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Hindi Journal of Applied Bioinformatics & Computational BiologyISSN: 2329-9533
KK Chaturvedi Author
Subjects of specialization
Affiliation
Mining Software, Biological Repositories, Artificial Intelligence, Precision Agriculture
ICAR-Indian Agriculture Statistical Research Institute, Pusa, New Delhi-110012 (Delhi), India
Biography
Dr. KK Chaturvedi is currenly working as a Principal Scientist in ICAR-Indian Agriculture Statistical Research Institute, Pusa, New Delhi-110012 (Delhi), India his current research interests includes Mining Software and Biological Repositories, Data Structures and Parallel Algorithm Development, Database, Data Warehousing, Decision Support System and Data Mining Artificial Intelligence and Precision Agriculture. He worked as a professor in the department of Software Engineering, Advanced Programming in Bioinformatics.
Publications
Review Article Open Access
A Review on Recent Statistical Models for RNA-Seq Data
Author(s): Mohammad Samir Farooqi, DC Mishra, KK Chaturvedi, Anil Rai, SB Lal, Sanjeev Kumar, Jyotika Bhati and Anu Sharma
The next generation sequencing technology, RNA-sequencing (RNA-seq), has got growing acceptance in transcriptome analyses. Statistical methods used for gene expression analyses with RNAseq provide meaningful inferences of gene expression using counts of reads. There are various statistical models with its pros and cons available for RNA-seq data analysis. There is a need for consistent statistical methods to explore the information from the developing sequencing technologies. The current article gives a review of the statistical methods with their limitations that can be useful for the RNA-seq analysis. The main emphasis is given to the parametric, nonparametric and hybrid models for identifying the genes with differential expression.
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