discretize: Converts a continuous variable into categorical

In olapuentesantana/easier: Estimate Systems Immune Response from RNA-seq data

Converts a continuous variable into categorical

Description

It is used to bin continuous gene expression values from a given gene signature into categories.

Usage

discretize(v, n_cat)

Arguments

v	numeric vector with gene mean expression across samples.
n_cat	number of categories to bin continuous values, here gene expression values.

Details

The source code was provided by original work: https://github.com/livnatje/ImmuneResistance

Value

A numeric vector providing an integer value (e.g. category) for each gene.

References

Jerby-Arnon, L., Shah, P., Cuoco, M.S., Rodman, C., Su, M.-J., Melms, J.C., Leeson, R., Kanodia, A., Mei, S., Lin, J.-R., et al. (2018). A Cancer Cell Program Promotes T Cell Exclusion and Resistance to Checkpoint Blockade. Cell 175, 984–997.e24. https://doi.org/10.1016/j.cell.2018.09.006.

Examples

# using a SummarizedExperiment object
library(SummarizedExperiment)
# Using example exemplary dataset (Mariathasan et al., Nature, 2018)
# from easierData. Original processed data is available from
# IMvigor210CoreBiologies package.
library("easierData")

dataset_mariathasan <- easierData::get_Mariathasan2018_PDL1_treatment()
RNA_tpm <- assays(dataset_mariathasan)[["tpm"]]

# Select a subset of patients to reduce vignette building time.
pat_subset <- c(
  "SAM76a431ba6ce1", "SAMd3bd67996035", "SAMd3601288319e",
  "SAMba1a34b5a060", "SAM18a4dabbc557"
)
RNA_tpm <- RNA_tpm[, colnames(RNA_tpm) %in% pat_subset]

# Log2 transformation:
log2_RNA_tpm <- log2(RNA_tpm + 1)

# Prepare input data
r <- list()
r$tpm <- log2_RNA_tpm

# Gene signature of immune resistance program
score_signature_genes <- suppressMessages(easierData::get_scores_signature_genes())
RIR_gene_signature <- score_signature_genes$RIR

# Compute gene average expression across samples
r$genes_dist <- r$genes_mean <- rowMeans(r$tpm)

# Bin genes into 50 expression bins according to their average
r$genes_dist_q <- discretize(r$genes_dist, n_cat = 50)

olapuentesantana/easier documentation built on Feb. 25, 2024, 3:39 p.m.