Custom Gene Lists

Pathway and GO analysis

Pathway and GO analysis gene set files are lists of genes that are somewhat associated with the respective pathway or GO term. Upon data preparation by the MQReader, measured proteins are indexed by their gene name originating from the FASTA file (header) to which the protein was mapped. Thus, measured protein intensities can be analysed using functional gene sets like those that are incorporated by the mspypeline package.
Since some analysis methods deploy such pathway and GO term lists, the provided files can be used to get an idea and generate an example for a potential analysis (see Gallery).
Pathway (and GO term) lists are configured globally for a data analysis and not individually for each plot. If one or more pathway lists are selected in the GUI or configs file, these pathways will be used for any of the three listed plots if they are being created.
To change the choice of pathways or GO terms for an analysis, the previously selected pathways have to be un-checked in the corresponding selection box in the GUI or the “pathways:” or “go_term:” arguments in the configs file have to be edited manually.

Tip

Any desired pathway and GO list can be manually provided to mspypeline by the user. The file simply has to:

  1. follow the one-column-txt-format that can be seen in the exemplary files listed below,

  2. be stored in one of these two locations:

    • saved in the …/mspypeline/config/pathway or go_term directory, where all the other files are stored (files saved here are available for all experiments and from the GUI).

    • saved in a pathways and go_terms directory in the same location where the txt folder of the experiment data is stored (files saved here are available for the particular experiment and are callable when mspypeline is used as a python module or when the list is specified in the configs file.

Attention

  • All pathway and GO analysis gene files provided here are based on the HUMAN genome/proteome.

  • All pathway and GO analysis gene files are retrieved from the open source GSEA Molecular Signature Data Base (22. Feb. 2021)

Pathways

GO Terms