NDLI: A survey and comparative study of statistical tests for identifying differential expression from microarray data

Please wait, while we are loading the content...

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 13

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 12

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 11

Issue 6, November/December 2014

Issue 5, September/October 2014

Issue 4, July/August 2014

Issue 3, May/June 2014

Issue 2, March/April 2014

Issue 1, January/February 2014

Editorial from the editor-in-chief

Guest editorial for the international conference on genome informatics (GIW 2013)

Coupling graphs, efficient algorithms and B-cell epitope prediction

Quantifying significance of MHC II residues

Intelligent consensus modeling for proline cis-trans isomerization prediction

Residue-specific side-chain polymorphisms via particle belief propagation

A new unsupervised binning approach for metagenomic sequences based on N-grams and automatic feature weighting

Gene name disambiguation using multi-scope species detection

Reliable and fast estimation of recombination rates by convergence diagnosis and parallel Markov Chain Monte Carlo

Identifying cis-regulatory elements and modules using conditional random fields

Evolution and controllability of cancer networks: a Boolean perspective

A survey and comparative study of statistical tests for identifying differential expression from microarray data

A new path based hybrid measure for gene ontology similarity

CAMS-RS: clustering algorithm for large-scale mass spectrometry data using restricted search space and intelligent random sampling

DNA copy number selection using robust structured sparsity-inducing norms

Constructing a gene team tree in almost O (n lg n) time

Detecting differentially coexpressed genes from labeled expression data: a brief review

HIV haplotype inference using a propagating dirichlet process mixture model

Improved and promising identification of human MicroRNAs by incorporating a high-quality negative set

Incorporation of biological pathway knowledge in the construction of priors for optimal Bayesian classification

Local exact pattern matching for non-fixed RNA structures

Maximizing deep coalescence cost

Multiple sequence alignment with hidden Markov models learned by random drift particle swarm optimization

Approximate k-Mer matching using fuzzy hash maps

Erratum to "Protein function prediction using multilabel ensemble classification"

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 10

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 9

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 8

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 7

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 6

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 5

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 4

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 3

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 2

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 1

A survey and comparative study of statistical tests for identifying differential expression from microarray data

Content Provider	ACM Digital Library
Author	Bandyopadhyay, Sanghamitra Mukhopadhyay, Anirban Mallik, Saurav
Copyright Year	2014
Abstract	DNA microarray is a powerful technology that can simultaneously determine the levels of thousands of transcripts (generated, for example, from genes/miRNAs) across different experimental conditions or tissue samples. The motto of differential expression analysis is to identify the transcripts whose expressions change significantly across different types of samples or experimental conditions. A number of statistical testing methods are available for this purpose. In this paper, we provide a comprehensive survey on different parametric and non-parametric testing methodologies for identifying differential expression from microarray data sets. The performances of the different testing methods have been compared based on some real-life miRNA and mRNA expression data sets. For validating the resulting differentially expressed miRNAs, the outcomes of each test are checked with the information available for miRNA in the standard miRNA database PhenomiR 2.0. Subsequently, we have prepared different simulated data sets of different sample sizes (from 10 to 100 per group/population) and thereafter the power of each test have been calculated individually. The comparative simulated study might lead to formulate robust and comprehensive judgements about the performance of each test in the basis of assumption of data distribution. Finally, a list of advantages and limitations of the different statistical tests has been provided, along with indications of some areas where further studies are required.
Starting Page	95
Ending Page	115
Page Count	21
File Format	PDF
ISSN	15455963
DOI	10.1109/TCBB.2013.147
Volume Number	11
Issue Number	1
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-01-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Differentially expressed transcripts Multiple testing corrections Parametric and nonparametric tests Power of test
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A Survey and Comparative Study of Statistical Tests for Identifying Differential Expression from Microarray Data

Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments (2002)

Statistical tests for identification of differentially expressed genes in cDNA microarray experiments

Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments (2002)

Spring: A Method for Identifying Differentially Expressed Genes in Microarray Data

Reproducibility-Optimized Test Statistic for Ranking Genes in Microarray Studies

A Powerful Approach for Effective Finding of Significantly Differentially Expressed Genes

Comparison of methods for identifying differentially expressed genes across multiple conditions from microarray data

Detecting differentially coexpressed genes from labeled expression data: a brief review

A survey and comparative study of statistical tests for identifying differential expression from microarray data

Similar Documents

A Survey and Comparative Study of Statistical Tests for Identifying Differential Expression from Microarray Data

Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments (2002)

Statistical tests for identification of differentially expressed genes in cDNA microarray experiments

Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments (2002)

Spring: A Method for Identifying Differentially Expressed Genes in Microarray Data

Reproducibility-Optimized Test Statistic for Ranking Genes in Microarray Studies

A Powerful Approach for Effective Finding of Significantly Differentially Expressed Genes

Comparison of methods for identifying differentially expressed genes across multiple conditions from microarray data

Detecting differentially coexpressed genes from labeled expression data: a brief review

A survey and comparative study of statistical tests for identifying differential expression from microarray data