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proteomicsr: enrichment using MSigDB gene sets (version 0.1.0+galaxy0)

Sample table:

Rows: unique identifiers (e.g. uniprot accessions), Columns: samples. Replicates should be indicated using _1, _2, .... Content should be numeric.

Gene set knowledgebase:

Visit https://www.gsea-msigdb.org/gsea/msigdb/human/collections.jsp to get more information on MSigDB categories and if the chosen category needs the definition of a subcategory. MEDICUS and LEGACY gene sets seem to be not supported yet.

Gene set knowledgebase subcategory:

Accession - Gene name mapping:

An optional table conatining columns Accession and Gene

Sample mapping:

An optional table that is used to relate different conditions to ggplot facets. See help.

Define provided identifier:

Define the ID type used in your dataframe of average Log2(FCs) and (adjusted) p-values. The ID should relate to attributes available using attributes = biomaRt::listAttributes(biomaRt::useMart(biomart = "ENSEMBL_MART_ENSEMBL", dataset = "hsapiens_gene_ensembl")) or the attributes specific for the defined organism (e.g. "mmusculus_gene_ensembl" or "rnorvegicus_gene_ensembl").

Organism used:

Pattern to select columns containing p-values to use:

Examples: When pvalue, all columns ending on _pvalue are used to filter for significantly altered candidates, whereas the pattern pvalueadj will use all columns ending with this pattern

Significance cutoff to filter for candidates used for enrichment:

All candidates with (adjusted) p-value below this threshold will be subjected to enrichment analysis

Significance cutoff to identify significantly enriched terms:

All terms with (adjusted) p-value below this threshold will be considered significantly enriched

Method for p-value adjustment during enrichment analysis:

Decide how to calculate the direction of the term regulation:

Decide whether to use median or mean values of the Log2(fold changes) of the candidates used for enrichment and assigned to the term.

Number of top enriched pathways to return and visualize:

In addition to exporting and visualizing all enriched terms and the significantly enriched terms, the top enriched terms will be exported and visualized based on the value defined here.

Extract the top enriched terms condition-wise:

Decide whether to extract the top enriched terms condition-wise or based on their summed enrichment over all conditions

Decide whether to visualize candidates assigned to enriched terms:

Color for up-regulated candidates:

Color for down-regulated candidates:

Optional outputs: