A design study to identify inconsistencies in kinship information

The case of the 1000 Genomes project

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Genome Wide Association Studies (GWAS) examine genetic variants in different individuals to detect variants associated to specific diseases. The 1000 Genomes project is such a collaborative research effort to sequence the genomes of at least 1000 participants of 26 different ethnicities, to establish a detailed summary of human genetic variation. The kinship information is a measure of individuals ancestor relationships within the considered populations. We study the design of kinship data visualizations allowing the experts to discover anomalies in GWAS data. The visual analysis of the 1000 Genomes Project kinship data reveals inconsistencies which call for a deeper analysis of the data quality within this project.

Original languageEnglish
Title of host publication2016 IEEE Pacific Visualization Symposium, PacificVis 2016 - Proceedings
PublisherIEEE Computer Society
Pages254-258
Number of pages5
Volume2016-May
ISBN (Electronic)9781509014514
DOIs
Publication statusPublished - 4 May 2016
Event9th IEEE Pacific Visualization Symposium, PacificVis 2016 - Taipei, Taiwan, Province of China
Duration: 19 Apr 201622 Apr 2016

Other

Other9th IEEE Pacific Visualization Symposium, PacificVis 2016
CountryTaiwan, Province of China
CityTaipei
Period19/4/1622/4/16

Fingerprint

Genes
Data visualization

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Software

Cite this

Aupetit, M., Ullah, E., Rawi, R., & Bensmail, H. (2016). A design study to identify inconsistencies in kinship information: The case of the 1000 Genomes project. In 2016 IEEE Pacific Visualization Symposium, PacificVis 2016 - Proceedings (Vol. 2016-May, pp. 254-258). [7465281] IEEE Computer Society. https://doi.org/10.1109/PACIFICVIS.2016.7465281

A design study to identify inconsistencies in kinship information : The case of the 1000 Genomes project. / Aupetit, Michael; Ullah, Ehsan; Rawi, Reda; Bensmail, Halima.

2016 IEEE Pacific Visualization Symposium, PacificVis 2016 - Proceedings. Vol. 2016-May IEEE Computer Society, 2016. p. 254-258 7465281.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Aupetit, M, Ullah, E, Rawi, R & Bensmail, H 2016, A design study to identify inconsistencies in kinship information: The case of the 1000 Genomes project. in 2016 IEEE Pacific Visualization Symposium, PacificVis 2016 - Proceedings. vol. 2016-May, 7465281, IEEE Computer Society, pp. 254-258, 9th IEEE Pacific Visualization Symposium, PacificVis 2016, Taipei, Taiwan, Province of China, 19/4/16. https://doi.org/10.1109/PACIFICVIS.2016.7465281
Aupetit M, Ullah E, Rawi R, Bensmail H. A design study to identify inconsistencies in kinship information: The case of the 1000 Genomes project. In 2016 IEEE Pacific Visualization Symposium, PacificVis 2016 - Proceedings. Vol. 2016-May. IEEE Computer Society. 2016. p. 254-258. 7465281 https://doi.org/10.1109/PACIFICVIS.2016.7465281
Aupetit, Michael ; Ullah, Ehsan ; Rawi, Reda ; Bensmail, Halima. / A design study to identify inconsistencies in kinship information : The case of the 1000 Genomes project. 2016 IEEE Pacific Visualization Symposium, PacificVis 2016 - Proceedings. Vol. 2016-May IEEE Computer Society, 2016. pp. 254-258
@inproceedings{b940de08888d45ff83fa1369afabd0fb,
title = "A design study to identify inconsistencies in kinship information: The case of the 1000 Genomes project",
abstract = "Genome Wide Association Studies (GWAS) examine genetic variants in different individuals to detect variants associated to specific diseases. The 1000 Genomes project is such a collaborative research effort to sequence the genomes of at least 1000 participants of 26 different ethnicities, to establish a detailed summary of human genetic variation. The kinship information is a measure of individuals ancestor relationships within the considered populations. We study the design of kinship data visualizations allowing the experts to discover anomalies in GWAS data. The visual analysis of the 1000 Genomes Project kinship data reveals inconsistencies which call for a deeper analysis of the data quality within this project.",
author = "Michael Aupetit and Ehsan Ullah and Reda Rawi and Halima Bensmail",
year = "2016",
month = "5",
day = "4",
doi = "10.1109/PACIFICVIS.2016.7465281",
language = "English",
volume = "2016-May",
pages = "254--258",
booktitle = "2016 IEEE Pacific Visualization Symposium, PacificVis 2016 - Proceedings",
publisher = "IEEE Computer Society",

}

TY - GEN

T1 - A design study to identify inconsistencies in kinship information

T2 - The case of the 1000 Genomes project

AU - Aupetit, Michael

AU - Ullah, Ehsan

AU - Rawi, Reda

AU - Bensmail, Halima

PY - 2016/5/4

Y1 - 2016/5/4

N2 - Genome Wide Association Studies (GWAS) examine genetic variants in different individuals to detect variants associated to specific diseases. The 1000 Genomes project is such a collaborative research effort to sequence the genomes of at least 1000 participants of 26 different ethnicities, to establish a detailed summary of human genetic variation. The kinship information is a measure of individuals ancestor relationships within the considered populations. We study the design of kinship data visualizations allowing the experts to discover anomalies in GWAS data. The visual analysis of the 1000 Genomes Project kinship data reveals inconsistencies which call for a deeper analysis of the data quality within this project.

AB - Genome Wide Association Studies (GWAS) examine genetic variants in different individuals to detect variants associated to specific diseases. The 1000 Genomes project is such a collaborative research effort to sequence the genomes of at least 1000 participants of 26 different ethnicities, to establish a detailed summary of human genetic variation. The kinship information is a measure of individuals ancestor relationships within the considered populations. We study the design of kinship data visualizations allowing the experts to discover anomalies in GWAS data. The visual analysis of the 1000 Genomes Project kinship data reveals inconsistencies which call for a deeper analysis of the data quality within this project.

UR - http://www.scopus.com/inward/record.url?scp=84973594532&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84973594532&partnerID=8YFLogxK

U2 - 10.1109/PACIFICVIS.2016.7465281

DO - 10.1109/PACIFICVIS.2016.7465281

M3 - Conference contribution

VL - 2016-May

SP - 254

EP - 258

BT - 2016 IEEE Pacific Visualization Symposium, PacificVis 2016 - Proceedings

PB - IEEE Computer Society

ER -