Does the current Seurat version have Pearson residual normalization? If not, is there an alternative tool to do scRNA analysis with Pearson residual normalization?
Does the current Seurat version have Pearson residual normalization? If not, is there an alternative tool to do scRNA analysis with Pearson residual normalization?
Hi,
Yes, it has the sctransform
method:
paper: Hafemeister and Satija, 2019
vignette: sctransform pipeline
The Hafemeister and Satija, 2019 clearly states in the abstract (citing):
"We propose that the Pearson residuals from “regularized negative binomial regression,” where cellular sequencing depth is utilized as a covariate in a generalized linear model, successfully remove the influence of technical characteristics from downstream analyses while preserving biological heterogeneity."
I hope this helps,
António
P.S.: Just came across the following paper - Ahlmann-Eltze and Huber, 2022 - comparing several transformations for single-cell RNA-seq. Under the scenarios tested the simplistic log1p normalization method with a scaling factor (i.e., log(y/s + y0)
) outperforms more sophisticated methods taking into account the metrics assessed.
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Thank you. Follow up question Seurat doesn't use Poisson method does it? I was looking at this paper and was trying to analyze my data using Poisson method https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02451-7
Sorry, I don't know the method to answer your question.
What it is clear from the description above is that the Pearson residuals come from a negative binomial regression.
Understood. Thank you for your help!