Background: Next-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. Results: Here 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. Conclusion: TileQC offers a highly adaptable and powerful tool for the quality control of Solexa-based DNA sequence data.
Bibliographical noteFunding Information:
We thank Larry J. Wilhelm and Dana K. Howe for help with developing tileQC. Thanks to Chris Sullivan and Mark Dasenko at the OSU Center for Genome Research and Biocomputing for assistance with Solexa data and computing support. Also thanks to Brian Knaus, Dr. Rongkun Shen, and Dr. Albyn Jones for valuable advice. We are grateful to the National Institutes of Health and OSU Computational and Genome Biology Initiative for funding support.