In oriolarques/GEGVIC: A workflow to analyse Gene Expression, Genetic Variations and Immune cell Composition of tumour samples using Next Generation Sequencing data.

knitr::opts_chunk$set(echo = TRUE)

library(GEGVIC)
library(clusterProfiler)

counts <- read.csv(params$counts, header = TRUE, sep = ',')
metadata <- read.csv(params$metadata, header = TRUE, sep = ',')
gmt <- read.gmt(params$gmt)
biomart <- read.csv(params$biomart, header = TRUE, sep = ',')

#gv_module
muts <- read.csv(params$muts, header = TRUE, sep = ',')

# Get data PCA
    ge_pca(counts = counts,
                  genes_id = params$genes_id,
                  metadata = metadata,
                  design = params$design,
                  colors = params$colors)

# Run differential gene expression analysis
    results.dds <- ge_diff_exp(counts = counts,
                               genes_id = params$genes_id,
                               metadata = metadata,
                               design = params$design,
                               ref_level = params$ref_level,
                               shrink = params$shrink)

# Annotate gene symbols
    annot.res <- ge_annot(results_dds = results.dds,
                          genes_id = params$genes_id,
                          biomart = biomart)

# Create volcano plot
    ge_volcano(annot_res = annot.res,
               fold_change = params$fold_change,
               p.adj = params$p.adj)

# Obtain GSEA results
    ge_gsea(annot_res = annot.res,
            gmt = gmt,
            gsea_pvalue = params$gsea_pvalue)

GV_module

gv_mut_signatures(muts = muts,
                   metadata = metadata,
                   response = Response,
                   gbuild = 'BSgenome.Hsapiens.UCSC.hg19',
                   mut_sigs = 'COSMIC_v2_SBS_GRCh37',
                   tri.counts.method = 'default',
                   colors = c('black', 'orange'))

oriolarques/GEGVIC documentation built on Oct. 30, 2024, 10:44 p.m.