Mercurial > repos > ebi-gxa > scanpy_normalise_data

comparison scanpy-normalise-data.xml @ 1:5704635cef67 draft

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"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit ba0c88ab1b077a0b1c60c8d3c529e72ca6946226"
author ebi-gxa
date Thu, 12 Mar 2020 09:08:10 +0000
parents 19805a556cd6
children
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0:19805a556cd6 1:5704635cef67
1 <?xml version="1.0" encoding="utf-8"?> 1 <?xml version="1.0" encoding="utf-8"?>
2 <tool id="scanpy_normalise_data" name="Scanpy NormaliseData" version="@TOOL_VERSION@+galaxy0"> 2 <tool id="scanpy_normalise_data" name="Scanpy NormaliseData" version="@TOOL_VERSION@+galaxy10" profile="@PROFILE@">
3 <description>to make all cells having the same total expression</description> 3 <description>to make all cells having the same total expression</description>
4 <macros> 4 <macros>
5 <import>scanpy_macros.xml</import> 5 <import>scanpy_macros2.xml</import>
6 </macros> 6 </macros>
7 <expand macro="requirements"/> 7 <expand macro="requirements"/>
8 <command detect_errors="exit_code"><![CDATA[ 8 <command detect_errors="exit_code"><![CDATA[
9 ln -s '${input_obj_file}' input.h5 && 9 ln -s '${input_obj_file}' input.h5 &&
10 PYTHONIOENCODING=utf-8 scanpy-normalise-data.py 10 PYTHONIOENCODING=utf-8 scanpy-normalise-data
11 -i input.h5 11 --normalize-to ${scale_factor}
12 -f '${input_format}' 12 --fraction ${fraction}
13 -o output.h5 13 --save-raw ${save_raw}
14 -F '${output_format}' 14 ${log_transform}
15 -s '${scale_factor}' 15 @INPUT_OPTS@
16 #if $save_raw 16 @OUTPUT_OPTS@
17 '${save_raw}' 17 @EXPORT_MTX_OPTS@
18 #end if
19 ]]></command> 18 ]]></command>
20 19
21 <inputs> 20 <inputs>
22 <expand macro="input_object_params"/> 21 <expand macro="input_object_params"/>
23 <expand macro="output_object_params"/> 22 <expand macro="output_object_params"/>
24 <param name="scale_factor" argument="--scale-factor" type="float" value="1e4" label="Target number to normalise to"/> 23 <param name="scale_factor" argument="--normalize-to" type="float" value="1e4" min="0"
25 <param name="save_raw" argument="--save-raw" type="boolean" truevalue="--save-raw" falsevalue="" checked="true" label="Save pre-normalised data"/> 24 label="Target number to normalise to" help="Aimed counts per cell after normalisation."/>
25 <param name="fraction" argument="--fraction" type="float" value="1" min="0" max="1"
26 label="Exclude top expressed genes until the remaining account for no greater than specified fraction of total counts"
27 help="Only non-excluded genes will sum up the target number."/>
28 <param name="log_transform" argument="--no-log-transform" type="boolean" truevalue="" falsevalue="--no-log-transform" checked="True"
29 label="Apply log transform?" help="If enabled, will apply a log transformation following normalisation."/>
30 <param name="save_raw" argument="--save-raw" type="boolean" truevalue="yes" falsevalue="no" checked="true"
31 label="Save normalised data in `.raw`" help="The saved normalised data are log1p transformed."/>
32 <expand macro="export_mtx_params"/>
26 </inputs> 33 </inputs>
27 34
28 <outputs> 35 <outputs>
29 <data name="output_h5" format="h5" from_work_dir="output.h5" label="${tool.name} on ${on_string}: Normalized data" /> 36 <expand macro="output_data_obj" description="Normalised data"/>
37 <expand macro="export_mtx_outputs"/>
30 </outputs> 38 </outputs>
31 39
32 <tests> 40 <tests>
33 <test> 41 <test>
34 <param name="input_obj_file" value="filter_genes.h5"/> 42 <param name="input_obj_file" value="filter_genes.h5"/>
39 <output name="output_h5" file="normalise_data.h5" ftype="h5" compare="sim_size"/> 47 <output name="output_h5" file="normalise_data.h5" ftype="h5" compare="sim_size"/>
40 </test> 48 </test>
41 </tests> 49 </tests>
42 50
43 <help><![CDATA[ 51 <help><![CDATA[
44 ========================================================= 52 =============================================================
45 Normalize total counts per cell (`pp.normalize_per_cell`) 53 Normalise total counts per cell (`scanpy.pp.normalize_total`)
46 ========================================================= 54 =============================================================
47 55
48 Normalize each cell by total counts over all genes, so that every cell has 56 Normalise each cell by total counts over all genes (excluding top expressed
49 the same total count after normalization. 57 genes if so required), so that every cell has the same total count after
58 normalisation.
50 59
51 Similar functions are used, for example, by Seurat, Cell Ranger or SPRING. 60 Similar functions are used, for example, by Seurat, Cell Ranger or SPRING.
52 61
53 @HELP@ 62 @HELP@
54 63