A report on the 2009 SIG on short read sequencing and algorithms (Short-SIG)

High-throughput sequencing (HTS) technologies are revolutionizing the way biologists acquire and analyze genomic data. HTS instruments, such as the Illumina Genomic Analyzer and the Applied Biosystems SOLiD System, are currently able to sequence tens of gigabases per week, at a cost of 200-fold less than previous methods, potentially enabling the routine sequencing of human and other genomes. Over the last few years the promise of HTS technologies has become a reality, however, realizing that the full promise of these technologies requires the development of computational methods that can analyze the resulting datasets to infer biological meaning. HTS can be used to study many biological problems, including assembling genomes of new organisms, identifying genome variation within a population, discovering novel transcripts, analyzing gene expression, discerning the regulatory mechanisms behind the expression levels and profiling the metagenome of a community. While many HTS datasets are readily available, the main bottleneck in the analysis is the dearth of computational methods that are able to directly answer biologists’ questions from these datasets. The Special Interest Group on Short Read Sequencing and Algorithms (Short-SIG), held in conjunction with the Intelligent Systems in Molecular Biology (ISMB) conference, is a meeting that brings together computational biologists interested in analyzing these HTS datasets. The first Short-SIG, held in Toronto in 2008, brought together over 120 attendees, and featured 18 podium presentations, with many of them addressing the computational problems of read mapping—the alignment of reads to a larger reference genome—and assembly—the de novo generation of the genome of an organism from short read data. During the year that followed, significant progress has been made in these fields, and the topic of the 2009 meeting, held in Stockholm on June 28, concentrated on the development of methods that can analyze the resulting read mappings and assemblies to infer biological meaning. The meeting brought together over 200 researchers, and featured 17 platform presentations selected from 27 abstracts and 17 full paper submissions. The keynote address at the SIG was delivered by Dr Edwin Cuppen of the Hubrecht Laboratory (Utrecht, The Netherlands). The paper submissions were handled in coordination with the Bioinformatics journal, and a physical copy of the Bioinformatics ‘virtual issue’on HTS, featuring papers published on this topic in Bioinformatics over the past year, was presented to all meeting attendees. Bioinformatics also sponsored a best paper award for the conference, given to Kai Ye and his co-authors for the paper ‘Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads’, as well as an award for a paper chosen from the ‘virtual issue’, that was given to Cole Trapnell and colleagues for ‘TopHat: discovering splice junctions with RNA-Seq’.