Description Usage Arguments Details Value Examples
Process and normalize RNA-Sequencing count data into a distribution appropriate for Poisson MRFs.
1 2 | processSeq(X, quanNorm = 0.75, nLowCount = 20, percentLowCount = 0.95, NumGenes = 500,
PercentGenes = 0.1)
|
X |
nxp data matrix. |
quanNorm |
an optional parameter controlling the quantile for sample normalization, default to 0.75. |
nLowCount |
minimum read count to decide if to filter a gene, default to 20. |
percentLowCount |
filter out a gene if it has this percentage of samples less than |
NumGenes |
number of genes to retain in the final data set, default to 500. |
PercentGenes |
percentage of genes to retain, default to 0.1. |
To process the next-generation sequencing count data into proper distribution (with dispersion removed), the following steps are taken in this function:
Quantile normalization for the samples.
Filter out genes with all low counts.
Filter genes by maximal variance (if specified).
Transform the data to be closer to the Poisson distribution. A log or power transform is considered and selected based upon the Kolmogorov-Smirnov goodness of fit test.
a n x NumGenes
or PercentGenes
processed data matrix.
1 2 3 |
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