Bioinformatics AdvancesBioinformaticsPeer-reviewed journal article
EGGS: Empirical Genotype Generalizer for Samples
Abstract
SummaryWe introduce Empirical Genotype Generalizer for Samples (EGGS) which accepts empirical genotypes with missing data and replicates the distribution of missing genotypes along the empirical segment in other replicates. The empirical segment must have a number of sites less than the replicate. In addition, EGGS can remove phase, remove polarization, simulate deamination, simulate sequencing error, create pseudohaploids, and convert between Variant Call Format (VCF), ms-style replicates, and EIGENSTRAT/ANCESTRYMAP. When producing VCF files, EGGS is not limited to biallelic sites and assumes all samples are diploid. Availability and ImplementationEGGS is written in the C programming language. Precompiled executables, source code, the manual, and the analysis conducted in the paper are available at https://github.com/TQ-Smith/EGGS
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: variant effect prediction
- research focus: software / tool
- approach: statistical model
- Citations
- 2
- FWCI
- 4.16
- Field percentile
- top 9%
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