<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Haller T</submitter><funding>Estonian Government</funding><funding>NIDDK NIH HHS</funding><funding>Estonian Center of Genomics/Roadmap II</funding><funding>EU H2020 grant ePerMed</funding><funding>US National Institute of Health</funding><funding>EU H2020 grant</funding><funding>European Regional Development Fund</funding><pagination>22</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6330393</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>20(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>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.&lt;h4>Results&lt;/h4>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 a</pubmed_abstract><journal>BMC bioinformatics</journal><pubmed_title>Manhattan Harvester and Cropper: a system for GWAS peak detection.</pubmed_title><pmcid>PMC6330393</pmcid><funding_grant_id>2014-2020.4.01.15-0012</funding_grant_id><funding_grant_id>692145</funding_grant_id><funding_grant_id>IUT20-60</funding_grant_id><funding_grant_id>R01DK075787</funding_grant_id><funding_grant_id>2014-2020.4.01.16-0125</funding_grant_id><funding_grant_id>R01 DK075787</funding_grant_id><funding_grant_id>633589</funding_grant_id><pubmed_authors>Metspalu A</pubmed_authors><pubmed_authors>Haller T</pubmed_authors><pubmed_authors>Tasa T</pubmed_authors></additional><is_claimable>false</is_claimable><name>Manhattan Harvester and Cropper: a system for GWAS peak detection.</name><description>&lt;h4>Background&lt;/h4>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.&lt;h4>Results&lt;/h4>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 a</description><dates><release>2019-01-01T00:00:00Z</release><publication>2019 Jan</publication><modification>2025-04-25T17:31:29.377Z</modification><creation>2019-03-26T22:37:54Z</creation></dates><accession>S-EPMC6330393</accession><cross_references><pubmed>30634901</pubmed><doi>10.1186/s12859-019-2600-4</doi></cross_references></HashMap>