We developed a novel algorithm, XBSeq, where a statistical model was established based on the assumption that observed signals are the convolution of true expression signals and sequencing noises. The mapped reads in non-exonic regions are considered as sequencing noises, which follows a Poisson distribution. Given measureable observed signal and background noise from RNA-seq data, true expression signals, assuming governed by the negative binomial distribution, can be delineated and thus the accurate detection of differential expressed genes.
|Imports:||DESeq2, Biobase, pracma, matrixStats, ggplot2,locfit, methods, BiocGenerics, dplyr, plotly, MetricsGraphics|
Maintainer: Yuanhang Liu <[email protected]>
H. I. Chen, Y. Liu, Y. Zou, Z. Lai, D. Sarkar, Y. Huang, et al., "Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads," BMC Genomics, vol. 16 Suppl 7, p. S14, Jun 11 2015.
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