Statistical methods in integrative genomics aim to answer important biology questions by jointly analyzing multiple types of genomic data (vertical integration) or aggregating the same type of data across multiple studies (horizontal integration). In this article, we introduce different types of genomic data and data resources, and then review statistical methods of integrative genomics, with emphasis on the motivation and rationale of these methods. We conclude with some summary points and future research directions
Advances in high-throughput technologies have led to the acquisition of various types of -omic data ...
My thesis is about developing statistical methods by integrating disparate data sources with real da...
In Chapter 2, we compare the power of association studies using cases and screened controls to studi...
Integrative genomic data analysis is a powerful tool to study the complex biological processes behin...
In recent years, technological breakthroughs have greatly enhanced our ability to understand the com...
Recent technological advances have made it possible to collect multiple types of genomic data on the...
Advances in high-throughput technologies have led to the acquisition of various types of -omic data ...
The objective of this book is to describe procedures for analyzing genome-wide association studies (...
The Genome-wide Association study (GWAS) is one of the primary tools for understanding the genetic b...
With the continued accumulation of genomic data at ever increasing resolution the challenge ahead li...
In recent years, large-scale studies have been conducted to investigate the genetic architecture und...
Although the cost of high-throughput technologies has decreased dramatically, it is still expensive ...
The purpose of cancer genome sequencing studies is to determine the nature and types of alterations ...
The "big data" revolution of the past decade has allowed researchers to procure or access biological...
Abstract In recent years, a very large variety of statistical methodologies, at various levels of co...
Advances in high-throughput technologies have led to the acquisition of various types of -omic data ...
My thesis is about developing statistical methods by integrating disparate data sources with real da...
In Chapter 2, we compare the power of association studies using cases and screened controls to studi...
Integrative genomic data analysis is a powerful tool to study the complex biological processes behin...
In recent years, technological breakthroughs have greatly enhanced our ability to understand the com...
Recent technological advances have made it possible to collect multiple types of genomic data on the...
Advances in high-throughput technologies have led to the acquisition of various types of -omic data ...
The objective of this book is to describe procedures for analyzing genome-wide association studies (...
The Genome-wide Association study (GWAS) is one of the primary tools for understanding the genetic b...
With the continued accumulation of genomic data at ever increasing resolution the challenge ahead li...
In recent years, large-scale studies have been conducted to investigate the genetic architecture und...
Although the cost of high-throughput technologies has decreased dramatically, it is still expensive ...
The purpose of cancer genome sequencing studies is to determine the nature and types of alterations ...
The "big data" revolution of the past decade has allowed researchers to procure or access biological...
Abstract In recent years, a very large variety of statistical methodologies, at various levels of co...
Advances in high-throughput technologies have led to the acquisition of various types of -omic data ...
My thesis is about developing statistical methods by integrating disparate data sources with real da...
In Chapter 2, we compare the power of association studies using cases and screened controls to studi...