{"id":"https://openalex.org/W3105283194","doi":"https://doi.org/10.1145/3388440.3414214","title":"Processing Millions of Single Cells by SHARP","display_name":"Processing Millions of Single Cells by SHARP","publication_year":2020,"publication_date":"2020-09-21","ids":{"openalex":"https://openalex.org/W3105283194","doi":"https://doi.org/10.1145/3388440.3414214","mag":"3105283194"},"language":"en","primary_location":{"id":"doi:10.1145/3388440.3414214","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388440.3414214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065053020","display_name":"Shibiao Wan","orcid":"https://orcid.org/0000-0003-0661-2684"},"institutions":[{"id":"https://openalex.org/I1313298211","display_name":"St. Jude Children's Research Hospital","ror":"https://ror.org/02r3e0967","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1313298211","https://openalex.org/I2802152183"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shibiao Wan","raw_affiliation_strings":["Center for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, TN, USA"],"affiliations":[{"raw_affiliation_string":"Center for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, TN, USA","institution_ids":["https://openalex.org/I1313298211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026578909","display_name":"Junil Kim","orcid":"https://orcid.org/0000-0002-1202-1808"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Junil Kim","raw_affiliation_strings":["Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012093142","display_name":"Yiping Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I1313298211","display_name":"St. Jude Children's Research Hospital","ror":"https://ror.org/02r3e0967","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1313298211","https://openalex.org/I2802152183"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiping Fan","raw_affiliation_strings":["Center for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, TN, USA"],"affiliations":[{"raw_affiliation_string":"Center for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, TN, USA","institution_ids":["https://openalex.org/I1313298211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060918471","display_name":"Kyoung\u2010Jae Won","orcid":"https://orcid.org/0000-0002-2924-9630"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Kyoung Jae Won","raw_affiliation_strings":["Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065053020"],"corresponding_institution_ids":["https://openalex.org/I1313298211"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11054851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.948199987411499,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10773","display_name":"Extracellular vesicles in disease","score":0.9200000166893005,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.8188323378562927},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8177567720413208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.681499719619751},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5854900479316711},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5455548167228699},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5433323383331299},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.48346027731895447},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.47118499875068665},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38819393515586853},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3523014485836029},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3091587424278259}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8188323378562927},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8177567720413208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.681499719619751},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5854900479316711},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5455548167228699},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5433323383331299},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.48346027731895447},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.47118499875068665},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38819393515586853},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3523014485836029},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3091587424278259},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3388440.3414214","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388440.3414214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G3589578894","display_name":null,"funder_award_id":"NNF17CC0027852","funder_id":"https://openalex.org/F4320325957","funder_display_name":"Novo Nordisk Fonden"},{"id":"https://openalex.org/G4889371882","display_name":null,"funder_award_id":"P30 CA021765","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G5616060558","display_name":null,"funder_award_id":"R313-2019-421","funder_id":"https://openalex.org/F4320321999","funder_display_name":"Lundbeckfonden"}],"funders":[{"id":"https://openalex.org/F4320321999","display_name":"Lundbeckfonden","ror":"https://ror.org/03hz8wd80"},{"id":"https://openalex.org/F4320325957","display_name":"Novo Nordisk Fonden","ror":"https://ror.org/04txyc737"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W3003444384"],"related_works":["https://openalex.org/W2515532094","https://openalex.org/W2790862734","https://openalex.org/W345943785","https://openalex.org/W2141406155","https://openalex.org/W3015962327","https://openalex.org/W2611813480","https://openalex.org/W2624745934","https://openalex.org/W2807562011","https://openalex.org/W3148922054","https://openalex.org/W2119226345"],"abstract_inverted_index":{"Single-cell":[0],"technologies":[1,38],"have":[2,39],"received":[3],"extensive":[4],"attention":[5],"from":[6,242],"bioinformatics":[7],"and":[8,22,30,58,96,128,153,206,223,237,246],"computational":[9],"biology":[10,29],"communities":[11],"due":[12],"to":[13,60,82,111,131,170,184,228],"their":[14],"evolutionary":[15],"impacts":[16],"on":[17,34,139],"uncovering":[18],"novel":[19],"cell":[20,234,240],"types":[21],"intra-population":[23],"heterogeneity":[24],"in":[25,116,133,149,181,187],"various":[26],"domains":[27],"of":[28,44,46,55,118,151,158,178,203,225],"medicine.":[31],"Recent":[32],"advances":[33],"single-cell":[35,211],"RNA-sequencing":[36],"(scRNA-seq)":[37],"enabled":[40],"parallel":[41],"transcriptomic":[42],"profiling":[43],"millions":[45],"cells.":[47,86,174],"However,":[48],"existing":[49,107],"scRNA-seq":[50,134,141],"clustering":[51,83,119,171],"methods":[52,148],"are":[53],"lack":[54],"scalability,":[56],"time-consuming":[57],"prone":[59],"information":[61],"loss":[62],"during":[63,125],"dimension":[64,126],"reduction.":[65],"To":[66,155],"address":[67],"these":[68],"concerns,":[69],"we":[70,196],"present":[71],"SHARP":[72,99,144,161,198],"[1],":[73],"an":[74,176],"ensemble":[75],"random":[76,94],"projection-based":[77],"algorithm":[78],"which":[79],"is":[80,162,168],"scalable":[81,110,169],"10":[84,172],"million":[85,173],"By":[87],"adopting":[88],"a":[89,92],"divide-and-conquer":[90],"strategy,":[91],"sparse":[93],"projection":[95],"two-layer":[97],"meta-clustering,":[98],"has":[100],"the":[101,156,163,204,221],"following":[102],"advantages:":[103],"(1)":[104],"hyper-faster":[105],"than":[106],"algorithms;":[108],"(2)":[109],"10-million":[112],"cells;":[113],"(3)":[114],"accurate":[115],"terms":[117,150],"performance;":[120],"(4)":[121],"preserving":[122],"cell-to-cell":[123],"distance":[124],"reduction;":[127],"(5)":[129],"robust":[130],"dropouts":[132],"data.":[135],"Comprehensive":[136],"benchmarking":[137],"tests":[138],"20":[140],"datasets":[142],"demonstrate":[143],"remarkably":[145],"outperforms":[146],"state-of-the-art":[147],"speed":[152,224],"accuracy.":[154],"best":[157],"our":[159],"knowledge,":[160],"only":[164],"R-based":[165],"tool":[166],"that":[167],"With":[175],"avalanche":[177],"single":[179,239],"cells":[180],"different":[182,243],"tissues":[183],"be":[185],"sequenced":[186],"multiple":[188],"international":[189],"projects":[190],"like":[191],"The":[192],"Human":[193],"Cell":[194],"Atlas,":[195],"believe":[197],"will":[199],"serve":[200],"as":[201],"one":[202],"useful":[205],"important":[207],"tools":[208],"for":[209],"large-scale":[210],"data":[212,241],"analysis.":[213],"Several":[214],"potential":[215],"future":[216],"directions":[217],"include":[218],"while":[219],"keeping":[220],"scalability":[222],"SHARP,":[226],"how":[227],"extend":[229],"its":[230],"functions":[231],"into":[232],"rare":[233],"type":[235],"detection":[236],"integrating":[238],"platforms,":[244],"experiments":[245],"conditions.":[247]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
