Karyon: a computational framework for the diagnosis of hybrids, aneuploids, and other nonstandard architectures in genome assemblies.

BACKGROUND: Recent technological developments have made genome sequencing and assembly highly accessible and widely used. However, the presence in sequenced organisms of certain genomic features such as high heterozygosity, polyploidy, aneuploidy, heterokaryosis, or extreme compositional biases can challenge current standard assembly procedures and result in highly fragmented assemblies. Hence, we hypothesized that genome databases must contain a nonnegligible fraction of low-quality assemblies that result from such type of intrinsic genomic factors. FINDINGS: Here we present Karyon, a Python-based toolkit that uses raw sequencing data and de novo genome assembly to assess several parameters and generate informative plots to assist in the identification of nonchanonical genomic traits. Karyon includes automated de novo genome assembly and variant calling pipelines. We tested Karyon by diagnosing 35 highly fragmented publicly available assemblies from 19 different Mucorales (Fungi) species. CONCLUSIONS: Our results show that 10 (28.57%) of the assemblies presented signs of unusual genomic configurations, suggesting that these are common, at least for some lineages within the Fungi.

HaploTypo: a variant-calling pipeline for phased genomes.

SUMMARY: An increasing number of phased (i.e. with resolved haplotypes) reference genomes are available. However, the most genetic variant calling tools do not explicitly account for haplotype structure. Here, we present HaploTypo, a pipeline tailored to resolve haplotypes in genetic variation analyses. HaploTypo infers the haplotype correspondence for each heterozygous variant called on a phased reference genome. AVAILABILITY AND IMPLEMENTATION: HaploTypo is implemented in Python 2.7 and Python 3.5, and is freely available at https://github.com/gabaldonlab/haplotypo, and as a Docker image. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.