Main logo
?
tutorial arrow
×
Create your own tool library
Bookmark tools and put favorites into folders to find them easily.

EBSeq | An empirical Bayes hierarchical model for inference in RNA-seq experiments

Provides ability to identify differentially expressed (DE) isoforms, results from simulations and case studies demonstrate good performance for identification of DE genes as well. EBSeq is an approach for inference in an RNA-seq experiment. It requires gene counts or estimates of isoform expression, but it is not specific to any particular estimation method. This model framework also enables comparisons of more than two biological conditions.

User report

tutorial arrow
×
Vote up tools and offer feedback
Give value to tools and make your expertise visible
Give your feedback on this tool
Sign up for free to join and share with the community

0 user reviews

star_border star_border star_border star_border star_border
star star star star star

0 user reviews

star_border star_border star_border star_border star_border
star star star star star

No review has been posted.

EBSeq forum

tutorial arrow
×
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.
Take part in the discussion
Sign up for free to ask question and share your advices

No open topic.

EBSeq classification

EBSeq specifications

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

EBSeq distribution

versioning

tutorial arrow
×
Upload and version your source code
Get a DOI for each update to improve tool traceability. Archive your releases so the community can easily visualize progress on your work.
Facilitate your tool traceability
Sign up for free to upload your code and get a DOI

No versioning.

download

EBSeq support

Documentation

Maintainers

  • Christina Kendziorski <>
  • Ning Leng <>

Additional information

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

Credits

tutorial arrow
×
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.
Promote your work
Sign up for free to badge your contributorship

Publications

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

Funding source(s)

Supported by NIH GM102756, NIH CA28954, NIEHS ES17400 and The Morgridge Institute for Research.

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.