Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach-Reference-Cited by-同舟云学术

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Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach

Published:2016-04 Issue:4 Volume:23 Page:239-247
ISSN:1066-5277
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Anjum Arfa¹,Jaggi Seema¹,Varghese Eldho¹,Lall Shwetank¹,Bhowmik Arpan¹,Rai Anil¹

Affiliation:

1. ICAR-Indian Agricultural Statistics Research Institute, Indian Council of Agricultural Research, New Delhi, India.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modelling and Simulation

Link

http://www.liebertpub.com/doi/pdf/10.1089/cmb.2015.0205

Reference19 articles.

1. Differential expression analysis for sequence count data

2. Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays

3. Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments

4. GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

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