Mercurial > repos > bgruening > hicexplorer_hictransform
view hicTransform.xml @ 18:1de2276f633f draft default tip
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/hicexplorer commit 79133bc3739fbcc6c2055d589679aae312161d03
author | iuc |
---|---|
date | Mon, 04 Nov 2024 23:51:37 +0000 |
parents | 27fe5cd1729c |
children |
line wrap: on
line source
<tool id="hicexplorer_hictransform" name="@BINARY@" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@"> <description>transform a matrix to obs/exp, pearson and covariance matrices</description> <macros> <token name="@BINARY@">hicTransform</token> <import>macros.xml</import> </macros> <expand macro="requirements" /> <command detect_errors="exit_code"><![CDATA[ ln -s '$matrix_h5_cooler' 'matrix.$matrix_h5_cooler.ext' && @BINARY@ --matrix 'matrix.$matrix_h5_cooler.ext' --method $method_selector #if $ligation_factor: $ligation_factor #end if $perChromosome #set chroms = ' '.join([ '\'' + str($var.chromosome) + '\'' for $var in $chromosomeOrder ]) #if chroms: --chromosomes $chroms #end if --outFileName 'out_matrix.$matrix_h5_cooler.ext' && mv 'out_matrix.$matrix_h5_cooler.ext' matrix ]]> </command> <inputs> <expand macro="matrix_h5_cooler_macro" /> <param name="method_selector" type="select" label="Choose method to apply"> <option value="obs_exp" selected="True">obs / exp</option> <option value="obs_exp_lieberman">obs / exp (Lieberman-Aiden 2009)</option> <option value="obs_exp_non_zero">obs / exp (exclude non-zero from exp)</option> <option value="pearson">pearson</option> <option value="covariance">covariance</option> </param> <param name="ligation_factor" type="boolean" truevalue="--ligation_factor" falsevalue="" checked="false" label="Multiplies a scaling factor to each entry of the expected matrix to take care of the proximity ligation" /> <param argument="--perChromosome" type="boolean" truevalue="--perChromosome" falsevalue="" checked="false" label="Computation per chromosome" /> <repeat name="chromosomeOrder" min="0" title="Chromosomes to include in the computation"> <param name="chromosome" type="text"> <validator type="empty_field" /> <validator type="expression" message="Only alphanumeric characters and the underscore can be used in chromosome names">value.replace('_', '').isalnum()</validator> </param> </repeat> </inputs> <outputs> <data name="matrix_out" from_work_dir="matrix" format="cool" label="${tool.name} on ${matrix_h5_cooler.name} [${on_string}]: $method_selector"> <change_format> <when input_dataset="matrix_h5_cooler" attribute="ext" value="h5" format="h5" /> </change_format> </data> </outputs> <tests> <test> <param name="matrix_h5_cooler" value="small_test_matrix.h5" /> <param name="method_selector" value="obs_exp_lieberman" /> <output name="matrix_out" ftype="h5"> <assert_contents> <has_h5_keys keys="intervals,matrix" /> </assert_contents> </output> </test> <test> <param name="matrix_h5_cooler" value="small_test_matrix.h5" /> <param name="method_selector" value="obs_exp_lieberman" /> <param name="ligation_factor" value="True" /> <output name="matrix_out" ftype="h5"> <assert_contents> <has_h5_keys keys="intervals,matrix" /> </assert_contents> </output> </test> </tests> <help><![CDATA[ Transformation of matrix for plotting ===================================== **hicTransform** computes a matrix based on one Hi-C contact matrix as input: - An **observed/expected matrix** obtained "by dividing each entry in the contact matrix by the genome-wide average contact probability for loci at that genomic distance" (`Lieberman-Aiden et al. (2009)`_). This transformation allows to better assess long range interactions. - An **observed/expected norm matrix** which computes the expected matrix as EXP_i,j = sum(diagonal(i-j)) * sum(row(j)) * sum(row(i)) / sum(matrix) - An **observed/expected non-zero values matrix** which computes the expected matrix as the sum per genomic distance j divided by sum of non-zero contacts: sum(diagonal(j) / number of non-zero elements in diagonal(j) - A **Pearson correlation matrix** obtained by computing the Pearson correlation between each bin based on observed/expected values. This matrix transformation allows to better identify the bins that are entering in contact together, or not, at long ranges, and thus helps defining compartments in the nucleus (``hicPCA``). - A **covariance matrix**, which is used as a basis for the Principal Component Analysis (PCA) to compute the eigenvectors outputed by **hicTransform**. These matrices can be used with ``hicPlotMatrix`` or ``pyGenomeTracks`` for a visualization of the A / B compartment analysis. _________________ Output ------ From one Hi-C contact matrix, **hicTransform** outputs a matrix with the selected method applied. _________________ | For more information about HiCExplorer please consider our documentation on readthedocs.io_ .. _readthedocs.io: http://hicexplorer.readthedocs.io/en/latest/index.html .. _`Lieberman-Aiden et al. (2009)`: https://pubmed.ncbi.nlm.nih.gov/19815776/ ]]> </help> <expand macro="citations" /> </tool>