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cgmisc: Enhanced Genome-wide Association Analyses and Visualisation
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
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2015 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 31, no 23, 3830-3831 p.Article in journal (Refereed) Published
Abstract [en]

SUMMARY:

High-throughput genotyping and sequencing technologies facilitate studies of complex genetic traits and provide new research opportunities. The increasing popularity of genome-wide association studies (GWAS) leads to the discovery of new associated loci and a better understanding of the genetic architecture underlying not only diseases, but also other monogenic and complex phenotypes. Several softwares are available for performing GWAS analyses, R environment being one of them.

RESULTS: We present cgmisc, an R package that enables enhanced data analysis and visualisation of results from GWAS. The package contains several utilities and modules that complement and enhance the functionality of the existing software. It also provides several tools for advanced visualisation of genomic data and utilises the power of the R language to aid in preparation of publication-quality figures. Some of the package functions are specific for the domestic dog (Canis familiaris) data.

AVAILABILITY: The package is operating system-independent and is available from: https://github.com/cgmisc-team/cgmisc CONTACT: cgmisc@imbim.uu.se.

Place, publisher, year, edition, pages
2015. Vol. 31, no 23, 3830-3831 p.
National Category
Bioinformatics and Systems Biology Medical Genetics
Identifiers
URN: urn:nbn:se:uu:diva-259684DOI: 10.1093/bioinformatics/btv426ISI: 000366378400016PubMedID: 6249815OAI: oai:DiVA.org:uu-259684DiVA: diva2:845064
Funder
Swedish Foundation for Strategic Research Swedish Research Council FormasSwedish Research CouncilEU, European Research CouncilEU, European Research Council
Available from: 2015-08-10 Created: 2015-08-10 Last updated: 2017-12-04Bibliographically approved

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Kierczak, MarcinJablonska, JagodaBianchi, MatteoTengvall, KatarinaPettersson, MatsMeadows, Jennifer R.Jern, PatricCarlborg, ÖrjanLindblad-Toh, Kerstin

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Kierczak, MarcinJablonska, JagodaBianchi, MatteoTengvall, KatarinaPettersson, MatsMeadows, Jennifer R.Jern, PatricCarlborg, ÖrjanLindblad-Toh, Kerstin
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Department of Medical Biochemistry and MicrobiologyScience for Life Laboratory, SciLifeLab
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Bioinformatics and Systems BiologyMedical Genetics

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