Jason Liu
Postdoctoral AssociateAbout
Research
Publications
2021
SCAN-ATAC-Sim: a scalable and efficient method for simulating single-cell ATAC-seq data from bulk-tissue experiments
Chen Z, Zhang J, Liu J, Zhang Z, Zhu J, Lee D, Xu M, Gerstein M. SCAN-ATAC-Sim: a scalable and efficient method for simulating single-cell ATAC-seq data from bulk-tissue experiments. Bioinformatics 2021, 37: 1756-1758. PMID: 33471102, PMCID: PMC8289380, DOI: 10.1093/bioinformatics/btaa1039.Peer-Reviewed Original Research
2020
STARRPeaker: uniform processing and accurate identification of STARR-seq active regions
Lee D, Shi M, Moran J, Wall M, Zhang J, Liu J, Fitzgerald D, Kyono Y, Ma L, White KP, Gerstein M. STARRPeaker: uniform processing and accurate identification of STARR-seq active regions. Genome Biology 2020, 21: 298. PMID: 33292397, PMCID: PMC7722316, DOI: 10.1186/s13059-020-02194-x.Peer-Reviewed Original ResearchNIMBus: a negative binomial regression based Integrative Method for mutation Burden Analysis
Zhang J, Liu J, McGillivray P, Yi C, Lochovsky L, Lee D, Gerstein M. NIMBus: a negative binomial regression based Integrative Method for mutation Burden Analysis. BMC Bioinformatics 2020, 21: 474. PMID: 33092526, PMCID: PMC7580035, DOI: 10.1186/s12859-020-03758-1.Peer-Reviewed Original ResearchConceptsDNase I hypersensitive sitesMutation rate heterogeneityDNA elementsCancer whole genome sequencesMutational hotspotsMutation burden analysisFunctional genomics dataNon-coding regionsGene regulatory networksWhole Genomes (PCAWG) projectWhole genome sequencesBackground mutation rateBurden analysisChromatin organizationReplication timingGenome sequenceRegulatory networksTranscription factorsHypersensitive sitesGenomic featuresRate heterogeneityGenome ProjectGenomic dataIntegrative methodGamma-Poisson mixture modelRADAR: annotation and prioritization of variants in the post-transcriptional regulome of RNA-binding proteins
Zhang J, Liu J, Lee D, Feng JJ, Lochovsky L, Lou S, Rutenberg-Schoenberg M, Gerstein M. RADAR: annotation and prioritization of variants in the post-transcriptional regulome of RNA-binding proteins. Genome Biology 2020, 21: 151. PMID: 32727537, PMCID: PMC7391703, DOI: 10.1186/s13059-020-01979-4.Peer-Reviewed Original ResearchConceptsTissue-specific inputsPost-transcriptional regulationDisease-specific variantsPrioritization of variantsVariant prioritization methodsTranscriptional regulationRNA structureBinding sitesRNAProteinPrioritization methodRegulationKey roleVariantsRegulomeGenomeSplicingGermlineExonsOverall impact scoreMotifConservationAnnotationDysregulationAn integrative ENCODE resource for cancer genomics
Zhang J, Lee D, Dhiman V, Jiang P, Xu J, McGillivray P, Yang H, Liu J, Meyerson W, Clarke D, Gu M, Li S, Lou S, Xu J, Lochovsky L, Ung M, Ma L, Yu S, Cao Q, Harmanci A, Yan KK, Sethi A, Gürsoy G, Schoenberg MR, Rozowsky J, Warrell J, Emani P, Yang YT, Galeev T, Kong X, Liu S, Li X, Krishnan J, Feng Y, Rivera-Mulia JC, Adrian J, Broach JR, Bolt M, Moran J, Fitzgerald D, Dileep V, Liu T, Mei S, Sasaki T, Trevilla-Garcia C, Wang S, Wang Y, Zang C, Wang D, Klein RJ, Snyder M, Gilbert DM, Yip K, Cheng C, Yue F, Liu XS, White KP, Gerstein M. An integrative ENCODE resource for cancer genomics. Nature Communications 2020, 11: 3696. PMID: 32728046, PMCID: PMC7391744, DOI: 10.1038/s41467-020-14743-w.Peer-Reviewed Original ResearchConceptsCell typesFunctional genomics datasetsEffect of MycStem-like stateNetwork-based annotationUncharacterized RBPsOncogenic TFSTARR-seqOncogene knockdownTranscription factorsGenomic datasetsOncogenic transformationGenome interpretationUniversal annotationCancer genomicsDifferential expressionSiRNA knockdownLuciferase assayTargeted validationRegulatorTumor transitionCustom annotationsAnnotationKnockdownCoherent workflowExpanded encyclopaedias of DNA elements in the human and mouse genomes
Moore J, Purcaro M, Pratt H, Epstein C, Shoresh N, Adrian J, Kawli T, Davis C, Dobin A, Kaul R, Halow J, Van Nostrand E, Freese P, Gorkin D, Shen Y, He Y, Mackiewicz M, Pauli-Behn F, Williams B, Mortazavi A, Keller C, Zhang X, Elhajjajy S, Huey J, Dickel D, Snetkova V, Wei X, Wang X, Rivera-Mulia J, Rozowsky J, Zhang J, Chhetri S, Zhang J, Victorsen A, White K, Visel A, Yeo G, Burge C, Lécuyer E, Gilbert D, Dekker J, Rinn J, Mendenhall E, Ecker J, Kellis M, Klein R, Noble W, Kundaje A, Guigó R, Farnham P, Cherry J, Myers R, Ren B, Graveley B, Gerstein M, Pennacchio L, Snyder M, Bernstein B, Wold B, Hardison R, Gingeras T, Stamatoyannopoulos J, Weng Z. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 2020, 583: 699-710. PMID: 32728249, PMCID: PMC7410828, DOI: 10.1038/s41586-020-2493-4.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsChromatinDatabases, GeneticDeoxyribonuclease IDNADNA FootprintingDNA MethylationDNA Replication TimingGenomeGenome, HumanGenomicsHistonesHumansMiceMice, TransgenicMolecular Sequence AnnotationRegistriesRegulatory Sequences, Nucleic AcidRNA-Binding ProteinsTranscription, GeneticTransposasesConceptsMouse genomeCandidate cis-regulatory elementsCis-regulatory elementsDNA Elements (ENCODE) projectMouse fetal developmentChromatin structureGene regulationRespective genomesCellular contextDNA elementsDNA methylationENCODE dataTranscription factorsRNA transcriptionWeb-based serverGenomeExpansive resourceRNAEncyclopediaProteinFetal developmentChromatinTranscriptionHumansMethylationDiNeR: a Differential graphical model for analysis of co-regulation Network Rewiring
Zhang J, Liu J, Lee D, Lou S, Chen Z, Gürsoy G, Gerstein M. DiNeR: a Differential graphical model for analysis of co-regulation Network Rewiring. BMC Bioinformatics 2020, 21: 281. PMID: 32615918, PMCID: PMC7333332, DOI: 10.1186/s12859-020-03605-3.Peer-Reviewed Original ResearchConceptsCo-regulation networkCo-regulatory networkNetwork rewiringDisease regulatorsGenome-wide binding profilesGM12878 cell lineRNA polymerase IITumor suppressor BRCA1Transcription factor bindsChIP-seq dataDifferential graphical modelsBinding profileComplete binding profilesKey TFsPolymerase IIHub regulatorsPhenotypic variationFactor bindsGene expressionExpression changesCancerous stateRisk genesRegulatorCell linesCoordinated mannerTopicNet: a framework for measuring transcriptional regulatory network change
Lou S, Li T, Kong X, Zhang J, Liu J, Lee D, Gerstein M. TopicNet: a framework for measuring transcriptional regulatory network change. Bioinformatics 2020, 36: i474-i481. PMID: 32657410, PMCID: PMC7355251, DOI: 10.1093/bioinformatics/btaa403.Peer-Reviewed Original ResearchConceptsRegulatory network changesTranscription factorsCellular statesDifferent regulatory programsCollection of genesDifferent cellular statesParticular cellular stateParticular transcription factorsRegulatory network connectivityKey transcription factorGene expression dataChromatin immunoprecipitationRegulatory networksCell statesExpression dataRegulatory programsHuman cellsDifferential survivalDiverse groupSupplementary dataDynamic changesLoss of targetImmunoprecipitationGenesActivity differences
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Mar 202527Thursday
- EveryoneNancy J. Brown, MD - Clemens Scherzer, MD - Xianjun Dong, PhD - Jason Liu - Stephen Strittmatter, MD, PhD, AB - Vlad Coric, MD - Thomas Biederer, PhD - Pietro De Camilli, MD - Sreeganga Chandra, PhD - Luke P. Lee - Jesse M. Cedarbaum, MD, FAAN (Neurology), FANA - Ana Vives-Rodriguez, MD