Mercurial > repos > goeckslab > cell_intensity_processing
changeset 3:4f5abe01531c draft
planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/mti-utils commit 4d6008b58593174b87c9d9cf50c79ddfafda7637
author | goeckslab |
---|---|
date | Fri, 10 May 2024 17:52:26 +0000 |
parents | 7f93f472a242 |
children | 5d541df02496 |
files | macros.xml process_intensities.xml |
diffstat | 2 files changed, 24 insertions(+), 2 deletions(-) [+] |
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--- a/macros.xml Wed Feb 28 20:52:16 2024 +0000 +++ b/macros.xml Fri May 10 17:52:26 2024 +0000 @@ -14,8 +14,8 @@ <citation type="doi">10.1101/2022.08.18.504436</citation> </citations> </xml> - + <token name="@TOOL_VERSION@">0.0.1</token> - <token name="@VERSION_SUFFIX@">3</token> + <token name="@VERSION_SUFFIX@">4</token> <token name="@PROFILE@">19.01</token> </macros>
--- a/process_intensities.xml Wed Feb 28 20:52:16 2024 +0000 +++ b/process_intensities.xml Fri May 10 17:52:26 2024 +0000 @@ -26,6 +26,23 @@ markers_to_normalize = marker_df['marker_name'].to_list() +#if $AF_method.select_method == 'SBR': +AF_markers = [x for x in list(marker_df['${AF_method.AF_col}'].unique()) if x != 'None'] +print(f'Detected {quant[AF_markers].eq(0.0).any(axis=1).sum()} cells with AF values of zero in the dataset') + +#if $AF_filter == 'filter': +pre_filter_count = len(quant) +quant = quant.loc[quant[AF_markers].ne(0.0).any(axis=1),:] +print(f'Filtered out {pre_filter_count - len(quant)} cells that had AF values of 0.0') + +#elif $AF_filter == 'clip': +print('Clipping all AF values equal to 0.0 to the minimum non-zero AF value') +for af in AF_markers: + quant[af] = quant[af].clip(lower = quant[af][quant[af].ne(0.0)].min()) + +#end if +#end if + for marker in markers_to_normalize: #if $exp.exposure == 'correct_exposure': @@ -74,6 +91,10 @@ </when> <when value="SBR"> <param name="AF_col" type="text" value="AF_channel" label="Name of column in markers file containing respective AF channel for each marker" /> + <param name="AF_filter" type="select" label="Select whether to clip or filter out AF values equal to 0"> + <option value="clip">Clip autofluorescence values of 0.0 to the minimum non-zero autofluorescence value</option> + <option value="filter">Filter out cells with autofluorescence values equal to 0.0</option> + </param> </when> </conditional> </inputs> @@ -89,6 +110,7 @@ </conditional> <conditional name="AF_method"> <param name="select_method" value="SBR" /> + <param name="AF_filter" value="clip" /> </conditional> <output name="processed_quant" ftype="csv"> <assert_contents>