annotate scran_normalize.xml @ 2:6864acb21714 draft default tip

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/gsc_scran_normalize commit a14fb3d106b647c4f1dea2c8d3ac7c1e8848b21c
author artbio
date Sun, 10 Dec 2023 00:27:45 +0000
parents fb2f1b8b0013
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6864acb21714 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/gsc_scran_normalize commit a14fb3d106b647c4f1dea2c8d3ac7c1e8848b21c
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1 <tool id="scran_normalize" name="scran_normalize" version="1.28.1+galaxy0">
0
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2 <description>Normalize raw counts expression values using deconvolution size factors</description>
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3 <requirements>
2
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4 <requirement type="package" version="1.28.1">bioconductor-scran</requirement>
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5 <requirement type="package" version="1.63_1">r-dynamictreecut</requirement>
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6 <requirement type="package" version="1.7.3">r-optparse</requirement>
0
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7 </requirements>
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8 <stdio>
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9 <exit_code range="1:" level="fatal" description="Tool exception" />
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10 </stdio>
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11 <command detect_errors="exit_code"><![CDATA[
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12 Rscript $__tool_directory__/scran-normalize.R
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13 --data '$input'
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14 #if $metacell.cluster == "Yes":
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15 --cluster
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16 --method '$metacell.method'
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17 --size '$metacell.size'
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18 #end if
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19 -o '${output}'
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20 ]]></command>
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21 <inputs>
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22 <param name="input" type="data" format="tabular" label="Raw counts of expression data" help = "A tsv file that must have an header line"/>
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23 <conditional name="metacell">
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24 <param name="cluster" type="select" label = "Do you want to cluster cells ?" help="Perform scaling method on metacell, see Details">
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25 <option value="Yes">Yes</option>
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26 <option value="No" selected="true">No</option>
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27 </param>
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28 <when value="Yes">
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29 <param name="method" type="select" label="Clustering method">
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30 <option value="hclust" selected="true">hclust</option>
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31 <option value="igraph">igprah</option>
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32 </param>
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33 <param name="size" type="integer" value="100" label="Minimum size of each cluster"/>
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34 </when>
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35 <when value="No"/>
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36 </conditional>
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37 </inputs>
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38 <outputs>
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39 <data name="output" format="tabular" label="Normalized Log counts of ${on_string}">
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40 </data>
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41 </outputs>
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42 <tests>
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43 <test>
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44 <param name="input" value="counts.tsv" ftype="tabular"/>
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45 <output name="output" file="logcounts.tsv" ftype="tabular"/>
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46 </test>
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47 <test>
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48 <param name="input" value="counts.tsv" ftype="tabular"/>
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49 <param name="cluster" value="Yes"/>
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50 <param name="method" value="igraph"/>
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51 <param name="size" value="25"/>
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52 <output name="output" file="logcounts_igraph.tsv" ftype="tabular"/>
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53 </test>
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54 <test>
2
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55 <param name="input" value="counts.tsv" ftype="tabular"/>
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56 <param name="cluster" value="Yes"/>
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57 <param name="method" value="hclust"/>
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58 <param name="size" value="25"/>
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59 <output name="output" file="logcounts_hclust.tsv" ftype="tabular"/>
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60 </test>
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61 </tests>
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62 <help>
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63
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64 **What it does**
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65
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66 Takes a raw count expression matrix and returns a table of log transformed scran-normalized expression values.
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67
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68 This computes size factors that are used to scale the counts in each cell. The assumption is that
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69 most genes are not differentially expressed (DE) between cells, such that any differences in
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70 expression across the majority of genes represents some technical bias that should be removed.
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71
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72 Cell-specific biases are normalized using the computeSumFactors method, which implements the
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73 deconvolution strategy for scaling normalization (A. T. Lun, Bach, and Marioni 2016). It creates a reference :
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74 - if no clustering step : the average count of all transcriptomes
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75 - if you choose to cluster your cells : the average count of each cluster.
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76 Then it pools cells and then sum their expression profiles. The size factor is described as the median ration
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77 between the count sums and the average across all genes. Finally it constructs a linear distribution (deconvolution method)
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78 of size factors by taking multiple pools of cells.
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79
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80 You can apply this method on cell cluster instead of your all set of cells by using quickCluster.
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81 It defines cluster using distances based on Spearman correlation on counts between cells, there is two available methods :
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82
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83 - *hclust* : hierarchical clustering on the distance matrix and dynamic tree cut.
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84 - *igraph* : constructs a Shared Nearest Neighbor graph (SNN) on the distance matrix and identifies highly connected communities.
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85
252eded61848 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit ddcf915dd9b690d7f3876e08b939adde36cbb8dd"
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86
252eded61848 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit ddcf915dd9b690d7f3876e08b939adde36cbb8dd"
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87 Note: First header row must NOT start with a '#' comment character
252eded61848 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit ddcf915dd9b690d7f3876e08b939adde36cbb8dd"
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88
252eded61848 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit ddcf915dd9b690d7f3876e08b939adde36cbb8dd"
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89 </help>
252eded61848 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit ddcf915dd9b690d7f3876e08b939adde36cbb8dd"
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90 <citations>
1
fb2f1b8b0013 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit e0357f07fdabee1ec6614aca6f7b51095111e0d5
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91 <citation type="doi">10.12688/f1000research.9501.2</citation>
0
252eded61848 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit ddcf915dd9b690d7f3876e08b939adde36cbb8dd"
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92 </citations>
252eded61848 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/gsc_scran_normalize commit ddcf915dd9b690d7f3876e08b939adde36cbb8dd"
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93 </tool>