Chorbadjiev, Liubomir, Cokol, Murat, Weinstein, Zohar, Shi, Kevin, Fleisch, Chris, Dimitrov, Nikolay, Mladenov, Svetlin, Xu, Simon, Hall, Jake, Ford, Steven, Lee, Yoon-Ha, Yamrom, Boris, Marks, Steven, Munoz, Adriana, Lash, Alex, Volfovsky, Natalia, Iossifov, Ivan (February 2024) The Genotype and Phenotypes in Families (GPF) platform manages the large and complex data at SFARI. bioRxiv. (Submitted)
Abstract
The exploration of genotypic variants impacting phenotypes is a cornerstone in genetics research. The emergence of vast collections containing deeply genotyped and phenotyped families has made it possible to pursue the search for variants associated with complex diseases. However, managing these large-scale datasets requires specialized computational tools tailored to organize and analyze the extensive data. GPF (Genotypes and Phenotypes in Families) is an open-source platform ( https://github.com/iossifovlab/gpf ) that manages genotypes and phenotypes derived from collections of families. The GPF interface allows interactive exploration of genetic variants, enrichment analysis for de novo mutations, and phenotype/genotype association tools. In addition, GPF allows researchers to share their data securely with the broader scientific community. GPF is used to disseminate two large-scale family collection datasets (SSC, SPARK) for the study of autism funded by the SFARI foundation. However, GPF is versatile and can manage genotypic data from other small or large family collections. Our GPF-SFARI GPF instance ( https://gpf.sfari.org/ ) provides protected access to comprehensive genotypic and phenotypic data for the SSC and SPARK. In addition, GPF-SFARI provides public access to an extensive collection of de novo mutations identified in individuals with autism and related disorders and to gene-level statistics of the protected datasets characterizing the genes' roles in autism. Here, we highlight the primary features of GPF within the context of GPF-SFARI.
Item Type: | Paper |
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Subjects: | bioinformatics bioinformatics > genomics and proteomics > genetics & nucleic acid processing bioinformatics > genomics and proteomics bioinformatics > genomics and proteomics > genetics & nucleic acid processing > genomes |
CSHL Authors: | |
Communities: | CSHL labs > Iossifov lab |
SWORD Depositor: | CSHL Elements |
Depositing User: | CSHL Elements |
Date: | 11 February 2024 |
Date Deposited: | 04 Mar 2024 13:56 |
Last Modified: | 04 Mar 2024 13:56 |
PMCID: | PMC10871337 |
Related URLs: | |
URI: | https://repository.cshl.edu/id/eprint/41451 |
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