In kalganem/KRSA: KRSA: Kinome Random Sampling Analyzer

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(KRSA)
library(knitr)
library(tidyverse)

Using Enrichr and KRSA

You can perform gene set enrichment analysis using Enrichr by using either a set of PamChip peptide IDs or gene symbols.

Using Peptide IDs

example_peptide_list <- c("ACM5_494_506", "ADDB_696_708", "ADRB2_338_350", "ANXA1_209_221")

enrichr_results <- krsa_enrichr(peptides = example_peptide_list)


head(enrichr_results, 10)

Using Gene Symbols

Alternatively, the input coould be gene symbols instead of peptide ids:

enrichr_results_genes <- krsa_enrichr(genes = c("AKT1", "AKT2", "AKTe"))


head(enrichr_results_genes, 10)

Visualization

The results could be plotted using the krsa_enrichr_plot function:

krsa_enrichr_plot(enrichr_results)

Showing only top 5 terms per library: `

krsa_enrichr_plot(enrichr_results, terms_to_plot = 5)

kalganem/KRSA documentation built on April 16, 2022, 5:20 a.m.