| runPSEA {PEIMAN2} | R Documentation |
Run Protein Set Enrichment Analysis (PSEA)
Description
This is the main function to run protein set enrichment analysis for a list of proteins and their score.
Usage
runPSEA(
protein,
os.name,
pexponent = 1,
nperm = 1000,
p.adj.method = "fdr",
sig.level = 0.05,
minSize = 1
)
Arguments
protein |
A dataframe with two columns. Frist column should be protein accession code, second column is the score. |
os.name |
A character vector of length one with exact taxonomy name of species. If you do not know the
the exact taxonomy name of species you are working with, please read |
pexponent |
Enrichment weighting exponent, p. For values of p < 1, one can detect incoherent patterns in a set of protein. If one expects a small number of proteins to be coherent in a large set, then p > 1 is a good choice. |
nperm |
Number of permutation to estimate false discovery rate (FDR). Default value is 1000. |
p.adj.method |
The adjustment method to correct pvalues for multiple testing in enrichment. Run p.adjust.methods() to get a list of possible methods. |
sig.level |
The significance level to filter PTM (applies on adjusted p-value) |
minSize |
PTMs with the number of proteins below this threshold are excluded. |
Value
Returns a list of 6: 1: A dataframe with protein set enrichment analysis (PSEA) results. Every row corresponds to a post-translational modification (PTM) pathway.
PTM: PTM keyword
pval: p-value for singular enrichment analysis
pvaladj: adjusted p-value
FreqinUniProt: The frequency of PTM in UniProt
FreqinList: The frequency of PTM in the given list
ES: enrichment score
NES: enrichmnt score normalized to mean enrichment of random samples of the same size
nMoreExtreme: number of times the permuted sample resulted in a profile with a larger ES value than abs(ES)
size: Number of proteins with the PTM
Enrichment: Whether the proteins in the pathway have been enriched in the list.
AC: Uniprot accession code (AC) of proteins with each PTM.
leadingEdge:
Examples
# We recommend at least nperm = 1000.
# The number of permutations was reduced to 10
# to accommodate CRAN policy on examples (run time <= 5 seconds).
psea_res <- runPSEA(protein = exmplData2, os.name = 'Rattus norvegicus (Rat)', nperm = 10)