Abstract
Most ancestry-assignment methods rely on putatively pure reference panels, which are often unrealistic and bias inference. The genome polarisation algorithm diem , introduced previously, avoids reference panels by jointly inferring the polarity of common allelic states and quantifying variant diagnosticity via an expectation–maximisation procedure. Here we present diempy , an efficient python implementation of diem coupled with tools that turn polarised calls into analysis-ready outputs. diempy offers lossless VCF-to- diem BED conversion; ploidy-aware handling of individuals and chromosomes; flexible masking of sites, regions and individuals; and interactive visualisation of polarised genomes, hybrid indices, clines and ternary plots. Post-processing functions include DI thresholding, kernel smoothing, and automatic detection and run-length encoding of contiguous ancestry tracts. BED-based I/O facilitates integration with population-genomic workflows (e.g. filtering by annotation or ploidy). These features make reference-free genome polarisation with diempy practical and reproducible for studies of population structure, admixture and species barriers.
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Abstract
Most ancestry-assignment methods rely on putatively pure reference panels, which are often unrealistic and bias inference. The genome polarisation algorithm diem, introduced previously, avoids reference panels by jointly inferring the polarity of common allelic states and quantifying variant diagnosticity via an expectation–maximisation procedure. Here we present diempy, an efficient python implementation of diem coupled with tools that turn polarised calls into analysis-ready outputs. diempy offers lossless VCF-to-diem BED conversion; ploidy-aware handling of individuals and chromosomes; flexible masking of sites, regions and individuals; and interactive visualisation of polarised genomes, hybrid indices, clines and ternary plots. Post-processing functions include DI thresholding, kernel smoothing, and automatic detection and run-length encoding of contiguous ancestry tracts. BED-based I/O facilitates integration with population-genomic workflows (e.g. filtering by annotation or ploidy). These features make reference-free genome polarisation with diempy practical and reproducible for studies of population structure, admixture and species barriers.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Figure 2: The labels and ordering of individuals was wrong in two subpanels. This has been fixed. There is no change to the data or to the results, simply fixing a plotting error.
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