EBSeq protocols

EBSeq specifications

Information


Unique identifier OMICS_01307
Name EBSeq
Software type Package/Module
Interface Graphical user interface
Restrictions to use None
Input format CSV,XLS,XLSX
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License Artistic License version 2.0
Computer skills Advanced
Version 1.18.0
Stability Stable
Requirements blockmodeling, gplots, testthat
Maintained Yes

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Documentation


Maintainers


  • person_outline Christina Kendziorski <>
  • person_outline Ning Leng <>

Additional information


https://www.biostat.wisc.edu/~kendzior/EBSEQ/

Publication for EBSeq

EBSeq IN pipelines

 (21)
2018
PMCID: 5855618
PMID: 29385681
DOI: 10.3390/ijms19020396

[…] function, which uses singular value decomposition, generally providing better numerical accuracy., to detect degs between b. dorsalis and b. correcta, we used the empirical bayes hierarchical model ebseq [72]. in this analysis, we adopted a well-established benjamini–hochberg method to calibrate p values from the original assumption test [73]. after calibration, the p value was determined using […]

2017
PMCID: 5366954
PMID: 28345651
DOI: 10.1038/srep45365

[…] the t. vaginalis genome using rsem with bowtie2 v2.0.0-beta759. the expression level of each transcript was quantified as fpkm (fragments per kilobase of exon per million fragments mapped), and the ebseq package60 was used to select differentially expressed genes. the rna-seq data were visualized using the integrative genomics viewer61. gene ontology analysis was conducted with david […]

2017
PMCID: 5449544
PMID: 28180283
DOI: 10.1093/nar/gkx086

[…] as discussed in the ‘results’ section., reads were mapped to hg19 reference genome and gene expression was quantified by rsem version 1.2.25 (31). differential expression analysis was conducted by ebseq version 1.10.0 (32). differentially expressed genes were defined as having posterior probability of differential expression equal to 1. gene ontology (go) analysis was conducted by bingo […]

2017
PMCID: 5487440
PMID: 28702037
DOI: 10.3389/fpls.2017.01115

[…] 2012) and express (trapnell et al., 2012) using default parameters resulting in an average mapping rate of 96% across all samples. differential gene expression between treatment was tested with ebseq (leng et al., 2013) at default parameters with a false discovery rate (fdr) set to 5% with significance identified and expressed as posterior probability differential expression (ppde) greater […]

2017
PMCID: 5657623
PMID: 29073274
DOI: 10.1371/journal.pone.0185961

[…] as n) and low-quality containing >20% bases with a quality of <13. the clean mrna reads were aligned to the bovine genome (version: bos 4.6.1) using the mapsplice program (v2.1.8) [18]. the ebseq algorithm was used to filter the de genes between the steers and bulls groups based on the significant analysis and false discovery rate (fdr) analysis under the following criteria: (1) fold […]

EBSeq institution(s)
Department of Statistics, University of Wisconsin, Madison, WI, USA; Morgridge Institute for Research, Madison, WI, USA; McArdle Laboratory for Cancer Research, Department of Oncology, University of Wisconsin, Madison, WI, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
EBSeq funding source(s)
Supported by NIH GM102756, NIH CA28954, NIEHS ES17400 and The Morgridge Institute for Research.

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