Bayesembler, a reference-based transcriptome assembler

Researchers from the University of Copenhagen introduce the 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, they demonstrate marked improvements in sensitivity and precision over state-of-the-art assemblers on both simulated and real data.

Input Files: 

Requires BAM files, produced by mapping paired reads against a reference genome with Tophat2.

Sample Files found here:  

Community Data > iplantcollaborative > example_data > input > Bayesembler

The files are two BAM files produced by mapping RNA-Seq reads against an appropriate reference genome file:  TrmPr1_SRR566981.sra_1.fastq.bam, TrmPr1_SRR567164.sra_1.fastq.bam

Output Files:

Typically the output assembly is in .GTF format. 

An example of some output files is found here:

Community Data > iplantcollaborative > example_data > output > Bayesembler

Software and more info: