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Tutorial: guidelines for quality filtering of whole-exome and whole-genome sequencing data for population-scale association analyses

Nature Protocols (2025)Cite this article

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Abstract

Genetic sequencing technologies are powerful tools for identifying rare variants and genes associated with Mendelian and complex traits; indeed, whole-exome and whole-genome sequencing are increasingly popular methods for population-scale genetic studies. However, careful quality control steps should be taken to ensure study accuracy and reproducibility, and sequencing data require extensive quality filtering to delineate true variants from technical artifacts. Although processing standards are harmonized across pipelines to call variants from sequencing reads, there currently exists no standardized pipeline for conducting quality filtering on variant-level datasets for the purpose of population-scale association analysis. In this Tutorial, we discuss key quality control parameters, provide guidelines for conducting quality filtering of samples and variants, and compare commonly used software programs for quality control of samples, variants and genotypes from sequencing data. As sequencing data continue to gain popularity in genetic research, establishing standardized quality control practices is crucial to ensure consistent, reliable and reproducible results across studies.

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Fig. 1: Overview of data processing steps and quality filtering for samples, genotypes and variants for sequencing data.
Fig. 2: The effects of filtering heterozygosity ratio with criteria from different samples stratified by ancestry.
Fig. 3: Distributions of sample QC metrics stratified by ancestry for WES (left) and WGS (right) from the 1KGP+HGDP dataset.

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Data availability

Figures 2 and 3 and Table 3 were created using the publicly available 1000 Genomes Project phase 3 and Human Genome Diversity Project data. These datasets can be directly loaded into Hail as a matrix table using the dataset repository (https://hail.is/docs/0.2/datasets.html).

Code availability

Python code for conducting sample and variant filtering using Hail can be found here at https://github.com/jsealock1/sequencing_qc.

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Acknowledgements

This work is supported by the Novo Nordisk Foundation (NNF21SA0072102) with the following funding sources: R37MH107649, U01MH125047, R01MH101244.

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Authors and Affiliations

  1. Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA

    Julia M. Sealock, Franjo Ivankovic, Calwing Liao, Siwei Chen, Claire Churchhouse, Konrad J. Karczewski, Daniel P. Howrigan & Benjamin M. Neale

  2. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Julia M. Sealock, Franjo Ivankovic, Calwing Liao, Siwei Chen, Claire Churchhouse, Konrad J. Karczewski, Daniel P. Howrigan & Benjamin M. Neale

  3. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Konrad J. Karczewski & Benjamin M. Neale

  4. Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Konrad J. Karczewski & Benjamin M. Neale

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  1. Julia M. Sealock
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Contributions

This tutorial was designed, developed, and written by J.M.S.; F.I., C.L., S.C., C.C., K.J.K., D.P.H. and B.M.N. provided critical feedback and manuscript edits; and K.J.K., D.P.H. and and B.M.N. supervised the work. All authors approved the final manuscript.

Corresponding author

Correspondence to Julia M. Sealock.

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Competing interests

B.M.N. is a member of the scientific advisory board at Deep Genomics and Neumora. K.J.K. is a consultant for Tome Biosciences, AlloDx and Vor Biosciences, and a member of the scientific advisory board of Nurture Genomics.

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Nature Protocols thanks Valerio Napolioni, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Note on Sequencing Generation, Supplementary Fig. 1 describing the structure of a Hail matrix table and references for the Supplementary Note.

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Sealock, J.M., Ivankovic, F., Liao, C. et al. Tutorial: guidelines for quality filtering of whole-exome and whole-genome sequencing data for population-scale association analyses. Nat Protoc (2025). https://doi.org/10.1038/s41596-025-01169-1

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