Transform/normalize counts using TF-IDF

Transform/normalize counts using TF-IDF

Usage

transformTFIDF(mat, scale.factor = 100000, count.min = 0, count.max = 1)

Arguments

mat

n x p input matrix (n = samples/cells; p = rna counts)

scale.factor

Scaling factor for the term-frequency (TF)

count.min

The minimum expression count used for TF-IDF. Binarizes when count.min = 0 and count.max = 1.

count.max

The maximum expression count used for TF-IDF. Binarizes when count.min = 0 and count.max = 1. binarizes the matrix. A cap value greater than 1 will cap counts at that value.

Value

A TF-IDF transformed matrix of the same dimensions as the input

Details

This function and its helpers were modeled after or taken from:

• http://andrewjohnhill.com/images/posts/2019-5-6-dimensionality-reduction-for-scatac-data/analysis.html

• https://divingintogeneticsandgenomics.rbind.io/post/clustering-scatacseq-data-the-tf-idf-way/

Examples

m <- 1000
n <- 100
mat <- round(matrix(runif(m * n), m, n))
# Input needs to be a tall matrix
tfidf <- transformTFIDF(mat)