exML: An Explainable Maximum Likelihood Tool for Proportion Estimation in DNA Data.

International Conference on Information and Knowledge Management (CIKM)(2022)

引用 0|浏览20
暂无评分
摘要
Estimating proportions of elements in a given set is a key problem in multiple scenarios. A particular use case of interest is the analysis of ancient DNA, where the goal is to estimate the proportion of species in a set of DNA reads extracted from sediments in archaeological sites. While there is a plethora of existing solutions for this type of problem, they lack explainability, which leads to challenges in their debugging and deployment as well as in downstream analysis tasks. To this end, we have developed exML, a Maximum Likelihood Estimator equipped with novel explanation methods. We propose to demonstrate exML in the context of analyzing ancient DNA samples. We will show use cases where the explanations generated by exML provide insights on otherwise ambiguous classification results.
更多
查看译文
关键词
Maximum Likelihood, Explainability, Computational genomics, Ancient DNA, Shapley value
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要