Bioinformatics for transcriptome sequencing


Transcriptomics has opened the way to study the genetic and functional information stored within any organism at an unprecedented scale and speed. For example, RNA-seq in principle enables the simultaneous study of transcript structure (such as alterna┬Čtive splicing), allelic information (e.g., SNPs) and expression with high resolution and broad dynamic range. Compared to genomic sequences, transcriptome sequences are dynamic: their states and quantities continually change based on internal and external factors. The evolution of Next-Generation Sequencing leads to high level of sequences and samples throughput. This has led to affordable prices for multi-sample analysis and has generated an increase in the demand for Whole Transcriptome Analysis.

In this training programme, we provide sessions on bioinformatics challenges associated with transcriptome analyses using short read sequences such as de-novo transcriptome assembly, analyzing gene expression levels of samples, comparing differential gene expression among multiple samples and novel isoforms, including the identification of alternatively spliced transcripts.

We have also included sessions that address the issue of quality check, alignment and assembly of reads; variant detection, annotation of assembled genome and comparative genomics. Now that there are many of these tools available the Bioinformatics community has begun to make applications that are useful for these specific applications.

Bioinformatics Centre