@article {49599, title = {BlindCall: ultra-fast base-calling of high-throughput sequencing data by blind deconvolution.}, volume = {30}, year = {2014}, month = {2014 May 1}, pages = {1214-9}, abstract = {

MOTIVATION: Base-calling of sequencing data produced by high-throughput sequencing platforms is a fundamental process in current bioinformatics analysis. However, existing third-party probabilistic or machine-learning methods that significantly improve the accuracy of base-calls on these platforms are impractical for production use due to their computational inefficiency.

RESULTS: We directly formulate base-calling as a blind deconvolution problem and implemented BlindCall as an efficient solver to this inverse problem. BlindCall produced base-calls at accuracy comparable to state-of-the-art probabilistic methods while processing data at rates 10 times faster in most cases. The computational complexity of BlindCall scales linearly with read length making it better suited for new long-read sequencing technologies.

}, keywords = {algorithms, High-Throughput Nucleotide Sequencing, HUMANS, Probability, Reproducibility of Results, Sequence Analysis, DNA, software, Time factors}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btu010}, author = {Ye, Chengxi and Hsiao, Chiaowen and Corrada Bravo, Hector} } @article {49605, title = {Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.}, volume = {30}, year = {2014}, month = {2014 May 15}, pages = {1363-9}, abstract = {

MOTIVATION: The recently released Infinium HumanMethylation450 array (the {\textquoteright}450k{\textquoteright} array) provides a high-throughput assay to quantify DNA methylation (DNAm) at \~{}450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years.

RESULTS: Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods.

AVAILABILITY AND IMPLEMENTATION: http://bioconductor.org/packages/release/bioc/html/minfi.html.

CONTACT: khansen@jhsph.edu; rafa@jimmy.harvard.edu

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

}, keywords = {Aged, algorithms, Colonic Neoplasms, DNA Methylation, Genome, High-Throughput Nucleotide Sequencing, HUMANS, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btu049}, author = {Aryee, Martin J and Jaffe, Andrew E and Corrada-Bravo, Hector and Ladd-Acosta, Christine and Feinberg, Andrew P and Hansen, Kasper D and Irizarry, Rafael A} }