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comparison scanpy-multiplet-scrublet.xml @ 7:2f9517a24c73 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 ee197a80b2d591c393e1662854bc119b2ecab11e-dirty
author ebi-gxa
date Tue, 27 Feb 2024 16:42:08 +0000
parents fadc4fbf8025
children 53ce0e336840
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6:fadc4fbf8025 7:2f9517a24c73
1 <?xml version="1.0" encoding="utf-8"?> 1 <?xml version="1.0" encoding="utf-8"?>
2 <tool id="scanpy_multiplet_scrublet" name="Scanpy Scrublet" version="@TOOL_VERSION@+galaxy93" profile="@PROFILE@"> 2 <tool id="scanpy_multiplet_scrublet" name="Scanpy Scrublet" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@">
3 <description>remove multiplets from annData objects with Scrublet</description> 3 <description>remove multiplets from annData objects with Scrublet</description>
4 <macros> 4 <macros>
5 <import>scanpy_macros2.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-multiplet scrublet 10 PYTHONIOENCODING=utf-8 scanpy-cli multiplet scrublet
11 #if $threshold 11 #if $threshold
12 --threshold '${threshold}' 12 --threshold '${threshold}'
13 #end if 13 #end if
14 #if $batch_key 14 #if $batch_key
15 --batch-key '${batch_key}' 15 --batch-key '${batch_key}'
101 <tests> 101 <tests>
102 <test> 102 <test>
103 <param name="input_obj_file" value="read_10x.h5"/> 103 <param name="input_obj_file" value="read_10x.h5"/>
104 <param name="input_format" value="anndata"/> 104 <param name="input_format" value="anndata"/>
105 <param name="output_format" value="anndata"/> 105 <param name="output_format" value="anndata"/>
106 <output name="output_h5" file="scrublet.h5" ftype="h5" compare="sim_size"/> 106 <output name="output_h5" file="scrublet.h5" ftype="h5" compare="sim_size" delta_frac="0.1"/>
107 </test> 107 </test>
108 </tests> 108 </tests>
109 109
110 <help><![CDATA[ 110 <help><![CDATA[
111 .. class:: infomark 111 .. class:: infomark
112 112
113 **What it does** 113 **What it does**
114 114
115 Predict cell doublets using a nearest-neighbor classifier of observed transcriptomes and simulated doublets. Works best if the input is a raw (unnormalized) counts matrix from a single sample or a collection of similar samples from the same experiment. This function is a wrapper around functions that pre-process using Scanpy and directly call functions of Scrublet(). 115 Predict cell doublets using a nearest-neighbor classifier of observed transcriptomes and simulated doublets. Works best if the input is a raw (unnormalized) counts matrix from a single sample or a collection of similar samples from the same experiment. This function is a wrapper around functions that pre-process using Scanpy and directly call functions of Scrublet().
116 116
117 This is a wrapper around the Scanpy wrapper for Scrublet- see https://scanpy.readthedocs.io/en/docsearch/external/scanpy.external.pp.scrublet.html. 117 This is a wrapper around the Scanpy wrapper for Scrublet- see https://scanpy.readthedocs.io/en/stable/generated/scanpy.external.pp.scrublet.html.
118 118
119 **Note** 119 **Note**
120 120
121 Where a threshold is not provided, Scrublet will try to automatically set one based on simulations, but this does not always work. There will be a warning, and no 'threshold' slot will be populated in .uns['scrublet']. The 'predicted_doublets' slot in .obs will be set to False for all cells such that no filtering will occur if this column is supplied to filtering steps. You can use the 'Scanpy Plot Scrublet' tool to plot the distribution of scores yourself and estimate a threshold to override this behaviour. 121 Where a threshold is not provided, Scrublet will try to automatically set one based on simulations, but this does not always work. There will be a warning, and no 'threshold' slot will be populated in .uns['scrublet']. The 'predicted_doublets' slot in .obs will be set to False for all cells such that no filtering will occur if this column is supplied to filtering steps. You can use the 'Scanpy Plot Scrublet' tool to plot the distribution of scores yourself and estimate a threshold to override this behaviour.
122 122