TY - JOUR
T1 - QCEWAS
T2 - automated quality control of results of epigenome-wide association studies
AU - Van Der Most, Peter J.
AU - Küpers, Leanne K.
AU - Snieder, Harold
AU - Nolte, Ilja
N1 - © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected].
PY - 2017/4/15
Y1 - 2017/4/15
N2 - Summary: The increasing popularity of epigenome-wide association studies (EWAS) has led to the establishment of several large international meta-analysis consortia. However, when using data originating from multiple sources, a thorough and centralized quality control is essential. To facilitate this, we developed the QCEWAS R package. QCEWAS enables automated quality control of results files of EWAS. QCEWAS produces cohort-specific statistics and graphs to interpret the quality of the results files, graphs comparing results of multiple cohorts, as well as cleaned input files ready for meta-analysis.
AB - Summary: The increasing popularity of epigenome-wide association studies (EWAS) has led to the establishment of several large international meta-analysis consortia. However, when using data originating from multiple sources, a thorough and centralized quality control is essential. To facilitate this, we developed the QCEWAS R package. QCEWAS enables automated quality control of results files of EWAS. QCEWAS produces cohort-specific statistics and graphs to interpret the quality of the results files, graphs comparing results of multiple cohorts, as well as cleaned input files ready for meta-analysis.
UR - http://www.scopus.com/inward/record.url?scp=85019098725&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btw766
DO - 10.1093/bioinformatics/btw766
M3 - Article (Academic Journal)
C2 - 28119308
SN - 1367-4811
VL - 33
SP - 1243
EP - 1245
JO - Bioinformatics
JF - Bioinformatics
IS - 8
ER -