scQ: scQ (single cell quantile normalization) for scRNAseq data
In GIS-SP-Group/RCA: RCA: Clustering Single Cell RNAseq Data using Reference Component Analysis
Description
Usage
Arguments
Value
Examples
Description
scQ (single cell quantile normalization) for scRNAseq data
Usage
1
Arguments
data
Expression data frame with genes in rows.
thr
cells with detected genes less than thr+1 would be thrown away. Also after normalization
only thr number of genes would have non zero epression in each cell.
Value
normalized data as a data frame retaining orginal row and column names
Examples
1
norm_Data <- scQ(fpkm_data,1000) # scQ normalization
GIS-SP-Group/RCA documentation built on May 6, 2019, 5:30 p.m.
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Description Usage Arguments Value Examples
Description
scQ (single cell quantile normalization) for scRNAseq data
Usage
1 |
Arguments
data |
Expression data frame with genes in rows. |
thr |
cells with detected genes less than |
Value
normalized data as a data frame retaining orginal row and column names
Examples
1 | norm_Data <- scQ(fpkm_data,1000) # scQ normalization
|
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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