RTAM_normalization: RTAM Nomalization Function

In alimahdipour/sciCNV: sciCNV

RTAM Nomalization Function

Description

RTAM1/2 normalization designed for but not limited to scRNA-seq data

Usage

RTAM_normalization(mat, method, Min_nGn, Optimizing)

Arguments

mat	The raw data matrix has genes as rows and cells as columns
Genes	are annotated with their genomic location (start and end locations)
Order_Matrix	is the original order of genes in the raw data
MinNumGenes	is a threshold used to exclude poor QC cells that have few detectable genes (default= minimum of 250 genes).
OptNumGenes	is the number of genes that when employed for RTAM normalization will optimally minimize the variance across cells of gene-set average expression

Value

The output is RTAM1 or 2 normalzied data at higher sensitivity, specificity and acuracy for all transcriptions (at loqwe, intermediate and higher levels)

Note

Please refer to the reference and supplemental materials described in the README for additional details.

Author(s)

Ali Mahdipour-Shirayeh, Princess Margaret Cancer Centre, University of Toronto

Examples

CV_for_RTAM1 <- RTAM_normalization(mat=raw_data, method="RTAM2", Min_nGn=250, Optimizing=FALSE)

alimahdipour/sciCNV documentation built on Oct. 16, 2022, 12:56 p.m.