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Predicted Impact of Coding SNPs (PICS) database

Project Coordinators: M Rudd & RS Houlston

We have classified and catalogued the predicted impact on protein function of non-synonymous single nucleotide polymorphisms (nsSNPs) in genes relevant to the biology of cancer using in silico computational tools. The data is supplementary to that published in: Matthew F. Rudd, Richard D. Williams, Emily L. Webb, Steffen Schmidt, Gabrielle S. Sellick, Richard S. Houlston. The PICS (Predicted Impact of Coding SNPs) database. Cancer Epidemiology, Biomarkers and Prevention (in press).

Supplementary Table 1 details 9,537 validated bi-allelic nsSNPs retrieved from NCBI dbSNP Build 123 located within one of 21,506 annotated genes. The data is available in Excel (.xls) and plain text (.txt) formats.

Supplementary Table 2
details the 7,080 genes curated on the basis of their potential biological relevance to cancer. The data is available in Excel (.xls) format.

Supplementary Table 3 details 3,009 nsSNPs located within one of 7,080 candidate cancer genes, with minor allele frequencies (MAF) >= 0.01 validated in Caucasian populations. The predicted impact on wild-type protein structure and function was computed for each entry using three freely available algorithms: Grantham matrix¹, PolyPhen², and SIFT³. The data is available in Excel (.xls) and plain text (.txt) formats.

Header descriptions for Tables 1 & 3 are found in the Readme (.doc) file.

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