EBSeq protocols

View EBSeq computational protocol

EBSeq statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left Differential expression Normalization chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

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 1.21.0
Stability Stable
Requirements
gplots, testthat, R(>=3.0.0), blockmodeling
Maintained Yes

Download


Versioning


Add your version

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

 (47)
2018
PMCID: 5818504
PMID: 29459759
DOI: 10.1038/s41598-018-21663-9

[…] we realigned and processed., rnaseq data from 10 normal human fibroblasts samples (geo dataset gse51518 from the ncbi) together with the ovarian fibrosarcoma data and used rsem and the r package ebseq to normalize, quantitate and compare the expression data. microrna analysis was performed using a mirna 4.0 array (affymetrix, santa clara, ca). a normal ovary cell line cel file was obtained […]

2018
PMCID: 5878829
PMID: 29619229
DOI: 10.1038/s41438-018-0025-2

[…] calculation. the expression patterns and posterior probability of differential expression ‘posterior probability of differential expression’ (ppde) values of each gene/contig were estimated by ebseq v1.1.5 , and the degs were identified with ppde = 1. the rna-seq raw data have been deposited in the ncbi sequencing read archive database and can be accessed with the following accession […]

2018
PMCID: 5896248
PMID: 29606348
DOI: 10.1016/j.ccell.2018.02.011

[…] along with custom r utilities. all rna-seq analyses were conducted in the r statistical programming language (http://www.r-project.org/). isoform-level differential analyses were performed using ebseq (). gene set enrichment analysis (gsea) was carried out using the pre-ranked mode with default settings (). enrichment maps were generated using the em () plugin for cytoscape (). heatmaps […]

2018
PMCID: 5900932
PMID: 29666761
DOI: 10.7717/peerj.4607

[…] based on fragments per kb per million fragments (fpkm) method in rsem v1.2.12 (). significantly differentially expressed genes (degs) were scanned among samples under low and high light using ebseq package v1.7.1 (), with a threshold of an absolute log2 ratio ≥ 2 and a false discovery rate (fdr) significance score <0.001. based on the kegg and go annotation, we classified degs […]

2018
PMCID: 5940870
PMID: 29739946
DOI: 10.1038/s41467-018-04134-7

[…] environment (r core team, 2014) was used at all of the stages of downstream data analysis. the entire set of libraries was pre-normalized as a pool using median normalization routine from ebseq package. ebseq with 10 iterations was applied to call for differential expression. the ebseq’s default procedure of filtering low-expressed genes was suppressed by setting the qtrmcut parameter […]


To access a full list of citations, you will need to upgrade to our premium service.

EBSeq in publications

 (164)
PMCID: 5941469
PMID: 29739322
DOI: 10.1186/s12870-018-1296-3

[…] dge profiles were compared in order to determine changes in gene expression during ovary differentiation and ovule growth in hazel. based on the unigene expression results, degs were identified with ebseq [] by setting the threshold of fold change as ≥2.00 and posterior probability of equivalent expression (ppee) as ≤0.05. kegg pathway enrichment analysis of dge data was carried by a blast […]

PMCID: 5930841
PMID: 29743953
DOI: 10.1186/s13068-018-1116-x

[…] the pool of gene length- and library size-normalized values (fpkm) was additionally quantile-normalized via bioconductor “affy” package []. the differential expression testing was performed using ebseq [], the empirical bayesian-based differential expression calling package. genes with posterior probability of differential expression above 0.95 were subject to further filtering based […]

PMCID: 5916929
PMID: 29695774
DOI: 10.1038/s41467-018-03766-z

[…] most strongly used in gut tissue.fig. 3, pca of enhancer expression showed separation between inflamed samples (uca and cda) and ctrl, but only minor separation between uca and cda (fig. ). we used ebseq to define four differentially expressed enhancer groups, analogous to the tss groups defined above: shared cda and uca up/downregulated vs. ctrl (ibdup and ibddown), upregulated in cda vs. uca […]

PMCID: 5908868
PMID: 29674689
DOI: 10.1038/s41598-018-24727-y

[…] htseq v 0.6.1p2 was used to count the number of uniquely aligned reads using rfam and mirbase21. differential expression analysis of mirna expression profiles was quartile-normalized using ebseq v 1.12.0. mirnas with an abundance of greater than one cpm in at least three of the samples were defined as true known mirnas. mirnas uniquely expressed in one tissue were defined […]

PMCID: 5896248
PMID: 29606348
DOI: 10.1016/j.ccell.2018.02.011

[…] along with custom r utilities. all rna-seq analyses were conducted in the r statistical programming language (http://www.r-project.org/). isoform-level differential analyses were performed using ebseq (). gene set enrichment analysis (gsea) was carried out using the pre-ranked mode with default settings (). enrichment maps were generated using the em () plugin for cytoscape (). heatmaps […]


To access a full list of publications, you will need to upgrade to our premium service.

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.

EBSeq reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review EBSeq