Next Generation Microarray Bioinformatics: Methods and Protocols
Preface
The twenty-first century is the time of excitement and optimism for biomedical research.
Since the completion of the human genome project in 2001, we are entering into the
postgenome era where the key research efforts are now interpreting and making sense of
these massive genomic data, in order to translate into disease treatment and management.
Over the past decade, DNA-based microarrays have been the assays of choice for highthroughput
studies of gene expression. Microarray-based expression profiling was
provided, for the first time, by means of monitoring genome-wide gene expression changes
in a single experiment. Though microarray technology has been widely employed to reveal
molecular portraits of gene expression in various cancers’ subtypes and correlations with
disease progression as well as response to drug treatments, it is not limited to measure gene
expression. As the technology became established in early 2000, researchers began to use
microarrays to measure other important biological phenomena. For example, (1) Microarrays
are being used to genotype single-nucleotide polymorphisms (SNPs) by hybridizing
the DNA of individuals to arrays of oligonucleotides representing different polymorphic
alleles. The SNP microarray has accelerated genome-wide association studies over the last 5
years, and many loci that are associated with diseases have been discovered and validated.
Similarly, another innovative application of the SNP microarray is to interrogate allelespecific
expression for identifying disease-associated genes. (2) Array-comparative genomic
hybridization (aCGH) is being used to detect genomic structural variations, such as
segments of the genome that have varying numbers of copies in different individuals. (3)
Epigenetic modifications such as methylation at CpG sites can also be assessed by microarray.
(4) Using ChIP-chip assay, genome-wide protein–DNA interactions and chromatin
modifications can be profiled by microarrays. (5) More recently, microarray has been used
to measure genome-wide microRNA expression patterns to reveal the regulatory role of
these noncoding RNAs in disease states. Obviously, the progress of microarray applications
is tightly associated with the development of novel computational and statistical methods
to analyze and interpret these data sets.
Recent improvements in the efficiency, quality, and cost of genome-wide sequencing
have prompted biologists and biomedical researchers to move away from microarray-based
technology to ultrahigh-throughput, massively parallel genomic sequencing (Next Generation
Sequencing, NGS) technology. NGS technology opens up new research avenues for
the investigation of a wide range of biological and medical questions across the entire
genome at single base resolution; for example, sequencing of several human genomes,
monitoring of genome-wide transcription levels (RNA-seq), understanding of epigenetic
phenomena, DNA–protein interactions (ChIP-seq), and de novo sequencing of several
genomes. Despite the differences in the underlying sequencing technologies of various
NGS machines, the common output from them are the capability to generate tens of
millions of short reads (tags) from each experimental run. Thus, NGS technology shifts the
bottleneck in sequencing processes from experimental data production to computationally
intensive informatics-based data analysis. As in the early days of microarray data analysis,
novel computational and statistical methods tailored to NGS are urgently needed for
drawing meaningful and accurate conclusions from the massive short reads. Furthermore,
it is expected that NGS technology may eventually replace microarray technology in the
next decade, which will grow from a pioneering method applied by innovators at the
cutting edge research to a ubiquitous technique that will allow researchers to investigate
“big-picture” questions in biology at much higher resolution.
This book, Next Generation Microarray Bioinformatics, is our attempt to bring
together current computational and statistical methods in analyzing and interpreting
both microarray and NGS data. Here, we have compiled and edited 26 chapters that
cover a wide range of methodological and application topics in microarray and NGS
bioinformatics. These chapters are organized into five thematic sections: (1) Resources
for Microarray Bioinformatics; (2) Microarray Data Analysis; (3) Microarray Bioinformatics
in Systems Biology; (4) Next Generation Sequencing Data Analysis; and (5) Emerging
Applications of Microarray and Next Generation Sequencing. Each chapter is a selfcontained
review of a specific methodological or application topic. Every chapter typically
starts with a brief review of a particular subject, then describes in detail the computational
and statistical techniques used to solve the biological questions, and finally discusses the
computational results generated by these bioinformatics tools. Therefore, the reader need
not read the chapters in a sequential manner. We expect this book would be a valuable
methodological resource not only to molecular biologists and computational biologists
who are interested in understanding the principle of these methods and designing future
research project, but also to computer scientists and statisticians who work in a microarray
core facility or other similar organizations that provide service for the high-throughput
experiment community.
Recent improvements in the efficiency, quality, and cost of genome-wide sequencing have prompted biologists and biomedical researchers to move away from microarray-based technology to ultra high-throughput, massively parallel genomic sequencing (Next Generation Sequencing, NGS) technology. In Next Generation Microarray Bioinformatics: Methods and Protocols, expert researchers in the field provide techniques to bring together current computational and statistical methods to analyze and interpreting both microarray and NGS data. These methods and techniques include resources for microarray bioinformatics, microarray data analysis, microarray bioinformatics in systems biology, next generation sequencing data analysis, and emerging applications of microarray and next generation sequencing. Written in the highly successful Methods in Molecular Biology™ series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Authoritative and practical, Next Generation Microarray Bioinformatics: Methods and Protocols seeks to aid scientists in the further study of this crucially important research into the human DNA.
2012 -- 417 Pages -- ISBN: 161779399X -- PDF -- 8.64 MB
Download
*
Preface
The twenty-first century is the time of excitement and optimism for biomedical research.
Since the completion of the human genome project in 2001, we are entering into the
postgenome era where the key research efforts are now interpreting and making sense of
these massive genomic data, in order to translate into disease treatment and management.
Over the past decade, DNA-based microarrays have been the assays of choice for highthroughput
studies of gene expression. Microarray-based expression profiling was
provided, for the first time, by means of monitoring genome-wide gene expression changes
in a single experiment. Though microarray technology has been widely employed to reveal
molecular portraits of gene expression in various cancers’ subtypes and correlations with
disease progression as well as response to drug treatments, it is not limited to measure gene
expression. As the technology became established in early 2000, researchers began to use
microarrays to measure other important biological phenomena. For example, (1) Microarrays
are being used to genotype single-nucleotide polymorphisms (SNPs) by hybridizing
the DNA of individuals to arrays of oligonucleotides representing different polymorphic
alleles. The SNP microarray has accelerated genome-wide association studies over the last 5
years, and many loci that are associated with diseases have been discovered and validated.
Similarly, another innovative application of the SNP microarray is to interrogate allelespecific
expression for identifying disease-associated genes. (2) Array-comparative genomic
hybridization (aCGH) is being used to detect genomic structural variations, such as
segments of the genome that have varying numbers of copies in different individuals. (3)
Epigenetic modifications such as methylation at CpG sites can also be assessed by microarray.
(4) Using ChIP-chip assay, genome-wide protein–DNA interactions and chromatin
modifications can be profiled by microarrays. (5) More recently, microarray has been used
to measure genome-wide microRNA expression patterns to reveal the regulatory role of
these noncoding RNAs in disease states. Obviously, the progress of microarray applications
is tightly associated with the development of novel computational and statistical methods
to analyze and interpret these data sets.
Recent improvements in the efficiency, quality, and cost of genome-wide sequencing
have prompted biologists and biomedical researchers to move away from microarray-based
technology to ultrahigh-throughput, massively parallel genomic sequencing (Next Generation
Sequencing, NGS) technology. NGS technology opens up new research avenues for
the investigation of a wide range of biological and medical questions across the entire
genome at single base resolution; for example, sequencing of several human genomes,
monitoring of genome-wide transcription levels (RNA-seq), understanding of epigenetic
phenomena, DNA–protein interactions (ChIP-seq), and de novo sequencing of several
genomes. Despite the differences in the underlying sequencing technologies of various
NGS machines, the common output from them are the capability to generate tens of
millions of short reads (tags) from each experimental run. Thus, NGS technology shifts the
bottleneck in sequencing processes from experimental data production to computationally
intensive informatics-based data analysis. As in the early days of microarray data analysis,
novel computational and statistical methods tailored to NGS are urgently needed for
drawing meaningful and accurate conclusions from the massive short reads. Furthermore,
it is expected that NGS technology may eventually replace microarray technology in the
next decade, which will grow from a pioneering method applied by innovators at the
cutting edge research to a ubiquitous technique that will allow researchers to investigate
“big-picture” questions in biology at much higher resolution.
This book, Next Generation Microarray Bioinformatics, is our attempt to bring
together current computational and statistical methods in analyzing and interpreting
both microarray and NGS data. Here, we have compiled and edited 26 chapters that
cover a wide range of methodological and application topics in microarray and NGS
bioinformatics. These chapters are organized into five thematic sections: (1) Resources
for Microarray Bioinformatics; (2) Microarray Data Analysis; (3) Microarray Bioinformatics
in Systems Biology; (4) Next Generation Sequencing Data Analysis; and (5) Emerging
Applications of Microarray and Next Generation Sequencing. Each chapter is a selfcontained
review of a specific methodological or application topic. Every chapter typically
starts with a brief review of a particular subject, then describes in detail the computational
and statistical techniques used to solve the biological questions, and finally discusses the
computational results generated by these bioinformatics tools. Therefore, the reader need
not read the chapters in a sequential manner. We expect this book would be a valuable
methodological resource not only to molecular biologists and computational biologists
who are interested in understanding the principle of these methods and designing future
research project, but also to computer scientists and statisticians who work in a microarray
core facility or other similar organizations that provide service for the high-throughput
experiment community.
Recent improvements in the efficiency, quality, and cost of genome-wide sequencing have prompted biologists and biomedical researchers to move away from microarray-based technology to ultra high-throughput, massively parallel genomic sequencing (Next Generation Sequencing, NGS) technology. In Next Generation Microarray Bioinformatics: Methods and Protocols, expert researchers in the field provide techniques to bring together current computational and statistical methods to analyze and interpreting both microarray and NGS data. These methods and techniques include resources for microarray bioinformatics, microarray data analysis, microarray bioinformatics in systems biology, next generation sequencing data analysis, and emerging applications of microarray and next generation sequencing. Written in the highly successful Methods in Molecular Biology™ series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Authoritative and practical, Next Generation Microarray Bioinformatics: Methods and Protocols seeks to aid scientists in the further study of this crucially important research into the human DNA.
2012 -- 417 Pages -- ISBN: 161779399X -- PDF -- 8.64 MB
Download
*