{"id":"https://openalex.org/W2167784579","doi":"https://doi.org/10.1093/bioinformatics/btq650","title":"SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures","display_name":"SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures","publication_year":2010,"publication_date":"2010-11-18","ids":{"openalex":"https://openalex.org/W2167784579","doi":"https://doi.org/10.1093/bioinformatics/btq650","mag":"2167784579","pmid":"https://pubmed.ncbi.nlm.nih.gov/21098430"},"language":"en","primary_location":{"id":"doi:10.1093/bioinformatics/btq650","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btq650","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/27/2/225/48867102/bioinformatics_27_2_225.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://academic.oup.com/bioinformatics/article-pdf/27/2/225/48867102/bioinformatics_27_2_225.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079420932","display_name":"Hongqiang Wang","orcid":"https://orcid.org/0000-0002-6677-7010"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong-Qiang Wang","raw_affiliation_strings":["1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038459444","display_name":"Lindsey K Tuominen","orcid":"https://orcid.org/0000-0001-8387-0797"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lindsey K. Tuominen","raw_affiliation_strings":["1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011660598","display_name":"Chung\u2010Jui Tsai","orcid":"https://orcid.org/0000-0002-9282-7704"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chung-Jui Tsai","raw_affiliation_strings":["1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5011660598"],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":{"value":3618,"currency":"USD","value_usd":3618},"apc_paid":null,"fwci":1.4915,"has_fulltext":true,"cited_by_count":243,"citation_normalized_percentile":{"value":0.81915272,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"27","issue":"2","first_page":"225","last_page":"231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.3944999873638153,"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/T10885","display_name":"Gene expression and cancer classification","score":0.3944999873638153,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.18050000071525574,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10261","display_name":"Genetic Associations and Epidemiology","score":0.12189999967813492,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/estimator","display_name":"Estimator","score":0.7745022773742676},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5926221609115601},{"id":"https://openalex.org/keywords/null-hypothesis","display_name":"Null hypothesis","score":0.5328595638275146},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.5323235392570496},{"id":"https://openalex.org/keywords/false-discovery-rate","display_name":"False discovery rate","score":0.528924822807312},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4970598518848419},{"id":"https://openalex.org/keywords/r-package","display_name":"R package","score":0.4903995990753174},{"id":"https://openalex.org/keywords/null","display_name":"Null (SQL)","score":0.45772939920425415},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.448681503534317},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43565601110458374},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.43068182468414307},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3378782570362091},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3004622757434845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2835509777069092},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22138768434524536},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11835804581642151}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7745022773742676},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5926221609115601},{"id":"https://openalex.org/C191988596","wikidata":"https://www.wikidata.org/wiki/Q628374","display_name":"Null hypothesis","level":2,"score":0.5328595638275146},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.5323235392570496},{"id":"https://openalex.org/C193244246","wikidata":"https://www.wikidata.org/wiki/Q5432696","display_name":"False discovery rate","level":3,"score":0.528924822807312},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4970598518848419},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.4903995990753174},{"id":"https://openalex.org/C203763787","wikidata":"https://www.wikidata.org/wiki/Q371029","display_name":"Null (SQL)","level":2,"score":0.45772939920425415},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.448681503534317},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43565601110458374},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.43068182468414307},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3378782570362091},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3004622757434845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2835509777069092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22138768434524536},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11835804581642151},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020411","descriptor_name":"Oligonucleotide Array Sequence Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020411","descriptor_name":"Oligonucleotide Array Sequence Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020411","descriptor_name":"Oligonucleotide Array Sequence Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D032107","descriptor_name":"Populus","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D032107","descriptor_name":"Populus","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D032107","descriptor_name":"Populus","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D032107","descriptor_name":"Populus","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D032107","descriptor_name":"Populus","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D032107","descriptor_name":"Populus","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.1093/bioinformatics/btq650","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btq650","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/27/2/225/48867102/bioinformatics_27_2_225.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},{"id":"pmid:21098430","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/21098430","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics (Oxford, England)","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1003.5018","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1003.5018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://bioinformatics.oxfordjournals.org/content/early/2010/11/23/bioinformatics.btq650.full.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1004.925","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1004.925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://bioinformatics.oxfordjournals.org/content/early/2010/11/18/bioinformatics.btq650.full.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.991.4222","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.991.4222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://bioinformatics.oxfordjournals.org/content/27/2/225.full.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1093/bioinformatics/btq650","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btq650","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/27/2/225/48867102/bioinformatics_27_2_225.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1196936200","display_name":"A Functional Genomics Approach to Investigate Regulation of Phenolic Glycoside Metabolism in Populus","funder_award_id":"0836433","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2167784579.pdf","grobid_xml":"https://content.openalex.org/works/W2167784579.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1964895626","https://openalex.org/W1976741643","https://openalex.org/W1981434053","https://openalex.org/W1988414849","https://openalex.org/W2006145698","https://openalex.org/W2006780198","https://openalex.org/W2009660843","https://openalex.org/W2073158462","https://openalex.org/W2081098333","https://openalex.org/W2105381419","https://openalex.org/W2110065044","https://openalex.org/W2115503758","https://openalex.org/W2140954822","https://openalex.org/W2149187761","https://openalex.org/W2595709335","https://openalex.org/W3099326140","https://openalex.org/W3103154150","https://openalex.org/W4235432393"],"related_works":["https://openalex.org/W2189374991","https://openalex.org/W2903799831","https://openalex.org/W2348480869","https://openalex.org/W2046875666","https://openalex.org/W2171537806","https://openalex.org/W1995992573","https://openalex.org/W200550325","https://openalex.org/W2485444738","https://openalex.org/W2979681497","https://openalex.org/W2585981346"],"abstract_inverted_index":{"MOTIVATION:":[0],"The":[1,135,157],"pre-estimate":[2],"of":[3,6,29,36,50,112,137,153,160],"the":[4,34,46,51,161],"proportion":[5],"null":[7],"hypotheses":[8],"(\u03c0(0))":[9],"plays":[10],"a":[11,56,67,95,110,148],"critical":[12],"role":[13],"in":[14,20,130],"controlling":[15],"false":[16],"discovery":[17],"rate":[18],"(FDR)":[19],"multiple":[21],"hypothesis":[22],"testing.":[23],"However,":[24],"hidden":[25],"complex":[26],"dependence":[27,63,118],"structures":[28,119],"many":[30],"genomics":[31],"datasets":[32,114],"distort":[33],"distribution":[35],"p-values,":[37],"rendering":[38],"existing":[39],"\u03c0(0)":[40,104,132,139],"estimators":[41],"less":[42],"effective.":[43],"RESULTS:":[44],"From":[45],"basic":[47],"non-linear":[48],"model":[49],"q-value":[52],"method,":[53],"we":[54],"developed":[55],"simple":[57],"linear":[58],"algorithm":[59],"to":[60,93,100,127],"probe":[61],"local":[62],"blocks.":[64],"We":[65],"uncovered":[66],"non-static":[68],"relationship":[69],"between":[70],"tests'":[71],"p-values":[72],"and":[73,83,120],"their":[74],"corresponding":[75],"q-values":[76],"that":[77,142],"is":[78,164],"influenced":[79],"by":[80],"data":[81,117],"structure":[82],"\u03c0(0).":[84],"Using":[85],"an":[86],"optimization":[87],"framework,":[88],"these":[89],"findings":[90],"were":[91],"exploited":[92],"devise":[94],"Sliding":[96],"Linear":[97],"Model":[98],"(SLIM)":[99],"more":[101],"reliably":[102],"estimate":[103],"under":[105],"dependence.":[106,134],"When":[107],"tested":[108],"on":[109,121],"number":[111],"simulation":[113],"with":[115],"varying":[116],"microarray":[122],"data,":[123],"SLIM":[124,143],"was":[125],"found":[126],"be":[128,145],"robust":[129],"estimating":[131],"against":[133],"accuracy":[136],"its":[138],"estimation":[140],"suggests":[141],"can":[144],"used":[146],"as":[147],"stand-alone":[149],"tool":[150],"for":[151,168],"prediction":[152],"significant":[154],"tests.":[155],"AVAILABILITY:":[156],"R":[158],"code":[159],"proposed":[162],"method":[163],"available":[165],"at":[166],"http://aspendb.uga.edu/downloads":[167],"academic":[169],"use.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":33},{"year":2022,"cited_by_count":32},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":32},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":13},{"year":2016,"cited_by_count":11},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":5}],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}