Data Preparation Modules: panoply_filter

panoply_filter

Description

This module preprocesses and filters proteomics (protein/PTM site) data. It is typically run after the panoply_normalize_ms_data module.

Preprocessing (always applied):

• If geneIdCol with Hugo Gene Symbols missing from sample annotation table, it will be created from the proteinIdCol
• If the sample annotation table contains a QC.status column, samples marked QC.pass will be retained in the output files. If not, all samples are assumed to be QC.pass, and a QC.status column is created accordingly.
• If separateQCTypes is set to 'true', additional output files (e.g. *-QC.fail.gct) will be created with non-QC.pass samples.

Filters available are:

• If sdFilterThreshold is specified, exclude rows with standard deviation less than sdFilterThreshold
• If combineReplicates replicates is specified and replicates are present in the data (identified by identical values in the Participant, Type (optional), and Timepoint (optional) columns in the sample annotation table), combine values across replicates for each row, using the method specified by combineReplicates.
• If naMax is specified, exclude rows with more than naMax missing values
• If noNA is 'true', create an additional table with no missing values

Input

Required inputs:

• inputData: (.tar file) tarball from panoply_normalize_ms_data, or normalized input data in gct format (when standalone is true)
• type: (String) proteomics data type
• standalone: (String) set to true to run as a self-contained module; if true the analysisDir input is required
• yaml: (.yaml file) parameters in yaml format
• analysisDir: (String) name of analysis directory

Optional inputs:

• filterProteomics: (String, default chosen in startup notebook) when 'true' filtering will be applied, when 'false' filtering is skipped. Preprocessing is always applied, regardless of toggle value.
• separateQCTypes: (String, default = 'false') toggle for generating additional output files, subset to non-QC.pass samples (e.g. *-QC.fail.gct). Filtering is not applied to these outputs.
• geneIdCol: (String, default = 'geneSymbol') name of (row) annotation column containing gene IDs.
• proteinIdCol: (String, default = 'id') name of (row) annotation column containing protein IDs.
• proteinIdType: (String, default chosen in startup notebook) keytype of protein IDs in proteinIdCol
• combineReplicates: (String, default = 'mean') method used to combine replicate samples, as are identified by identical values in the Participant, Type (optional), and Timepoint (optional) columns of the sample annotation table. If null, replicates will not be combined.
• naMax: (Float, default = 0.7) maximum allowed NA values per row (protein/PTM site); can be fraction between 0-1 or an integer specifying actual number of samples. If null, NA values will not be removed.
• noNA: (String, default = 'false') toggle for generating a GCT in which rows (protein/PTM sites) containing any NA values are excluded
• sdFilterThreshold: (Float, default = 0.5) standard deviation (SD) threshold for SD filtering; rows (proteins/PTM sites) with SD less than sdFilterThreshold are excluded from the filtered output table. If null, sd filtering will not be applied.
• ndigits: (Int, default = 5) number of decimal digits to use in output tables
• outTar: (String, default = "panoply_filter-output.tar") output .tar file name
• outTable: (String, default = "filtered_table-output.gct") output .gct filtered file name

Output

• output_tar: Tarball including the following files in the filtered-data subdirectory:
  • Filtered data files:
    • data table containing only QC-pass samples (*-ratio-norm.gct), with no other filters applied
    • filtered data table (*-ratio-norm-filt.gct)
  • Optional data files:
    • data table containing non-QC.pass samples of some {qc.type} (*-ratio-norm-{qc.type}.gct), with no other filters applied
    • filtered data table, with rows (protein/PTM sites) containing any NA values excluded (*-ratio-norm-filt-noNA.gct)
• outputs: (.gct file) filtered data table (equivalent to *-ratio-norm-filt.gct)
• output_yaml: finalized parameter file

References

• Mertins, P., Mani, D., Ruggles, K., Gillette, M., Clauser, K., Wang, P., Wang, X., Qiao, J., Cao, S., Petralia, F., et al. (2016). Proteogenomics connects somatic mutations to signalling in breast cancer. Nature 534(7605), 55 - 62. https://dx.doi.org/10.1038/nature18003.
• Gillette, M., Satpathy, S., Cao, S., Dhanasekaran, S., Vasaikar, S., Krug, K., Petralia, F., Li, Y., Liang, W., Reva, B., et al. (2020). Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma. Cell 182(1), 200 - 225.e35. https://dx.doi.org/10.1016/j.cell.2020.06.013