Literature DB >> 20672376

pfSNP: An integrated potentially functional SNP resource that facilitates hypotheses generation through knowledge syntheses.

Jingbo Wang1, Mostafa Ronaghi, Samuel S Chong, Caroline G L Lee.   

Abstract

Currently, >14,000,000 single nucleotide polymorphisms (SNPs) are reported. Identifying phenotype-affecting SNPs among these many SNPs pose significant challenges. Although several Web resources are available that can inform about the functionality of SNPs, these resources are mainly annotation databases and are not very comprehensive. In this article, we present a comprehensive, well-annotated, integrated pfSNP (potentially functional SNPs) Web resource (http://pfs.nus.edu.sg/), which is aimed to facilitate better hypothesis generation through knowledge syntheses mediated by better data integration and a user-friendly Web interface. pfSNP integrates >40 different algorithms/resources to interrogate >14,000,000 SNPs from the dbSNP database for SNPs of potential functional significance based on previous published reports, inferred potential functionality from genetic approaches as well as predicted potential functionality from sequence motifs. Its query interface has the user-friendly "auto-complete, prompt-as-you-type" feature and is highly customizable, facilitating different combination of queries using Boolean-logic. Additionally, to facilitate better understanding of the results and aid in hypotheses generation, gene/pathway-level information with text clouds highlighting enriched tissues/pathways as well as detailed-related information are also provided on the results page. Hence, the pfSNP resource will be of great interest to scientists focusing on association studies as well as those interested to experimentally address the functionality of SNPs.
© 2010 Wiley-Liss, Inc.

Mesh:

Year:  2011        PMID: 20672376     DOI: 10.1002/humu.21331

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  17 in total

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7.  Robust Performance of Potentially Functional SNPs in Machine Learning Models for the Prediction of Atorvastatin-Induced Myalgia.

Authors:  Brandon N S Ooi; Ariel F Ying; Yong Zher Koh; Yu Jin; Sherman W L Yee; Justin H S Lee; Samuel S Chong; Jack W C Tan; Jianjun Liu; Caroline G Lee; Chester L Drum
Journal:  Front Pharmacol       Date:  2021-04-22       Impact factor: 5.810

8.  GWASdb: a database for human genetic variants identified by genome-wide association studies.

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9.  dbNSFP: a lightweight database of human nonsynonymous SNPs and their functional predictions.

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Journal:  Hum Mutat       Date:  2011-08       Impact factor: 4.878

10.  A fast and powerful W-test for pairwise epistasis testing.

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