Manhattan Harvester and Cropper: a system for GWAS peak detection
Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond...
Uložené v:
| Vydané v: | BMC bioinformatics Ročník 20; číslo 1; s. 22 - 8 |
|---|---|
| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
London
BioMed Central
11.01.2019
BioMed Central Ltd Springer Nature B.V BMC |
| Predmet: | |
| ISSN: | 1471-2105, 1471-2105 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | Background
Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study.
Results
We developed Manhattan Harvester, a tool designed for “peak extraction” from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester.
Conclusions
We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. |
|---|---|
| AbstractList | Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. We developed Manhattan Harvester, a tool designed for "peak extraction" from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. We developed Manhattan Harvester, a tool designed for "peak extraction" from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. Abstract Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. Results We developed Manhattan Harvester, a tool designed for “peak extraction” from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. Conclusions We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study.BACKGROUNDSelection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study.We developed Manhattan Harvester, a tool designed for "peak extraction" from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester.RESULTSWe developed Manhattan Harvester, a tool designed for "peak extraction" from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester.We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available.CONCLUSIONSWe conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. Results We developed Manhattan Harvester, a tool designed for “peak extraction” from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. Conclusions We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. Results We developed Manhattan Harvester, a tool designed for “peak extraction” from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. Conclusions We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. Results We developed Manhattan Harvester, a tool designed for "peak extraction" from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. Conclusions We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. Keywords: GWAS, Manhattan plots, Peak detection, Peak quality score, Software |
| ArticleNumber | 22 |
| Audience | Academic |
| Author | Tasa, Tõnis Haller, Toomas Metspalu, Andres |
| Author_xml | – sequence: 1 givenname: Toomas orcidid: 0000-0002-5069-6523 surname: Haller fullname: Haller, Toomas email: Toomas.Haller@ut.ee organization: Estonian Genome Center, Institute of Genomics, University of Tartu – sequence: 2 givenname: Tõnis surname: Tasa fullname: Tasa, Tõnis organization: Institute of Computer Science, University of Tartu – sequence: 3 givenname: Andres surname: Metspalu fullname: Metspalu, Andres organization: Estonian Genome Center, Institute of Genomics, University of Tartu |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30634901$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9kl9v0zAUxSM0xP7AB-AFReIFHjLutR3H4QGpqthWaQiJgXi03MTuXFK72O7Evv0cOrZ1AuSHWCe_c2xfncNiz3mni-IlwjGi4O8iElG3FWBbEQ5QsSfFAbIGK4JQ7z3Y7xeHMS4BsBFQPyv2KXDKWsCDYvJJuUuVknLlmQpXOiYdSuX6chr8eq3D-1KV8Tqrq9L4UJ5-n1yUa61-lL1OukvWu-fFU6OGqF_cfo-Kbycfv07PqvPPp7Pp5LzqOG1SRQRomOcL9TwLirQUDOu5wJZQPgdjgAlAaFpTc02RGKHNCCGylmJn6FEx2-b2Xi3lOtiVCtfSKyt_Cz4spArJdoOWFJjBnjAAUjNiWsEwK4wR3hA0Ysz6sM1ab-Yr3XfapaCGndDdP85eyoW_kpxSoC3NAW9uA4L_uclTkysbOz0Mymm_iZJg01JWAxvR14_Qpd8El0eVKS5YTbCGe2qh8gOsMz6f242hclILZMAY1pk6_guVV69XtsvlMDbrO4a3O4bMJP0rLdQmRjm7-LLLvno4lLtp_ClLBnALdMHHGLS5QxDkWEi5LaTMhZRjISXLnuaRp7NJjb3JN7fDf51k64z5FLfQ4X5u_zbdAHwh7QM |
| CitedBy_id | crossref_primary_10_1038_s41467_025_58465_3 crossref_primary_10_1038_s41588_024_01964_8 crossref_primary_10_1534_g3_119_400452 crossref_primary_10_3390_pathogens10121604 crossref_primary_10_1186_s13059_022_02742_7 crossref_primary_10_1016_j_indcrop_2025_120873 |
| Cites_doi | 10.1371/journal.pbio.2005485 10.1038/nn.4404 10.1016/j.ajhg.2017.06.005 10.1038/ncomms11122 10.1007/s10742-016-0145-9 10.1093/bib/bbt066 10.1186/1471-2105-11-288 |
| ContentType | Journal Article |
| Copyright | The Author(s). 2019 COPYRIGHT 2019 BioMed Central Ltd. Copyright © 2019. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: The Author(s). 2019 – notice: COPYRIGHT 2019 BioMed Central Ltd. – notice: Copyright © 2019. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | C6C AAYXX CITATION NPM ISR 3V. 7QO 7SC 7X7 7XB 88E 8AL 8AO 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABUWG AEUYN AFKRA ARAPS AZQEC BBNVY BENPR BGLVJ BHPHI CCPQU DWQXO FR3 FYUFA GHDGH GNUQQ HCIFZ JQ2 K7- K9. L7M LK8 L~C L~D M0N M0S M1P M7P P5Z P62 P64 PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS Q9U 7X8 5PM DOA |
| DOI | 10.1186/s12859-019-2600-4 |
| DatabaseName | Springer Nature OA Free Journals CrossRef PubMed Gale In Context: Science ProQuest Central (Corporate) Biotechnology Research Abstracts Computer and Information Systems Abstracts Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Computing Database (Alumni Edition) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest One Sustainability (subscription) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials Biological Science Collection (subscription) ProQuest Central Technology collection Natural Science Collection ProQuest One Community College ProQuest Central Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database ProQuest Health & Medical Complete (Alumni) Advanced Technologies Database with Aerospace Biological Sciences Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Computing Database Health & Medical Collection (Alumni Edition) Medical Database Biological Science Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Open Access Full Text |
| DatabaseTitle | CrossRef PubMed Publicly Available Content Database Computer Science Database ProQuest Central Student ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts SciTech Premium Collection ProQuest Central China ProQuest One Applied & Life Sciences ProQuest One Sustainability Health Research Premium Collection Natural Science Collection Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Advanced Technologies & Aerospace Collection ProQuest Biological Science Collection ProQuest One Academic Eastern Edition ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts ProQuest Health & Medical Complete ProQuest One Academic UKI Edition Engineering Research Database ProQuest One Academic ProQuest One Academic (New) Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central ProQuest Health & Medical Research Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Advanced Technologies Database with Aerospace ProQuest Computing ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest SciTech Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest Medical Library ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | PubMed MEDLINE - Academic Publicly Available Content Database |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: PIMPY name: ProQuest Publicly Available Content url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Biology |
| EISSN | 1471-2105 |
| EndPage | 8 |
| ExternalDocumentID | oai_doaj_org_article_304f1d24002542f984104f4426721f8f PMC6330393 A581404415 30634901 10_1186_s12859_019_2600_4 |
| Genre | Journal Article |
| GeographicLocations | Estonia |
| GeographicLocations_xml | – name: Estonia |
| GrantInformation_xml | – fundername: US National Institute of Health grantid: R01DK075787 – fundername: EU H2020 grant grantid: 633589 – fundername: EU H2020 grant ePerMed grantid: 692145 – fundername: Estonian Government grantid: IUT20-60 – fundername: Estonian Center of Genomics/Roadmap II grantid: 2014-2020.4.01.16-0125 – fundername: European Regional Development Fund grantid: 2014-2020.4.01.15-0012 – fundername: ; grantid: IUT20-60 – fundername: ; grantid: 692145 – fundername: ; grantid: 2014-2020.4.01.15-0012 – fundername: ; grantid: 633589 – fundername: ; grantid: 2014-2020.4.01.16-0125 – fundername: ; grantid: R01DK075787 |
| GroupedDBID | --- 0R~ 23N 2WC 53G 5VS 6J9 7X7 88E 8AO 8FE 8FG 8FH 8FI 8FJ AAFWJ AAJSJ AAKPC AASML ABDBF ABUWG ACGFO ACGFS ACIHN ACIWK ACPRK ACUHS ADBBV ADMLS ADUKV AEAQA AENEX AEUYN AFKRA AFPKN AFRAH AHBYD AHMBA AHYZX ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS ARAPS AZQEC BAPOH BAWUL BBNVY BCNDV BENPR BFQNJ BGLVJ BHPHI BMC BPHCQ BVXVI C6C CCPQU CS3 DIK DU5 DWQXO E3Z EAD EAP EAS EBD EBLON EBS EJD EMB EMK EMOBN ESX F5P FYUFA GNUQQ GROUPED_DOAJ GX1 HCIFZ HMCUK HYE IAO ICD IHR INH INR ISR ITC K6V K7- KQ8 LK8 M1P M48 M7P MK~ ML0 M~E O5R O5S OK1 OVT P2P P62 PGMZT PHGZM PHGZT PIMPY PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO PUEGO RBZ RNS ROL RPM RSV SBL SOJ SV3 TR2 TUS UKHRP W2D WOQ WOW XH6 XSB AAYXX AFFHD CITATION ALIPV NPM 3V. 7QO 7SC 7XB 8AL 8FD 8FK FR3 JQ2 K9. L7M L~C L~D M0N P64 PKEHL PQEST PQUKI PRINS Q9U 7X8 5PM |
| ID | FETCH-LOGICAL-c637t-280e0b471d6c63a2930f4d6819236b0ff04801079f56e312f8ef2930114931cf3 |
| IEDL.DBID | DOA |
| ISICitedReferencesCount | 7 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000455456600003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1471-2105 |
| IngestDate | Fri Oct 03 12:50:53 EDT 2025 Tue Nov 04 01:57:50 EST 2025 Sun Nov 09 10:07:51 EST 2025 Mon Oct 06 18:39:29 EDT 2025 Tue Nov 11 10:57:49 EST 2025 Tue Nov 04 18:15:29 EST 2025 Thu Nov 13 16:37:25 EST 2025 Thu Apr 03 07:12:13 EDT 2025 Sat Nov 29 05:40:03 EST 2025 Tue Nov 18 21:15:46 EST 2025 Sat Sep 06 07:27:26 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | Peak detection Software GWAS Peak quality score Manhattan plots |
| Language | English |
| License | Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c637t-280e0b471d6c63a2930f4d6819236b0ff04801079f56e312f8ef2930114931cf3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ORCID | 0000-0002-5069-6523 |
| OpenAccessLink | https://doaj.org/article/304f1d24002542f984104f4426721f8f |
| PMID | 30634901 |
| PQID | 2168452150 |
| PQPubID | 44065 |
| PageCount | 8 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_304f1d24002542f984104f4426721f8f pubmedcentral_primary_oai_pubmedcentral_nih_gov_6330393 proquest_miscellaneous_2179345043 proquest_journals_2168452150 gale_infotracmisc_A581404415 gale_infotracacademiconefile_A581404415 gale_incontextgauss_ISR_A581404415 pubmed_primary_30634901 crossref_primary_10_1186_s12859_019_2600_4 crossref_citationtrail_10_1186_s12859_019_2600_4 springer_journals_10_1186_s12859_019_2600_4 |
| PublicationCentury | 2000 |
| PublicationDate | 2019-01-11 |
| PublicationDateYYYYMMDD | 2019-01-11 |
| PublicationDate_xml | – month: 01 year: 2019 text: 2019-01-11 day: 11 |
| PublicationDecade | 2010 |
| PublicationPlace | London |
| PublicationPlace_xml | – name: London – name: England |
| PublicationTitle | BMC bioinformatics |
| PublicationTitleAbbrev | BMC Bioinformatics |
| PublicationTitleAlternate | BMC Bioinformatics |
| PublicationYear | 2019 |
| Publisher | BioMed Central BioMed Central Ltd Springer Nature B.V BMC |
| Publisher_xml | – name: BioMed Central – name: BioMed Central Ltd – name: Springer Nature B.V – name: BMC |
| References | 2600_CR12 D Hedeker (2600_CR11) 2016; 16 2600_CR6 PM Visscher (2600_CR2) 2017; 101 A Ganna (2600_CR3) 2016; 19 2600_CR7 R Mägi (2600_CR10) 2010; 11 G Gibson (2600_CR1) 2018; 16 2600_CR9 J Kettunen (2600_CR8) 2016; 7 2600_CR4 T Haller (2600_CR5) 2015; 16 |
| References_xml | – volume: 16 start-page: e2005485 issue: 3 year: 2018 ident: 2600_CR1 publication-title: PLoS Biol doi: 10.1371/journal.pbio.2005485 – ident: 2600_CR6 – volume: 19 start-page: 1563 issue: 12 year: 2016 ident: 2600_CR3 publication-title: Nat Neurosci doi: 10.1038/nn.4404 – volume: 101 start-page: 5 issue: 1 year: 2017 ident: 2600_CR2 publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2017.06.005 – ident: 2600_CR7 – ident: 2600_CR4 – volume: 7 start-page: 11122 year: 2016 ident: 2600_CR8 publication-title: Nat Commun doi: 10.1038/ncomms11122 – volume: 16 start-page: 117 issue: 3 year: 2016 ident: 2600_CR11 publication-title: Health Serv Outcomes Res Methodol doi: 10.1007/s10742-016-0145-9 – volume: 16 start-page: 39 issue: 1 year: 2015 ident: 2600_CR5 publication-title: Brief Bioinform doi: 10.1093/bib/bbt066 – volume: 11 start-page: 288 year: 2010 ident: 2600_CR10 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-11-288 – ident: 2600_CR9 – ident: 2600_CR12 |
| SSID | ssj0017805 |
| Score | 2.3142354 |
| Snippet | Background
Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no... Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer... Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no... Abstract Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This... |
| SourceID | doaj pubmedcentral proquest gale pubmed crossref springer |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 22 |
| SubjectTerms | Algorithms Bioinformatics Biomedical and Life Sciences Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computer programs Genome-wide association studies Genomes GWAS Harvesters Harvesting Inspection Life Sciences Manhattan plots Microarrays Parameters Peak detection Peak quality score Phenotypes Regression analysis Researchers Results and data Science Software Technology application |
| SummonAdditionalLinks | – databaseName: Computer Science Database dbid: K7- link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3da9UwFA86FXzxW1edEkUQlLCkyU1TX-Q6nIo4xCnuLbRpsg1He73tFfzvPafN7ezEvfjSh-QUmuSX85Gc_g4hT_PSKaczyTSvcqY096zUOTxkJbNZ6aRRQ7GJbG_PHBzkn-KBWxvTKtc6sVfUVePwjHw7FdoosDUz_mrxg2HVKLxdjSU0LpJLIk0F4vxDxsZbBOTrjzeZwujtViBbGwTPOUNadqYmtqin7P9bMf9hmc5mTZ65Ou0t0u71_x3LDXIt-qJ0PoDnJrng61vkylCd8tdtMv9Y1EdFB94jxQpCPaUCLeqK7iybxcIvX9KCDkTQFDxf-vbbfJ8ufPGdVr7rE7zqO-Tr7psvO-9YrLjAnJZZx1LDPS_BXlUaGgpwBXhQlUbSNKlLHkLPNsOzPMy0lyINxgcUgqAql8IFeZds1E3tNwktdQmRoMmMLMELyEQpncpNxVPvg5alTwhfz711kY4cq2Kc2D4sMdoOy2VhuSwul1UJeT6-shi4OM4Tfo0LOgoijXbf0CwPbdyVVnIVRIVptBAnpyEHYEKLAq8FAuNgQkKeIBwsEmXUmIlzWKza1r7f_2znM-QKw2g0Ic-iUGhgBK6IPzbAPCC31kRyayIJO9lNu9dwsVGTtPYUKwl5PHbjm5gdV_tmhTKgZRVy0SXk3gDScdwQEkoFTl9Csgl8JxMz7amPj3qecS0l_rmdkBdroJ9-1j_n_f75g3hArqa4AblgQmyRjW658g_JZfezO26Xj_rt-xu26UYI priority: 102 providerName: ProQuest – databaseName: SpringerLINK Contemporary 1997-Present dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Zb9QwEB5BAYkX7iNQkEFISKAIJ_Y6Dm9LRYEHKtTl6JuVw26rVskqySLx75lxDkg5JHjZB3ssrSdzasbfADxJ80IWKhGh4mUaSsVtmKsUf0QpkkVeCC37YRPJ3p4-OEg_DO-427HbfSxJekvt1VqrF21EWGuY-qYhgaqH8jxcQG-nSRv3V5-n0gGB9A_ly98emzkgj9P_qzX-yR2dbZU8Uy_1bmj36n9d4BpcGaJOtuzF5Dqcs9UNuNTPofx2E5bvs-oo6zBOZDQryIMnsKwq2U5Tr9e2ecky1kM-M4xx2ZsvyxVb2-yElbbzrVzVLfi0-_rjzttwmK0QFkokXRhrbnmOnqlUuJCh0-dOlorg0YTKuXMeV4YnqVsoK6LYaeuICNOnVESFE7dhq6orexdYrnLM-XSiRY7-PolyUchUlzy21imR2wD4yHBTDMDjNP_i1PgERCvTc8YgZwxxxsgAnk1H1j3qxt-IX9FXnAgJMNsv1M2hGfTPCC5dVFLDLGbEsUtRBHFFYnyCKbDTLoDHJAOGIDEq6rk5zDZta96t9s1yQahglHcG8HQgcjXeoMiGJwzIB0LRmlFuzyhRZ4v59ihqZrAZrYkjpSVGUwsewKNpm05SH1xl6w3RoD2VhDoXwJ1eMqd7Y_InJIZ3ASQzmZ0xZr5THR95RHElBL3RDuD5KLk__tYf-X7vn6jvw-WYRJ9HYRRtw1bXbOwDuFh87Y7b5qFX4e8GKzv2 priority: 102 providerName: Springer Nature |
| Title | Manhattan Harvester and Cropper: a system for GWAS peak detection |
| URI | https://link.springer.com/article/10.1186/s12859-019-2600-4 https://www.ncbi.nlm.nih.gov/pubmed/30634901 https://www.proquest.com/docview/2168452150 https://www.proquest.com/docview/2179345043 https://pubmed.ncbi.nlm.nih.gov/PMC6330393 https://doaj.org/article/304f1d24002542f984104f4426721f8f |
| Volume | 20 |
| WOSCitedRecordID | wos000455456600003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVADU databaseName: Open Access: BioMedCentral Open Access Titles customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: RBZ dateStart: 20000101 isFulltext: true titleUrlDefault: https://www.biomedcentral.com/search/ providerName: BioMedCentral – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: DOA dateStart: 20000101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: M~E dateStart: 20000101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: P5Z dateStart: 20090101 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Biological Science Database customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: M7P dateStart: 20090101 isFulltext: true titleUrlDefault: http://search.proquest.com/biologicalscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Computer Science Database customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: K7- dateStart: 20090101 isFulltext: true titleUrlDefault: http://search.proquest.com/compscijour providerName: ProQuest – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: 7X7 dateStart: 20090101 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: BENPR dateStart: 20090101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Publicly Available Content customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: PIMPY dateStart: 20090101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK customDbUrl: eissn: 1471-2105 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017805 issn: 1471-2105 databaseCode: RSV dateStart: 20001201 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3di9QwEB_0VPBF_LZ6LlEEQSmXNtkk9W3vuNNDbim7fqy-hH4k3qF0l-2u4H_vTNtdryfqiy-BJhNoppPM_Mj0NwDPkryQhdIiVLxMQqm4C3OVYCNKoYd5IYxsi03o8djMZkl6rtQX5YS19MCt4vYQbvuopExHhDKxT3Au9kh0LIhdvPF0-mLUswFT3f0BMfV3d5iRUXt1RDxtCJuTkAjZQ9nzQg1Z_-9H8jmfdDFf8sKlaeOLjm7CjS6IZKP25W_BJVfdhmttWckfd2B0klWn2QrDPkalfxouBJZVJTtYzhcLt3zFMtYyODMMWdnrj6MpW7jsKyvdqsnMqu7C-6PDdwdvwq5UQlgooVdhbLjjOTqaUmFHhj6ce1kqYjsTKufeNzQxXCd-qJyIYm-cJyFEQ4mICi_uwU41r9wDYLnKEcIZbUSO7ltHuShkYkoeO-eVyF0AfKM6W3Q84lTO4ptt8IRRttW2RW1b0raVAbzYTlm0JBp_E96n77EVJP7rpgOtwnZWYf9lFQE8pa9pieGiohSaL9m6ru3xdGJHQyL5IhgZwPNOyM9xBUXW_ZGAeiBSrJ7kbk8St2DRH94Yje2OgNrGkTISg6MhD-DJdphmUlpb5eZrksHjURKJXAD3WxvbrhuxnJAYrQWge9bXU0x_pDo7bQjClRD0y3UALzd2-uu1_qj3h_9D74_geky7jEdhFO3Czmq5do_havF9dVYvB3BZz3TTmgFc2T8cp5NBs2-xfavDASXeptimw884nh6fpJ_waTL98BNg9D8W |
| linkProvider | Directory of Open Access Journals |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VAoIL70eggEEgJFBUJ_Y6DhJCS6F0te0KtUX0ZvKw2wqUXTa7oP4pfiMzeWxJEb31wCUHexzF9jzj8TcAT-M0k5mKhK94HvtSceunKsaHyEXUSzOhZV1sIhqN9N5e_HEJfrV3YSitstWJlaLOxxn9I18NA6Ul2poefzP57lPVKDpdbUto1GwxtEc_MWQrXw_e4f4-C8P197trG35TVcDPlIhmfqi55Snq5FxhQ4LmjjuZKwIGEyrlzlWIKjyKXU9ZEYROW0dEGDjEIsicwPeeg_NS6Iiw-oeRvzi1oPoAzclpoNVqGRA6HAbrsU8w8L7s2L6qRMDfhuAPS3gyS_PEUW1lAdev_m9rdw2uNL4269fCcR2WbHEDLtbVN49uQn8rKQ6SGXrHjCokVZARLClytjYdTyZ2-oolrAa6ZujZsw-f-ztsYpOvLLezKoGtuAWfzuT7b8NyMS7sXWCpSjHS1ZEWKXo5UZCKTMY656G1TonUesDbvTZZA7dOVT--mSrs0srU7GGQPQyxh5EevFgMmdRYI6cRvyUGWhASTHjVMJ7um0brGMGlC3JKEw57MnQxCh62SPTKMPB32nnwhNjPEBBIQZlG-8m8LM1gZ9v0e4SFRtG2B88bIjfGGWRJc3ED14GwwzqUKx1K1FRZt7tlT9NoytIc86YHjxfdNJKy_wo7nhMNWhFJWHse3KmFYjFvDHmFRKfWg6gjLp2F6fYUhwcVjroSgm6me_CyFazjz_rnut87fRKP4NLG7tam2RyMhvfhckjCzwM_CFZgeTad2wdwIfsxOyynDyvVweDLWcvbbwXanrY |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Zb9QwEB5BOcQLZwuBAgYhIYGiOrHXcXhbCgsVsKpYCn2zcthtBUpWmywS_56ZXJBySIiXfbDH0noyY8-nGX8D8ChOM5mpSPiK57EvFbd-qmL8EbmIJmkmtGybTUTzuT48jPe7PqdVX-3epyTbNw3E0lTUO8vctS6u1U4VEO8awuDYJ4J1X56Fc5J6BhFcX3wc0ghE2N-lMn-7bHQZNZz9v57MP11Np8smT-VOmytpduW_N3MVLnfRKJu25nMNztjiOlxo-1N-uwHTd0lxnNQYPzLqIdSQKrCkyNnuqlwu7eoZS1hLBc0w9mWvPk0XbGmTzyy3dVPiVWzCwezlh93Xftdzwc-UiGo_1NzyFG-sXOFAgsEAdzJXRJsmVMqda_hmeBS7ibIiCJ22joQQVsUiyJzYgo2iLOwtYKlKEQvqSIsU44AoSEUmY53z0FqnRGo94L3yTdYRklNfjC-mASZamVYzBjVjSDNGevBkWLJs2Tj-JvycvuggSETazUC5OjKdXxrBpQtyKqRFpBy6GE0TRyTGLQiNnXYePCR7MESVUVAtzlGyriqzt3hvphNiCyM86sHjTsiVuIMs6Z42oB6IXWskuT2SRF_OxtO92ZnuLKlMGCgtMcqacA8eDNO0kurjCluuSQbPWUlsdB7cbK102DeCQiEx7PMgGtnvSDHjmeLkuGEaV0LQ220PnvZW_ONv_VHvt_9J-j5c3H8xM2_35m_uwKWQvIAHfhBsw0a9Wtu7cD77Wp9Uq3uNZ38Hg1NHvg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Manhattan+Harvester+and+Cropper%3A+a+system+for+GWAS+peak+detection&rft.jtitle=BMC+bioinformatics&rft.au=Toomas+Haller&rft.au=T%C3%B5nis+Tasa&rft.au=Andres+Metspalu&rft.date=2019-01-11&rft.pub=BMC&rft.eissn=1471-2105&rft.volume=20&rft.issue=1&rft.spage=1&rft.epage=8&rft_id=info:doi/10.1186%2Fs12859-019-2600-4&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_304f1d24002542f984104f4426721f8f |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1471-2105&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1471-2105&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1471-2105&client=summon |