2022
Benchmarking automated cell type annotation tools for single-cell ATAC-seq data
Wang Y, Sun X, Zhao H. Benchmarking automated cell type annotation tools for single-cell ATAC-seq data. Frontiers In Genetics 2022, 13: 1063233. PMID: 36583014, PMCID: PMC9792779, DOI: 10.3389/fgene.2022.1063233.Peer-Reviewed Original ResearchCell type annotationScATAC-seq dataScRNA-seq dataScATAC-seqCell typesSingle-cell ATAC-seq dataAvailable single-cell datasetsRegulatory genomic regionsScRNA-seq data setsSingle-cell datasetsATAC-seq dataNovel cell typesSimilar cell typesSeurat v3Genomic regionsSequencing depthComplex tissuesDeep annotationAnnotationCellular compositionHuman tissuesType annotationsAnnotation toolAnnotation methodLabel transfer
2015
A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data
Lu Q, Hu Y, Sun J, Cheng Y, Cheung KH, Zhao H. A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data. Scientific Reports 2015, 5: 10576. PMID: 26015273, PMCID: PMC4444969, DOI: 10.1038/srep10576.Peer-Reviewed Original ResearchConceptsHuman genomeFunctional regionsStatistical frameworkAnnotation dataFunctional annotation dataWhole-genome annotationNon-coding regionsGenomic conservationHigh-throughput experimentsENCODE projectExperimental annotationsGenomeUnsupervised statistical learningFunctional potentialHuman geneticsStatistical learningComputational predictionsIntegrated analysisAnnotationAnnotation methodDiverse typesPowerful toolGeneticsMajor goalWeb server