Abstract
BackgroundNext-generation DNA sequencing technologies such as Illumina's Solexa platform and Roche's 454 approach provide new avenues for investigating genome-scale questions. However, they also present novel analytical challenges that must be met for their effective application to biological questions.ResultsHere we report the availability of tileQC, a tile-based quality control system for Solexa data written in the R language. TileQC provides a means of recognizing bias and error in Solexa output by graphically representing data generated by flow cell tiles. The data represented in the images is then made available in the R environment for further analysis and automation of error detection.ConclusionTileQC offers a highly adaptable and powerful tool for the quality control of Solexa-based DNA sequence data.
Highlights
Next-generation DNA sequencing technologies such as Illumina's Solexa platform and Roche's 454 approach provide new avenues for investigating genome-scale questions
Illumina's Solexa sequencing approach consists of a process whereby DNA samples are nebulized to small pieces (~150 bp), ligated to adapters that bind to linker molecules on the surface of a flow cell where amplified DNA clusters are sequenced in real-time using Solexa's reversible dye terminator approach [5]
All C. elegans data were subject to the standard Solexa data analysis pipeline prior to application of tileQC tools
Summary
We report the availability of tileQC, a tile-based quality control system for Solexa data written in the R language. TileQC provides a means of recognizing bias and error in Solexa output by graphically representing data generated by flow cell tiles. The data represented in the images is made available in the R environment for further analysis and automation of error detection
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