Bioinformatics is an emerging field in which statistical and computational techniques
are used extensively to analyze and interpret biological data obtained
from high-throughput genomic technologies. Genomic technologies allow us
to monitor thousands of biological processes going on inside living organisms
in one snapshot, and are rapidly growing as driving forces of research,
particularly in the genetics, biomedical, biotechnology, and pharmaceutical
industries.
The success of genome technologies and related techniques, however, heavily
depends on correct statistical analyses of genomic data. Through statistical analyses
and the graphical displays of genomic data, genomic experiments allow
biologists to assimilate and explore the data in a natural and intuitive manner.
The storage, retrieval, interpretation, and integration of large volumes of data
generated by genomic technologies demand increasing dependence on sophisticated
computer and statistical inference techniques. New statistical tools have
been developed to make inferences from the genomic data obtained through
genomic studies in a more meaningful way.
This textbook is of an interdisciplinary nature, and material presented here can
be covered in a one- or two-semester course. It is written to give a solid base in
statistics while emphasizing applications in genomics. It is my sincere attempt
to integrate different fields to understand the high-throughput biological data
and describe various statistical techniques to analyze data. In this textbook, new
methods based on Bayesian techniques,MCMCmethods, likelihood functions,
design of experiments, and nonparametric methods, along with traditional
methods, are discussed. Insights into some useful software such as BAMarray,
ORIGEN, and SAM are provided.