Genome Biol
2014[]; 15
(10
): 501
PMID25367074
show ga
RNA sequencing allows for simultaneous transcript discovery and quantification,
but reconstructing complete transcripts from such data remains difficult. Here,
we introduce Bayesembler, a novel probabilistic method for transcriptome assembly
built on a Bayesian model of the RNA sequencing process. Under this model,
samples from the posterior distribution over transcripts and their abundance
values are obtained using Gibbs sampling. By using the frequency at which
transcripts are observed during sampling to select the final assembly, we
demonstrate marked improvements in sensitivity and precision over
state-of-the-art assemblers on both simulated and real data. Bayesembler is
available at https://github.com/bioinformatics-centre/bayesembler.
free
free
free
