calc.DESeq2.L2FC: Fold-change calculation for CRISPR screen

In christensensm/COMPOSE: Calculation and Visualization of Phenotypic CRISPR Screens

Description

Calculates log2 fold-changes between samples of a specified variable using input of a count matrix and metadata dataframe

Usage

calc.DESeq2.L2FC(
  countsTable,
  metadata,
  meta.idnum = NULL,
  include.batch = F,
  p.cutoff = 0.05,
  save = F,
  verbose = T
)

Arguments

countsTable	input matrix containing normalized gRNA counts with gRNA ids as row names
metadata	input dataframe containing sample names and other identifiers or data
meta.idnum	vector containing the column numbers in metadata that represent (1) Cell line, (2) replicates, and (3) condition
include.batch	logical to include replicates in the model
p.cutoff	numeric - specified p-value cut-off
save	logical - do you want to save the fold-change table to csv
verbose	TRUE/FALSE

Value

matrix containing Log2 fold-changes for each comparison

Examples

L2FC <- calc.DESeq2.L2FC(countsTable, design.table, save = T)
...

christensensm/COMPOSE documentation built on Dec. 22, 2020, 3:43 a.m.