RNASeqBias contains functions and sample data for detecting and correcting for biases in gene expression levels from RNA-Seq experiments. Considered bias factors are gene length, GC content and dinucleotide frequencies. Principal component analysis on GC content and dinucleotide frequencies are first performed, and the resulting principal components and gene length were used as covariates to fit a generalized additive model with smoothing spline on gene expression levels as response. The package also have codes to generate bias plots before and after bias correction, and to compare with other quantitative platforms.
- Windows / Linux / MacOsX
- R Package
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BMC Bioinformatics. 2011 Jul 19;12:290. doi: 10.1186/1471-2105-12-290.
Bias detection and correction in RNA-Sequencing data.
Zheng W1, Chung LM, Zhao H.