{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Kannan L"],"funding":["NIAID NIH HHS","NIMHD NIH HHS","NHGRI NIH HHS","NCI NIH HHS","NIH HHS"],"pagination":["603-15"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC4945830"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["17(4)"],"pubmed_abstract":["Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative ge"],"journal":["Briefings in bioinformatics"],"pubmed_title":["Public data and open source tools for multi-assay genomic investigation of disease."],"pmcid":["PMC4945830"],"funding_grant_id":["G12 MD007599","U24 CA180996","U19 AI111224","U41 HG004059","S10 OD020069"],"pubmed_authors":["Castelo R","Gendoo DM","Davis S","Waldron L","Kannan L","El-Hachem N","Hansen KD","Gomez-Cabrero D","Culhane AC","Re A","Ramos M","Carey VJ","Haibe-Kains B","Safikhani Z","Morgan M"],"additional_accession":[]},"is_claimable":false,"name":"Public data and open source tools for multi-assay genomic investigation of disease.","description":"Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative ge","dates":{"release":"2016-01-01T00:00:00Z","publication":"2016 Jul","modification":"2025-04-25T22:33:05.719Z","creation":"2019-03-27T02:18:25Z"},"accession":"S-EPMC4945830","cross_references":{"pubmed":["26463000"],"doi":["10.1093/bib/bbv080"]}}