Data Algorithms

Chapter 25. RNA Sequencing

In recent years, RNA (ribonucleic acid) sequencing has revolutionized the exploration of gene expression. Improvements in RNA sequencing methods have enabled researchers to rapidly profile and investigate the transcriptome. Dr. Ananya Mandel defines RNA as “an important molecule with long chains of nucleotides. A nucleotide contains a nitrogenous base, a ribose sugar, and a phosphate. Just like DNA, RNA is vital for living beings.” RNA’s main function is to transfer the genetic code needed for the creation of proteins from the nucleus to the ribosome. According to Dr. Mandel: “This process prevents the DNA from having to leave the nucleus. This keeps the DNA and genetic code protected from damage. Without RNA, proteins could never be made.”

This chapter will provide a complete MapReduce solution for a computational pipeline for analyzing RNA sequencing (RNA-Seq) data for differential gene expression. In our implementation, we will utilize two open source packages:

TopHat

A fast splice junction mapper for RNA-Seq reads. It aligns RNA-Seq reads to mammalian-sized genomes using the ultra-high-throughput short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons.

Cufflinks

Assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks ...