Very low-depth whole-genome sequencing in complex trait association studies

@inproceedings{Gilly2018VeryLW,
  title={Very low-depth whole-genome sequencing in complex trait association studies},
  author={A de Kersaint Gilly and Lorraine Southam and Daniel Suveges and Karoline Kuchenbaecker and Rachel M. Moore and Giorgio E. M. Melloni and Konstantinos Hatzikotoulas and Aliki-Eleni Farmaki and Graham R. S. Ritchie and Jeremy Schwartzentruber and Peter Danecek and Britt Kilian and Martin O Pollard and Xiangyu Ge and Emmanouil Tsafantakis and George V.Z. Dedoussis and Eleftheria Zeggini},
  booktitle={Bioinformatics},
  year={2018}
}
Motivation Very low depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterisation of the genotype quality and association power for very low depth sequencing designs is still lacking. Results We perform cohort-wide whole genome sequencing (WGS) at low depth in 1,239 individuals (990 at 1x depth and 249 at 4x depth) from an isolated population, and establish a robust pipeline… CONTINUE READING
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Key Quantitative Results

  • Using genotyping chip, whole-exome sequencing (WES, 75x depth) and high-depth (22x) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1x WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants.
  • Using genotyping chip, whole-exome sequencing (75 depth) and high-depth (22 ) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1 WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants.
  • 2.1 Variant calling pipeline Prior to any imputation-based refinement, our approach allowed the capture of 80 and 100% of low-frequency (MAF 1–5%) and common (MAF > 5%) SNVs, respectively, when compared to variants present on the Illumina OmniExpress and HumanExome chips genotyped in the same samples. In 10 control samples from the Platinum Genomes dataset (Eberle et al., 2017) with high-depth WGS data (50 ) downsampled to 1 , joint calling with MANOLIS resulted in pre-imputation false-positive and false-negative rates of 12 and 24.6%, respectively (see Section 4).

References

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