@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} } @article {38276, title = {Gene expression anti-profiles as a basis for accurate universal cancer signatures}, journal = {BMC bioinformaticsBMC Bioinformatics}, volume = {13}, year = {2012}, note = {http://www.ncbi.nlm.nih.gov/pubmed/23088656?dopt=Abstract}, type = {10.1186/1471-2105-13-272}, abstract = {BACKGROUND: Early screening for cancer is arguably one of the greatest public health advances over the last fifty years. However, many cancer screening tests are invasive (digital rectal exams), expensive (mammograms, imaging) or both (colonoscopies). This has spurred growing interest in developing genomic signatures that can be used for cancer diagnosis and prognosis. However, progress has been slowed by heterogeneity in cancer profiles and the lack of effective computational prediction tools for this type of data. RESULTS: We developed anti-profiles as a first step towards translating experimental findings suggesting that stochastic across-sample hyper-variability in the expression of specific genes is a stable and general property of cancer into predictive and diagnostic signatures. Using single-chip microarray normalization and quality assessment methods, we developed an anti-profile for colon cancer in tissue biopsy samples. To demonstrate the translational potential of our findings, we applied the signature developed in the tissue samples, without any further retraining or normalization, to screen patients for colon cancer based on genomic measurements from peripheral blood in an independent study (AUC of 0.89). This method achieved higher accuracy than the signature underlying commercially available peripheral blood screening tests for colon cancer (AUC of 0.81). We also confirmed the existence of hyper-variable genes across a range of cancer types and found that a significant proportion of tissue-specific genes are hyper-variable in cancer. Based on these observations, we developed a universal cancer anti-profile that accurately distinguishes cancer from normal regardless of tissue type (ten-fold cross-validation AUC > 0.92). CONCLUSIONS: We have introduced anti-profiles as a new approach for developing cancer genomic signatures that specifically takes advantage of gene expression heterogeneity. We have demonstrated that anti-profiles can be successfully applied to develop peripheral-blood based diagnostics for cancer and used anti-profiles to develop a highly accurate universal cancer signature. By using single-chip normalization and quality assessment methods, no further retraining of signatures developed by the anti-profile approach would be required before their application in clinical settings. Our results suggest that anti-profiles may be used to develop inexpensive and non-invasive universal cancer screening tests.}, keywords = {Area Under Curve, Colonic Neoplasms, Gene Expression Profiling, Genetic Variation, Genomics, HUMANS, Oligonucleotide Array Sequence Analysis, Prognosis, Transcriptome, Tumor Markers, Biological}, author = {H{\'e}ctor Corrada Bravo and Pihur, Vasyl and McCall, Matthew and Irizarry, Rafael A. and Leek, Jeffrey T.} }