comparison anndata_operations.xml @ 27:7ebc22f77d86 draft

planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 2db372e91d658f2c139ff282ffb493ea56f581f8-dirty

26:825dfd66e3fb

<?xml version="1.0" encoding="utf-8"?>
<tool id="anndata_ops" name="AnnData Operations" version="@TOOL_VERSION@+galaxy9" profile="@PROFILE@">
  <description>modifies metadata and flags genes</description>
  <macros>
    <import>scanpy_macros2.xml</import>
  </macros>
  <expand macro="requirements"/>

#if $copy_u.default:
#for $i, $us in enumerate($copy_u.uns_sources):
  ln -s '${us}' uns_source_${i}.h5 &&
#end for
#end if
python $operations
]]></command>
  <configfiles>
    <configfile name="operations">

  if new_field is None:
    new_field = f"{field}_u"
  appendents = (suffix + df.groupby(field).cumcount().astype(str).replace('0','')).replace(suffix, '')
  df[new_field] = df[field].astype(str) + appendents.astype(str)
  return df

adata = sc.read('input.h5')

#if $copy_adata_to_raw:
adata.raw = adata
#end if

</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"/>
    <param name="copy_adata_to_raw" type="boolean" label="Copy AnnData to .raw" help="If activated, it will do 'adata.raw = adata'" checked="false"/>
    <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"/>

        </assert_contents>
      </output>
    </test>
    <test>
      <param name="input_obj_file" value="anndata_ops.h5"/>
      <repeat name="var_modifications" >
        <param name="from_var" value = "gene_symbols" />
        <param name="to_var" value = "gene_symbols_unique" />
        <param name="make_unique" value = "True" />
      </repeat>

27:7ebc22f77d86

<?xml version="1.0" encoding="utf-8"?>
<tool id="anndata_ops" name="AnnData Operations" version="@TOOL_VERSION@+galaxy91" profile="@PROFILE@">
  <description>modifies metadata and flags genes</description>
  <macros>
    <import>scanpy_macros2.xml</import>
  </macros>
  <expand macro="requirements"/>

#if $copy_u.default:
#for $i, $us in enumerate($copy_u.uns_sources):
  ln -s '${us}' uns_source_${i}.h5 &&
#end for
#end if

#if $add_cell_metadata.default:
  ln -s ${add_cell_metadata.file} cell_metadata.tsv &&
#end if
python $operations
]]></command>
  <configfiles>
    <configfile name="operations">

  if new_field is None:
    new_field = f"{field}_u"
  appendents = (suffix + df.groupby(field).cumcount().astype(str).replace('0','')).replace(suffix, '')
  df[new_field] = df[field].astype(str) + appendents.astype(str)
  return df
	    
adata = sc.read('input.h5')

#if $add_cell_metadata.default:
import pandas as pd

def add_cell_metadata(ad, metadata_file="cell_metadata.tsv", drop_duplicates=True):
  metadata_df = pd.read_csv(metadata_file, sep="\t", index_col=0)
  # we avoid renames in the original object or outright drop the column in the metadata
  for col in ad.obs.columns:
      if col in metadata_df.columns:
          print(f"Renaming {col} to {col}_x")
          if drop_duplicates:
              metadata_df = metadata_df.drop(col, axis=1)
          else:
              metadata_df.rename(columns={col: col + "_x"}, inplace=True)
  # merge metadata into ad.obs column by column, changing columns to category dtype if they become object dtype on merge
  merged_obs = ad.obs.merge(
      metadata_df, left_index=True, right_index=True, how="left"
  )
  for o_col in metadata_df.columns:
      col = o_col
      # lets consider cases where columns where renamed during merge
      if o_col + "_x" in merged_obs.columns:
          col = o_col + "_x"
      if o_col + "_y" in merged_obs.columns:
          col = o_col + "_y"
      if col in merged_obs.columns:
          if merged_obs[col].dtype == object:
              prev_dtype = metadata_df[o_col].dtype
              if prev_dtype == str or prev_dtype == object:
                  prev_dtype = "category"
              print(f"Changing {col} from {merged_obs[col].dtype} to {prev_dtype}")
              merged_obs[col] = merged_obs[col].astype(prev_dtype)
  return merged_obs
	    
adata.obs = add_cell_metadata(adata)
#end if

#if $copy_adata_to_raw:
adata.raw = adata
#end if

</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"/>
    <conditional name="add_cell_metadata">
      <param name="default" type="boolean" checked="false" label="Merge additional cell metadata"/>
      <when value="true">
        <param name="file" type="data" label="Cell metadata with headers" help="A tabular file with headers, where the first column contains cell barcodes. Will be merged via a left join, so not all cells in the obs need to be in the metadata. Currently duplicated column headers will be ignored and the originals in the AnnData will be kept." format="tsv,tabular"/>
      </when>
      <when value="false"/>
    </conditional>
    <param name="copy_adata_to_raw" type="boolean" label="Copy AnnData to .raw" help="If activated, it will do 'adata.raw = adata'" checked="false"/>
    <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"/>

        </assert_contents>
      </output>
    </test>
    <test>
      <param name="input_obj_file" value="anndata_ops.h5"/>
      <conditional name="add_cell_metadata">
        <param name="default" value="true"/>
        <param name="file" value="test_incomplete_metadata.tsv"/>
      </conditional>
      <output name="output_h5ad" ftype="h5ad">
        <assert_contents>
          <has_h5_keys keys="obs/cell_type"/>
        </assert_contents>
      </output>
    </test>
    <test>
      <param name="input_obj_file" value="anndata_ops.h5"/>
      <repeat name="var_modifications" >
        <param name="from_var" value = "gene_symbols" />
        <param name="to_var" value = "gene_symbols_unique" />
        <param name="make_unique" value = "True" />
      </repeat>