QCEWAS: automated quality control of results of epigenome-wide association studies

Peter J. Van Der Most; Leanne K. Küpers; Harold Snieder; Ilja Nolte

doi:10.1093/bioinformatics/btw766

QCEWAS: automated quality control of results of epigenome-wide association studies

Peter J. Van Der Most, Leanne K. Küpers, Harold Snieder, Ilja Nolte^*

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

31 Citations (Scopus)

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Abstract

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.

Original language	English
Pages (from-to)	1243-1245
Number of pages	3
Journal	Bioinformatics
Volume	33
Issue number	8
Early online date	24 Jan 2017
DOIs	https://doi.org/10.1093/bioinformatics/btw766
Publication status	Published - 15 Apr 2017

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abstract = "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.",

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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

PY - 2017/4/15

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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 - https://www.scopus.com/pages/publications/85019098725

U2 - 10.1093/bioinformatics/btw766

DO - 10.1093/bioinformatics/btw766

M3 - Article (Academic Journal)

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SP - 1243

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JO - Bioinformatics

JF - Bioinformatics

IS - 8

ER -

QCEWAS: automated quality control of results of epigenome-wide association studies

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