Poster abstracts

Poster number 102 submitted by Kenji Oman

Computational methods for the analysis of high throughput sequencing data in RNA biology

Kenji Oman (Department of Physics, Center for RNA Biology; The Ohio State University), Kurt Fredrick (Department of Microbiology, Ohio State Biochemistry Program, Center for RNA Biology; The Ohio State University), Dan Schoenberg (Department of Molecular and Cellular Biochemistry, Ohio State Biochemistry Program, Center for RNA Biology; The Ohio State University), Ralf Bundschuh (Department of Physics, Department of Chemistry and Biochemistry, Division of Hematology, Center for RNA Biology; The Ohio State University)

Abstract:
High Throughput Sequencing (HTS) techniques are useful in the study of RNA Biology, providing relatively fast and inexpensive genome-wide coverage. However, they produce unique challenges, most notably in the large volumes of information generated, and in the fragmentation of RNA reads across exon boundaries. There exist well established tools for global differential expression analysis using RNA-Seq, but there are many other applications of HTS in RNA Biology, where the local coverage along the transcripts is of interest, such as, e.g., ribosome profiling. Here we introduce computer programs and techniques developed to analyze such specialized HTS data sets. In particular, we share techniques used to, from an aligned data set, remove contaminant reads (such as rRNA in a ribosome profiling study), visualize genome-wide coverage, aggregate reads by transcripts, normalize data to different standards, calculate coverage ratios, handle biological replicates, and quantify and identify changes in read distribution along transcripts, both globally and transcript by transcript. One benefit of these tools is that they can be equally applied to whole transcriptome data sets (such as TrueSeq), to ribosome profiling data sets, or to other data sets resulting from special purpose library construction schemes involving RNA. We also discuss some of the quality control mechanisms developed to test wet lab effectiveness and program validity.

Keywords: Computation, High Throughput Sequencing, Ribosome Profiling