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...

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Bibliographic Details
Published in:BMC bioinformatics Vol. 20; no. 1; pp. 22 - 8
Main Authors: Haller, Toomas, Tasa, Tõnis, Metspalu, Andres
Format: Journal Article
Language:English
Published: London BioMed Central 11.01.2019
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
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
Estonia
Peak detection
Software
GWAS
Peak quality score
Manhattan plots
ISSN:1471-2105, 1471-2105
Online Access:Get full text
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Summary: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.
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-019-2600-4