get.size.factor: Get Size Factor Estimate

In estfernan/boost: Bayesian Modeling of Spatial Transcriptomics Data

Get Size Factor Estimate

Description

Obtain the size factor estimates to capture all nuisance effects and compute the relative gene expression levels.

Usage

get.size.factor(count, estimation.method = c("TSS", "Q75", "RLE", "TMM"))

Arguments

count	An n-by-p numeric matrix Y that denotes the absolute gene expression count table. Each entry is the absolute read count for gene j collected at spot i.
estimation.method	An optional character string to specify the size factor computation technique. The default is "TSS" for total sum scaling.

Details

Normalization is critical to sequence count data analysis. As a result, to counteract various artifacts and bias due to biological and technical reasons, the read counts should be converted to their relative gene expression levels i.e., divide the counts by the result of this function. If the main interest is in the absolute gene expression level, then the size factor is set to the same value; otherwise, the size factor is computed directly from the gene expression count data.

This method offers the following options for computing size factors: total sum scaling (TSS), upper-quartiles (Q75), relative log expression (RLE), and weighted trimmed mean by M-values (TMM).

See Jiang et al. (2021) for more information and references on these options.

Value

A numeric vector, where each entry denotes the size factor for sample i.

References

Jiang, X., Li, Q., & Xiao, G. (2021). Bayesian Modeling of Spatial Transcriptomics Data via a Modified Ising Model. arXiv preprint arXiv:2104.13957.

estfernan/boost documentation built on June 24, 2022, 12:20 a.m.