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Protocols

BitSeq specifications

Information


Unique identifier OMICS_01269
Name BitSeq
Alternative name Bayesian inference of transcripts from sequencing data
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C++, R
Computer skills Advanced
Version 0.7.5
Stability Stable
Requirements
GNU make, g++, zlib
Maintained Yes

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Versioning


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Documentation


Maintainer


  • person_outline Magnus Rattray

Publication for Bayesian inference of transcripts from sequencing data

BitSeq citations

 (20)
call_split

Campylobacter jejuni transcriptome changes during loss of culturability in water

2017
PLoS One
PMCID: 5708674
PMID: 29190673
DOI: 10.1371/journal.pone.0188936
call_split See protocol

[…] atmaps were constructed using heatmap2 in R.For pairwise Differential Expression analysis between samples, the data were re-mapped to the C. jejuni M1 genome [] using Bowtie2 [], and parsed using the BitSeq (Bayesian Inference of Transcripts from Sequencing data) pipeline []. BitSeq takes into account biological replicates and technical noise, and thereby calculates a posterior distribution of dif […]

library_books

Improved data driven likelihood factorizations for transcript abundance estimation

2017
Bioinformatics
PMCID: 5870700
PMID: 28881996
DOI: 10.1093/bioinformatics/btx262

[…] the transcript abundances that would be most likely given the observed data (i.e. the alignments of the sequenced fragments to the underlying genome or transcriptome). Bayesian methodologies such as BitSeq () and Tigar () were also developed and adopt different inferential approaches varying from fully Bayesian approaches like collapsed Gibbs sampling () to approximate inference approaches like v […]

library_books

DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates

2017
Bioinformatics
PMCID: 5870796
PMID: 28595376
DOI: 10.1093/bioinformatics/btx357

[…] 0 genes using RNASeqReadSimulator for each of five replicates in both conditions, using default settings. To test the robustness of DEIsoM, we repeat the above simulation process 10 times. For RSEM, BitSeq, MISO, and DEIsoM, the simulated reads are mapped back to the reference transcriptom using Bowtie2 (). For Cuffdiff, the reads are mapped back to the hg19 reference genome using Tophat (). The […]

library_books

ICF specific DNMT3B dysfunction interferes with intragenic regulation of mRNA transcription and alternative splicing

2017
Nucleic Acids Res
PMCID: 5449610
PMID: 28334849
DOI: 10.1093/nar/gkx163

[…] lation of alternative isoform expression.To address this possibility and to investigate whether this process is perturbed by ICF1-specific DNMT3B mutations, we analyzed the RNA-Seq datasets using the BitSeq tool, which evaluates the exon–exon junction usage to measure the transcript isoform abundance (; ).Nearly 55% of differentially expressed isoform (DE-isoform) associated genes were shared by t […]

library_books

A Bayesian model selection approach for identifying differentially expressed transcripts from RNA sequencing data

2017
PMCID: 5763373
PMID: 29353941
DOI: 10.1111/rssc.12213

[…] nario 7). See the on‐line supplementary Fig. and appendix K for the details of the ground truth that was used in our simulations.Next, we applied the method proposed and compared our results against Bitseq, Cuffdiff and EBSeq, using the receiver operating characteristic,the squared error, accuracy receiver operating characteristic area measure, SAR (Sing et al., ), andthe power to achieved FDR cu […]

library_books

Pooled CRISPR screening with single cell transcriptome read out

2017
Nat Methods
PMCID: 5334791
PMID: 28099430
DOI: 10.1038/nmeth.4177

[…] q -p 6 -a -m 100 -minins 0 -maxins 5000 -fr -sam -chunkmbs 200. Duplicate reads were removed with Picard’s MarkDuplicates utility using standard parameters, followed by transcript quantification with BitSeq using the Markov chain Monte Carlo method and standard parameters. To obtain gene-level quantifications, we assigned to each gene the expression value of its most highly expressed transcript, c […]

Citations

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BitSeq institution(s)
School of Computer Science, University of Manchester, Oxford Road, Manchester, UK; Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, University of Helsinki, Finland; Department of Computer Science and Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK

BitSeq review

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Andrew Miller

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Desktop
A great tool for RNA-seq analyses !