Mercurial > repos > ebi-gxa > anndata_ops
view anndata_operations.xml @ 7:265348777440 draft
"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 |
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date | Thu, 12 Mar 2020 05:17:34 -0400 |
parents | d586ebb8ff43 |
children | b8eb50bd397c |
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<?xml version="1.0" encoding="utf-8"?> <tool id="anndata_ops" name="AnnData Operations" version="0.0.1+galaxy2" profile="@PROFILE@"> <description>modifies metadata and flags genes</description> <macros> <import>scanpy_macros2.xml</import> </macros> <expand macro="requirements"/> <command detect_errors="exit_code"><![CDATA[ ln -s '${input_obj_file}' input.h5 && python $operations ]]></command> <configfiles> <configfile name="operations"> import scanpy as sc import logging adata = sc.read('input.h5') gene_name = '${gene_symbols_field}' qc_vars = list() #for $i, $s in enumerate($modifications) adata.obs['${s.to_obs}'] = adata.obs['${s.from_obs}'] #end for gene_names = getattr(adata.var, gene_name) #for $i, $flag in enumerate($gene_flags) k_cat = gene_names.str.startswith('${flag.startswith}') if k_cat.sum() > 0: adata.var['${flag.flag}'] = k_cat qc_vars.append('${flag.flag}') else: logging.warning('No genes starting with {} found, skip calculating expression of {} genes'.format('${flag.startswith}', '${flag.flag}')) #end for if len(qc_vars) > 0: pct_top = [${top_genes}] sc.pp.calculate_qc_metrics(adata, qc_vars=qc_vars, percent_top=pct_top, inplace=True) if 'n_genes' not in adata.obs.columns: sc.pp.filter_cells(adata, min_genes=0) if 'n_counts' not in adata.obs.columns: sc.pp.filter_cells(adata, min_counts=0) if 'n_cells' not in adata.var.columns: sc.pp.filter_genes(adata, min_cells=0) if 'n_counts' not in adata.var.columns: sc.pp.filter_genes(adata, min_counts=0) adata.write('output.h5', compression='gzip') </configfile> </configfiles> <inputs> <param name="input_obj_file" argument="input-object-file" type="data" format="h5,h5ad" label="Input object in hdf5 AnnData format"/> <expand macro="output_object_params_no_loom"/> <repeat name="modifications" title="Change field names in AnnData observations" min="0"> <param name="from_obs" type="text" label="Original name" help="Name in observations that you want to change"> <sanitizer> <valid initial="string.printable"/> </sanitizer> </param> <param name="to_obs" type="text" label="New name" help="New name in observations that you want to change"/> </repeat> <param name="gene_symbols_field" value='index' type="text" label="Gene symbols field in AnnData" help="Field inside var.params where the gene symbols are, normally 'index' or 'gene_symbols'"/> <repeat name="gene_flags" title="Flag genes that start with these names"> <param name="startswith" type="text" label="Starts with" help="Text that you expect the genes to be flagged to start with, such as 'MT-' for mito genes"/> <param name="flag" type="text" label="Var name" help="Name of the column in var.names where this boolean flag is stored, for example 'mito' for mitochondrial genes."/> </repeat> <param name="top_genes" label="Number of top genes" value='50' help="to calculate percentage of the flagged genes in that number of top genes. Used by sc.pp.calculate_qc_metrics (integer)." type="integer"/> </inputs> <outputs> <expand macro="output_data_obj_no_loom" description="metadata changes on"/> </outputs> <tests> <test> <param name="input_obj_file" value="find_cluster.h5"/> <param name="input_format" value="anndata"/> <param name="color_by" value="louvain"/> <output name="output_h5ad" file="output.h5" ftype="h5" compare="sim_size"/> </test> </tests> <help><![CDATA[ ============================= Operations on AnnData objects ============================= Performs the following operations: * Change observation fields, mostly for downstreaming processes convenience. Multiple fields can be changed as one. * Flag genes that start with a certain text: useful for flagging mitochondrial, spikes or other groups of genes. * For the flags created, calculates qc metrics (pct_<flag>_counts). * Calculates `n_genes`, `n_counts` for cells and `n_cells`, `n_counts` for genes. * For top <N> genes specified, calculate qc metrics (pct_counts_in_top_<N>_genes). This functionality will probably be added in the future to a larger package. ]]></help> <expand macro="citations"/> </tool>