Bayesian Correlation Analysis for Sequence Count Data.
Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities' measurements based on high-throughput sequencing data. Th...
Main Authors: | Daniel Sánchez-Taltavull, Parameswaran Ramachandran, Nelson Lau, Theodore J Perkins |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2016-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5049778?pdf=render |
Similar Items
-
Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks.
by: Parameswaran Ramachandran, et al.
Published: (2017-01-01) -
baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data
by: Hardcastle Thomas J, et al.
Published: (2010-08-01) -
Bayesian Semiparametric Regression Analysis of Multivariate Panel Count Data
by: Chunling Wang, et al.
Published: (2022-05-01) -
Hierarchical Bayesian Models for Multiple Count Data
by: Radu Tunaru
Published: (2016-04-01) -
Empirical Bayes single nucleotide variant-calling for next-generation sequencing data
by: Ali Karimnezhad, et al.
Published: (2024-01-01)