print +, data_imputation = my_w4m_filter_imputation ) my_print("\nResult of '", modNamC, "' Galaxy module call to 'w4mclassfilter::w4m_filter_by_sample_class' R function: ",