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Statistical Approach to Study Microarray Analysis Using Bioconductor

Drushti Bhatt

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ISBN 10: 3659133418 / ISBN 13: 9783659133411
Published by LAP Lambert Academic Publishing
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64 pages. Dimensions: 8.7in. x 5.9in. x 0.1in.Microarray is a novel technology to identify gene expression of thousands of genes simultaneously. This work is attempted to perform microarray data analyses to determine differential gene expression using the open-source R programming environment in conjunction with the open-source Bioconductor software. We describe procedures for analysis of data using box plots and recommended procedures from Affymetrix for quality control are discussed. The Robust Multichip Averaging (RMA) and MAS5 procedure was used for background correction, normalization and summarization of the AffyBatch probe-level data to obtain expression level data and to discover differentially expressed genes. . Heatmaps are used to demonstrate over and under expressed genes in conjunction with t-statistics for determining interesting genes while pFDR was performed to remove false negative. We showed, with real data, how implementation of functions in R and Bioconductor successfully identified differentially expressed genes that may play a role in obesity. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9783659133411

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Title: Statistical Approach to Study Microarray ...

Publisher: LAP Lambert Academic Publishing

Binding: Paperback

Book Condition:New

Book Type: Paperback

About this title

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Microarray is a novel technology to identify gene expression of thousands of genes simultaneously. This work is attempted to perform microarray data analyses to determine differential gene expression using the open-source R programming environment in conjunction with the open-source Bioconductor software.We describe procedures for analysis of data using box plots and recommended procedures from Affymetrix for quality control are discussed. The Robust Multichip Averaging (RMA) and MAS5 procedure was used for background correction, normalization and summarization of the AffyBatch probe-level data to obtain expression level data and to discover differentially expressed genes.. Heatmaps are used to demonstrate over and under expressed genes in conjunction with t-statistics for determining interesting genes while pFDR was performed to remove false negative. We showed, with real data, how implementation of functions in R and Bioconductor successfully identified differentially expressed genes that may play a role in obesity.

About the Author:

Pursuing M.Phil Bioinformatics from Gujarat University, Ahmedabad, India. Completed research work on Microarray data analysis using R Language. Presently working on the project miRNA(microRNA), targeting to treat disease in cellular level.

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