The (in)dependence of single-cell data inferences on model constructs.

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Tác giả: Qhawe Bhembe, Robert G Cowell, Catherine M Grgicak, Desmond S Lun, Klaas Slooten

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: Netherlands : Forensic science international. Genetics , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 737108

Recent developments in single-cell analysis have revolutionized basic research and have garnered the attention of the forensic domain. Though single-cell analysis is not new to forensics, the ways in which these data can be generated and interpreted are. Modern interpretation strategies report likelihood ratios that rely on a model of the world that is a simplification of it. It is, therefore, plausible that different reasonable models will assign noticeably different weights of evidence (WoEs) to some of these data, resulting in inconsistent reports and protracted reviews of that evidence, potentially across years. With one goal of research being to identify and understand sources of inconsistencies during early stages, we undertake a study that evaluates WoE at the limit of one single-cell electropherogram (scEPG) across three architecturally distinct probabilistic models. The three are named EESCIt (Evidentiary Evaluation of Single Cells), TD (Top-Down), and DCM (Discrete Cell Model). To do this, we performance test the three models on a set of 996 individual scEPGs and conduct one H
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