ArticleBioinformatics (Oxford, England)2013
AbCD: arbitrary coverage design for sequencing-based genetic studies.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
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Who cites it
9 citing papers in PubMed.
- Advances in haplotype phasing and genotype imputation.Nature reviews. Genetics · 2026Review
- Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework.Mathematics (Basel, Switzerland) · 2023Article
- Increased burden of ultra-rare structural variants localizing to boundaries of topologically associated domains in schizophrenia.Nature communications · 2020Article
- Analysis of genetic and nongenetic factors influencing triglycerides-lowering drug effects based on paired observations.BMC proceedings · 2018Article
- Low-, high-coverage, and two-stage DNA sequencing in the design of the genetic association study.Genetic epidemiology · 2017Article
- Likelihood-based complex trait association testing for arbitrary depth sequencing data.Bioinformatics (Oxford, England) · 2015Article
- Association studies with imputed variants using expectation-maximization likelihood-ratio tests.PloS one · 2014Article
- Imputation of coding variants in African Americans: better performance using data from the exome sequencing project.Bioinformatics (Oxford, England) · 2013Article
- Advances in biotechnology and informatics to link variation in the genome to phenotypes in plants and animals.Functional & integrative genomics · 2013Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Recent advances in sequencing technologies have revolutionized genetic studies. Although high-coverage sequencing can uncover most variants present in the sequenced sample, low-coverage sequencing is appealing for its cost effectiveness. Here, we present AbCD (arbitrary coverage design) to aid the design of sequencing-based studies. AbCD is a user-friendly interface providing pre-estimated effective sample sizes, specific to each minor allele frequency category, for designs with arbitrary coverage (0.5-30×) and sample size (20-10 000), and for four major ethnic groups (Europeans, Africans, Asians and African Americans). In addition, we also present two software tools: ShotGun and DesignPlanner, which were used to generate the estimates behind AbCD. ShotGun is a flexible short-read simulator for arbitrary user-specified read length and average depth, allowing cycle-specific sequencing error rates and realistic read depth distributions. DesignPlanner is a full pipeline that uses ShotGun to generate sequence data and performs initial SNP discovery, uses our previously presented linkage disequilibrium-aware method to call genotypes, and, finally, provides minor allele frequency-specific effective sample sizes. ShotGun plus DesignPlanner can accommodate effective sample size estimate for any combination of high-depth and low-depth data (for example, whole-genome low-depth plus exonic high-depth) or combination of sequence and genotype data [for example, whole-exome sequencing plus genotyping from existing Genomewide Association Study (GWAS)].
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.