recipe bioconductor-xbseq

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 and noise signals 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.



GPL (>=3)




biotools: xbseq, doi: 10.1186/1471-2164-16-S7-S14

package bioconductor-xbseq

(downloads) docker_bioconductor-xbseq


1.14.0-0, 1.12.0-0, 1.8.0-0, 1.6.0-0

Depends bioconductor-biobase


Depends bioconductor-deseq2


Depends bioconductor-roar


Depends r-base


Depends r-dplyr

Depends r-ggplot2

Depends r-locfit

Depends r-magrittr

Depends r-matrixstats

Depends r-pracma



With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-xbseq

and update with:

conda update bioconductor-xbseq

or use the docker container:

docker pull<tag>

(see bioconductor-xbseq/tags for valid values for <tag>)