2020
Data Sanitization to Reduce Private Information Leakage from Functional Genomics
Gürsoy G, Emani P, Brannon CM, Jolanki OA, Harmanci A, Strattan JS, Cherry JM, Miranker AD, Gerstein M. Data Sanitization to Reduce Private Information Leakage from Functional Genomics. Cell 2020, 183: 905-917.e16. PMID: 33186529, PMCID: PMC7672785, DOI: 10.1016/j.cell.2020.09.036.Peer-Reviewed Original ResearchConceptsFunctional genomicsSingle-cell RNA sequencingAccurate reference genomesFunctional genomics datasetsFunctional genomics experimentsOrganismal phenotypesGene regulationReference genomeNext-generation sequencingRaw readsGenomics experimentsRNA sequencingGenomic datasetsGenetic variantsGenomicsKnown individualsSequencingReadsEnvironmental samplesGenomeIlluminaPhenotypeGood statistical powerRegulationStatistical power
2016
Quantification of private information leakage from phenotype-genotype data: linking attacks
Harmanci A, Gerstein M. Quantification of private information leakage from phenotype-genotype data: linking attacks. Nature Methods 2016, 13: 251-256. PMID: 26828419, PMCID: PMC4834871, DOI: 10.1038/nmeth.3746.Peer-Reviewed Original Research
2011
Genomics and Privacy: Implications of the New Reality of Closed Data for the Field
Greenbaum D, Sboner A, Mu XJ, Gerstein M. Genomics and Privacy: Implications of the New Reality of Closed Data for the Field. PLOS Computational Biology 2011, 7: e1002278. PMID: 22144881, PMCID: PMC3228779, DOI: 10.1371/journal.pcbi.1002278.Peer-Reviewed Original ResearchConceptsPrivacy issuesGenomic privacySecure cloud computing environmentCloud computing environmentPersonal genomic dataComputing environmentPrivacy problemsPrivate dataData securityPrivacy concernsOpen sourceOpen dataPrivacyLarge datasetsImportant data setsVariant informationClosed dataData setsFuture accessSmall labsDatasetGenome CenterGenomic dataComputational strategyLarge scale