Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research
On region based inference in genome wide association study. / Malov , Sergey V. ; Antonik, Alexey ; Shevchenko, Andrey K. .
Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2020): The Twelfth International Multiconference (06–10 July 2020, Novosibirsk, Russia); Abstracts. Novosibirsk : Институт цитологии и генетики Сибирского отделения Российской академии наук, 2020. p. 177-178.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research
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TY - GEN
T1 - On region based inference in genome wide association study
AU - Malov , Sergey V.
AU - Antonik, Alexey
AU - Shevchenko, Andrey K.
N1 - Conference code: 12
PY - 2020
Y1 - 2020
N2 - We consider an advanced framework forgenome wide association study (GWAS) based on the signallocalization. Instead of looking for single genetic markersassociated with the phenotype we attempt to discover regionsof genetic markers, which are associated with phenotype. Wefocus on the localization by moving sums of negativelogarithms of p-values, which is efficient for discovery of wideregions of genetic markers associated with phenotype.Particularly, we expect the method should be efficient forsearching genes containing a number of genetic markers, if anyreconstruction in a gene related to a phenotype. The method isimplemented in GWATCH software for visualization andinterpretation results of multiple statistical tests for genomeassociations. We discuss some features of the GWATCHsoftware and apply them for HIV/AIDS cohort study fromBotswana.
AB - We consider an advanced framework forgenome wide association study (GWAS) based on the signallocalization. Instead of looking for single genetic markersassociated with the phenotype we attempt to discover regionsof genetic markers, which are associated with phenotype. Wefocus on the localization by moving sums of negativelogarithms of p-values, which is efficient for discovery of wideregions of genetic markers associated with phenotype.Particularly, we expect the method should be efficient forsearching genes containing a number of genetic markers, if anyreconstruction in a gene related to a phenotype. The method isimplemented in GWATCH software for visualization andinterpretation results of multiple statistical tests for genomeassociations. We discuss some features of the GWATCHsoftware and apply them for HIV/AIDS cohort study fromBotswana.
KW - GWAS
KW - signal localization
KW - Chi-square test
UR - https://bgrssb.icgbio.ru/2020/wp-content/uploads/sites/2/2020/08/BGRS_2020_31.07.2020.pdf
M3 - Conference contribution
SN - 9785912910517
SP - 177
EP - 178
BT - Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2020)
PB - Институт цитологии и генетики Сибирского отделения Российской академии наук
CY - Novosibirsk
T2 - Bioinformatics of Genome Regulation and Structure/Systems Biology
Y2 - 6 July 2020 through 10 July 2020
ER -
ID: 62357949