{"id":"https://openalex.org/W7197023754","doi":"https://doi.org/10.32614/rj-2026-011","title":"QTLEMM: An R Package for QTL Mapping and Hotspot Detection","display_name":"QTLEMM: An R Package for QTL Mapping and Hotspot Detection","publication_year":2026,"publication_date":"2026-04-27","ids":{"openalex":"https://openalex.org/W7197023754","doi":"https://doi.org/10.32614/rj-2026-011"},"language":"en","primary_location":{"id":"doi:10.32614/rj-2026-011","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2026-011","pdf_url":"https://journal.r-project.org/articles/RJ-2026-011/RJ-2026-011.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journal.r-project.org/articles/RJ-2026-011/RJ-2026-011.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072743024","display_name":"Ping-Yuan Chung","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141710","display_name":"Institute of Statistical Science, Academia Sinica","ror":"https://ror.org/044gv5910","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210141710","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ping-Yuan Chung","raw_affiliation_strings":["Institute of Statistical Science, Academia Sinica"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Statistical Science, Academia Sinica","institution_ids":["https://openalex.org/I4210141710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5145928455","display_name":"You-Tsz Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141710","display_name":"Institute of Statistical Science, Academia Sinica","ror":"https://ror.org/044gv5910","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210141710","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"You-Tsz Guo","raw_affiliation_strings":["Institute of Statistical Science, Academia Sinica"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Statistical Science, Academia Sinica","institution_ids":["https://openalex.org/I4210141710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026922048","display_name":"Hsiang-An Ho","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141710","display_name":"Institute of Statistical Science, Academia Sinica","ror":"https://ror.org/044gv5910","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210141710","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsiang-An Ho","raw_affiliation_strings":["Institute of Statistical Science, Academia Sinica"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Statistical Science, Academia Sinica","institution_ids":["https://openalex.org/I4210141710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011736621","display_name":"Hsin-I Lee","orcid":"https://orcid.org/0000-0002-5187-3085"},"institutions":[{"id":"https://openalex.org/I4210141710","display_name":"Institute of Statistical Science, Academia Sinica","ror":"https://ror.org/044gv5910","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210141710","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsin-I Lee","raw_affiliation_strings":["Institute of Statistical Science, Academia Sinica"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Statistical Science, Academia Sinica","institution_ids":["https://openalex.org/I4210141710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031458180","display_name":"Po\u2010Ya Wu","orcid":"https://orcid.org/0000-0002-7342-2867"},"institutions":[{"id":"https://openalex.org/I4210141710","display_name":"Institute of Statistical Science, Academia Sinica","ror":"https://ror.org/044gv5910","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210141710","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Po-Ya Wu","raw_affiliation_strings":["Institute of Statistical Science, Academia Sinica"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Statistical Science, Academia Sinica","institution_ids":["https://openalex.org/I4210141710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086173128","display_name":"Man-Hsia Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I26359584","display_name":"Council of Agriculture","ror":"https://ror.org/0358yps07","country_code":"TW","type":"government","lineage":["https://openalex.org/I26359584"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Man-Hsia Yang","raw_affiliation_strings":["Crop Science Division, Taiwan Agricultural Research Institute, Council\nof Agriculture"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Crop Science Division, Taiwan Agricultural Research Institute, Council\nof Agriculture","institution_ids":["https://openalex.org/I26359584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112035953","display_name":"MIAO-HUI ZENG","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141710","display_name":"Institute of Statistical Science, Academia Sinica","ror":"https://ror.org/044gv5910","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210141710","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Miao-Hui Zeng","raw_affiliation_strings":["Institute of Statistical Science, Academia Sinica"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Statistical Science, Academia Sinica","institution_ids":["https://openalex.org/I4210141710"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100825113","display_name":"Chen-Hung Kao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141710","display_name":"Institute of Statistical Science, Academia Sinica","ror":"https://ror.org/044gv5910","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210141710","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chen-Hung Kao","raw_affiliation_strings":["Institute of Statistical Science, Academia Sinica"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Statistical Science, Academia Sinica","institution_ids":["https://openalex.org/I4210141710"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.90172954,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"1","first_page":"39","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11468","display_name":"Genetic Mapping and Diversity in Plants and Animals","score":0.9927999973297119,"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"}},"topics":[{"id":"https://openalex.org/T11468","display_name":"Genetic Mapping and Diversity in Plants and Animals","score":0.9927999973297119,"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"}},{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.0003000000142492354,"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/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hotspot","display_name":"Hotspot (geology)","score":0.7627000212669373},{"id":"https://openalex.org/keywords/quantitative-trait-locus","display_name":"Quantitative trait locus","score":0.7317000031471252},{"id":"https://openalex.org/keywords/r-package","display_name":"R package","score":0.5480999946594238},{"id":"https://openalex.org/keywords/inclusive-composite-interval-mapping","display_name":"Inclusive composite interval mapping","score":0.5303000211715698},{"id":"https://openalex.org/keywords/genotyping","display_name":"Genotyping","score":0.4869999885559082},{"id":"https://openalex.org/keywords/family-based-qtl-mapping","display_name":"Family-based QTL mapping","score":0.40139999985694885},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.3808000087738037},{"id":"https://openalex.org/keywords/genomics","display_name":"Genomics","score":0.35740000009536743}],"concepts":[{"id":"https://openalex.org/C146481406","wikidata":"https://www.wikidata.org/wiki/Q105131","display_name":"Hotspot (geology)","level":2,"score":0.7627000212669373},{"id":"https://openalex.org/C81941488","wikidata":"https://www.wikidata.org/wiki/Q853421","display_name":"Quantitative trait locus","level":3,"score":0.7317000031471252},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6004999876022339},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.5480999946594238},{"id":"https://openalex.org/C121212380","wikidata":"https://www.wikidata.org/wiki/Q6014918","display_name":"Inclusive composite interval mapping","level":5,"score":0.5303000211715698},{"id":"https://openalex.org/C31467283","wikidata":"https://www.wikidata.org/wiki/Q912147","display_name":"Genotyping","level":4,"score":0.4869999885559082},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4293000102043152},{"id":"https://openalex.org/C21249469","wikidata":"https://www.wikidata.org/wiki/Q5433313","display_name":"Family-based QTL mapping","level":5,"score":0.40139999985694885},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3808000087738037},{"id":"https://openalex.org/C189206191","wikidata":"https://www.wikidata.org/wiki/Q222046","display_name":"Genomics","level":4,"score":0.35740000009536743},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.34040001034736633},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2928999960422516},{"id":"https://openalex.org/C134443026","wikidata":"https://www.wikidata.org/wiki/Q4809584","display_name":"Association mapping","level":5,"score":0.27639999985694885},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C193244246","wikidata":"https://www.wikidata.org/wiki/Q5432696","display_name":"False discovery rate","level":3,"score":0.260699987411499},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.25780001282691956},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.25760000944137573}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32614/rj-2026-011","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2026-011","pdf_url":"https://journal.r-project.org/articles/RJ-2026-011/RJ-2026-011.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32614/rj-2026-011","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2026-011","pdf_url":"https://journal.r-project.org/articles/RJ-2026-011/RJ-2026-011.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7197023754.pdf","grobid_xml":"https://content.openalex.org/works/W7197023754.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"an":[3],"R":[4],"package":[5],"QTLEMM":[6,25,69,94,131],"that":[7,99],"implements":[8],"commonly":[9],"used":[10],"and":[11,18,37,63,74,78,82,109,118,134,137],"popular":[12],"statistical":[13,97],"methods":[14,45,51],"for":[15,31],"QTL":[16,19,23,39,91],"mapping":[17],"hotspot":[20,92,116],"detection.":[21],"For":[22,90],"mapping,":[24],"offers":[26],"a":[27,126],"suite":[28],"of":[29,84,115,123,142,149],"functions":[30],"simulating":[32],"data,":[33,77,111],"computing":[34],"significance":[35],"thresholds,":[36,117],"estimating":[38],"parameters":[40],"using":[41],"single-QTL":[42],"or":[43],"multiple-QTL":[44],"in":[46,87,146,152],"diverse":[47],"experimental":[48],"populations.":[49],"These":[50],"encompass":[52],"linear":[53],"regression,":[54],"permutation":[55],"tests,":[56],"Gaussian":[57],"stochastic":[58],"process,":[59],"normal":[60,65],"mixture":[61,66],"models,":[62],"truncated":[64],"models.":[67],"Moreover,":[68],"accommodates":[70],"both":[71,102],"complete":[72],"genotyping":[73,76],"selective":[75],"enables":[79],"the":[80,88,96,103,113,140,147],"fitting":[81],"comparison":[83],"different":[85],"models":[86],"analysis.":[89],"detection,":[93],"devises":[95],"framework":[98],"can":[100,138],"handle":[101],"data":[104],"from":[105],"genetical":[106],"genomics":[107],"experiments":[108],"summarized":[110],"mitigate":[112],"underestimation":[114],"also":[119],"identify":[120],"various":[121],"types":[122],"hotspots":[124],"at":[125],"very":[127],"low":[128],"computational":[129],"cost.":[130],"provides":[132],"numerical":[133],"graphical":[135],"results,":[136],"facilitate":[139],"discovery":[141],"more":[143],"significant":[144],"results":[145],"analysis":[148],"quantitative":[150],"traits":[151],"biological":[153],"studies.":[154]},"counts_by_year":[],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2026-08-07T00:00:00"}
