Heng Li studies advanced computational algorithms to solve practical biological problems, currently with a focus on sequence alignment, variant calling, de novo assembly, data storage, and information query. He developed and maintains several widely used software packages, such as BWA, samtools, minimap2, and seqtk, for analyzing high-throughput sequencing data. He has also collaborated with multiple research groups and published work on the analysis of single-cell sequence data, chromosome conformation, cancer genomics, population genetics and species evolution.
DBMI Research Areas
A high-coverage genome sequence from an archaic Denisovan individual.
Authors: Meyer M, Kircher M, Gansauge MT, Li H, Racimo F, Mallick S, Schraiber JG, Jay F, Prüfer K, de Filippo C, Sudmant PH, Alkan C, Fu Q, Do R, Rohland N, Tandon A, Siebauer M, Green RE, Bryc K, Briggs AW, Stenzel U, Dabney J, Shendure J, Kitzman J, Hammer MF, Shunkov MV, Derevianko AP, Patterson N, Andrés AM, Eichler EE, Slatkin M, Reich D, Kelso J, Pääbo S.
Science
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Science
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A direct characterization of human mutation based on microsatellites.
Authors: Sun JX, Helgason A, Masson G, Ebenesersdóttir SS, Li H, Mallick S, Gnerre S, Patterson N, Kong A, Reich D, Stefansson K.
Nat Genet
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Nat Genet
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Exploring single-sample SNP and INDEL calling with whole-genome de novo assembly.
pIRS: Profile-based Illumina pair-end reads simulator.
Authors: Hu X, Yuan J, Shi Y, Lu J, Liu B, Li Z, Chen Y, Mu D, Zhang H, Li N, Yue Z, Bai F, Li H, Fan W.
Bioinformatics
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Bioinformatics
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Extremely low-coverage sequencing and imputation increases power for genome-wide association studies.
Authors: Pasaniuc B, Rohland N, McLaren PJ, Garimella K, Zaitlen N, Li H, Gupta N, Neale BM, Daly MJ, Sklar P, Sullivan PF, Bergen S, Moran JL, Hultman CM, Lichtenstein P, Magnusson P, Purcell SM, Haas DW, Liang L, Sunyaev S, Patterson N, de Bakker PI, Reich D, Price AL.
Nat Genet
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Nat Genet
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The date of interbreeding between Neandertals and modern humans.
Authors: Sankararaman S, Patterson N, Li H, Pääbo S, Reich D.
PLoS Genet
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PLoS Genet
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A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.
Inference of human population history from individual whole-genome sequences.
Improving SNP discovery by base alignment quality.
Tabix: fast retrieval of sequence features from generic TAB-delimited files.