2015
DOI: 10.1093/bioinformatics/btv193
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EBSeq-HMM: a Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments

Abstract: Motivation: With improvements in next-generation sequencing technologies and reductions in price, ordered RNA-seq experiments are becoming common. Of primary interest in these experiments is identifying genes that are changing over time or space, for example, and then characterizing the specific expression changes. A number of robust statistical methods are available to identify genes showing differential expression among multiple conditions, but most assume conditions are exchangeable and thereby sacrifice po… Show more

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Cited by 95 publications
(103 citation statements)
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“…We used ebseq‐hmm software (Leng et al., 2015) to compute statistically significant time patterns. To reduce the complexity, the 4M and 10M samples were not included in this analysis.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…We used ebseq‐hmm software (Leng et al., 2015) to compute statistically significant time patterns. To reduce the complexity, the 4M and 10M samples were not included in this analysis.…”
Section: Resultsmentioning
confidence: 99%
“…EdgeR package and EBSeq‐HMM (Leng et al., 2015) were used to perform differential gene expression analysis.…”
Section: Methodsmentioning
confidence: 99%
“…The expression of each transcript was calculated using rsem-calculate-expression using the option -forwardprob 0. Differential expression was determined using EBSeq (v1.6) with the "MedianNorm" normalization method (26,27).…”
Section: Table 1 Primers Used For Qpcrmentioning
confidence: 99%
“…68 Differentially expressed (DE) genes and isoforms were identified using EBSeq. 69 Bowtie, RSEM and EBSeq (ver 1.3.2) 69 were ran using default parameters. Quality control on sequences was performed by FASTQC.…”
Section: Plasmid Transfection and Viral Transductionmentioning
confidence: 99%