Featured Publications
SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data
Liu Y, Li N, Qi J, Xu G, Zhao J, Wang N, Huang X, Jiang W, Wei H, Justet A, Adams T, Homer R, Amei A, Rosas I, Kaminski N, Wang Z, Yan X. SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data. Genome Biology 2024, 25: 271. PMID: 39402626, PMCID: PMC11475911, DOI: 10.1186/s13059-024-03416-2.Peer-Reviewed Original ResearchTesting gene set enrichment for subset of genes: Sub-GSE
Yan X, Sun F. Testing gene set enrichment for subset of genes: Sub-GSE. BMC Bioinformatics 2008, 9: 362. PMID: 18764941, PMCID: PMC2543030, DOI: 10.1186/1471-2105-9-362.Peer-Reviewed Original Research
2021
Openness weighted association studies: leveraging personal genome information to prioritize non-coding variants
Song S, Shan N, Wang G, Yan X, Liu JS, Hou L. Openness weighted association studies: leveraging personal genome information to prioritize non-coding variants. Bioinformatics 2021, 37: 4737-4743. PMID: 34260700, PMCID: PMC8665759, DOI: 10.1093/bioinformatics/btab514.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesFunctional annotationGWAS signalsAssociation studiesComplex diseasesSpecific functional annotationsTissue-specific patternsNon-coding variationsPotential functional differencesDisease-relevant pathwaysPersonal genome informationGenome informationGenomic regionsComprehensive annotationHuman genomeChromosome accessibilityGenomic segmentsMore heritabilityNoncoding variantsPersonal genomesRelevant pathwaysNovel insightsFunctional differencesGenomeDisease mechanisms
2006
MARD: a new method to detect differential gene expression in treatment-control time courses
Cheng C, Ma X, Yan X, Sun F, Li LM. MARD: a new method to detect differential gene expression in treatment-control time courses. Bioinformatics 2006, 22: 2650-2657. PMID: 16928738, DOI: 10.1093/bioinformatics/btl451.Peer-Reviewed Original Research