首页|SLEDGe: Inference of ancient whole genome duplications using machine learning
SLEDGe: Inference of ancient whole genome duplications using machine learning
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NETL
NSTL
According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from biorxiv.org: “Ancient whole-genome duplication–previous genome duplication events that have since been eroded via diploidization, are increasingly identified throughout eukaryotes. One of the constraints against large-scale studies of ancient eukaryotic WGD is the relatively large, high-quality datasets often needed to definitively establish ancient WGD events; alternatively, the more low-input method interpretation of genome-wide synonymous substitution rates (Ks plots) is prone to bias and inconsistency. We improve upon the shortcomings of the current Ks plot method by building a Ks plot simulator. “This data-agnostic approach simulates common distributions found in Ks plots in the presence or absence of ancient WGD signatures. “In conjunction with a machine-learning classifier, this approach can quickly assess the likelihood that transcriptomic and genomic data bear WGD signatures. On independently-generated synthetic data and real plant transcriptomic data, SLEDGE is capable of correctly identifying ancient WGD in 93-100% of samples.
NETL
NSTL
