counts_to_rle: Size Factor normalization as used by DESeq for differential...
In ssarda/genomeutils: Utilities for Genome Analysis
Description
Usage
Arguments
Value
Description
First the geometric mean of each gene across all cells is calculated. The size factor for each cell is the median across genes of the ratio of the expression to the gene’s geometric mean.
Spike-ins should be excluded from the calculation of total expression in order to correct for total cell RNA content, therefore they should be specified to exclude them from downstream analysis
Usage
1
counts_to_rle(expr_mat, spikes = NULL)
Arguments
expr_mat
Input matrix with expression values for genes in the form (Genes x Samples)
spikes
A vector of genes that were spike-ins in the original experiment
Value
A matrix with SF normalized RLE values
ssarda/genomeutils documentation built on May 30, 2019, 8:42 a.m.
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Description Usage Arguments Value
Description
First the geometric mean of each gene across all cells is calculated. The size factor for each cell is the median across genes of the ratio of the expression to the gene’s geometric mean. Spike-ins should be excluded from the calculation of total expression in order to correct for total cell RNA content, therefore they should be specified to exclude them from downstream analysis
Usage
1 | counts_to_rle(expr_mat, spikes = NULL)
|
Arguments
expr_mat |
Input matrix with expression values for genes in the form (Genes x Samples) |
spikes |
A vector of genes that were spike-ins in the original experiment |
Value
A matrix with SF normalized RLE values
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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