Statistics And Data Analysis For Microarrays Using R And Bioconductor, Second Edition (chapman & Hall/crc Mathematical And Computational Biology)
by Sorin Draghici /
2011 / English / PDF
130.8 MB Download
Richly illustrated in color,
Richly illustrated in color,Statistics and Data Analysis
for Microarrays Using R and Bioconductor, Second Edition
Statistics and Data Analysis
for Microarrays Using R and Bioconductor, Second Edition
provides a clear and rigorous description of powerful analysis
techniques and algorithms for mining and interpreting biological
information. Omitting tedious details, heavy formalisms, and
cryptic notations, the text takes a hands-on, example-based
approach that teaches students the basics of R and microarray
technology as well as how to choose and apply the proper data
analysis tool to specific problems.
provides a clear and rigorous description of powerful analysis
techniques and algorithms for mining and interpreting biological
information. Omitting tedious details, heavy formalisms, and
cryptic notations, the text takes a hands-on, example-based
approach that teaches students the basics of R and microarray
technology as well as how to choose and apply the proper data
analysis tool to specific problems.New to the Second
Edition
New to the Second
EditionCompletely updated and double the size
of its predecessor, this timely second edition replaces the
commercial software with the open source R and Bioconductor
environments. Fourteen new chapters cover such topics as the
basic mechanisms of the cell, reliability and reproducibility
issues in DNA microarrays, basic statistics and linear models in
R, experiment design, multiple comparisons, quality control, data
pre-processing and normalization, Gene Ontology analysis, pathway
analysis, and machine learning techniques. Methods are
illustrated with toy examples and real data and the R code for
all routines is available on an accompanying CD-ROM.
Completely updated and double the size
of its predecessor, this timely second edition replaces the
commercial software with the open source R and Bioconductor
environments. Fourteen new chapters cover such topics as the
basic mechanisms of the cell, reliability and reproducibility
issues in DNA microarrays, basic statistics and linear models in
R, experiment design, multiple comparisons, quality control, data
pre-processing and normalization, Gene Ontology analysis, pathway
analysis, and machine learning techniques. Methods are
illustrated with toy examples and real data and the R code for
all routines is available on an accompanying CD-ROM.
With all the necessary prerequisites included, this best-selling
book guides students from very basic notions to advanced analysis
techniques in R and Bioconductor. The first half of the text
presents an overview of microarrays and the statistical elements
that form the building blocks of any data analysis. The second
half introduces the techniques most commonly used in the analysis
of microarray data.
With all the necessary prerequisites included, this best-selling
book guides students from very basic notions to advanced analysis
techniques in R and Bioconductor. The first half of the text
presents an overview of microarrays and the statistical elements
that form the building blocks of any data analysis. The second
half introduces the techniques most commonly used in the analysis
of microarray data.