Evidence map›Paper›PMID 37745566›Full record

ArticlebioRxiv : the preprint server for biology2023

Decreased accuracy of forensic DNA mixture analysis for groups with lower genetic diversity.

Maria Flores, Cara Ly, Evan Ho, Niquo Ceberio, Kamillah Felix, Hannah Mariko Thorner, Miguel Guardado, Matt Paunovich, Chris Godek, Carina Kalaydjian and 1 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Maria FloresSan Francisco State University; Department of Biology; San Francisco, CA, 94132, USA.
Cara LySan Francisco State University; Department of Biology; San Francisco, CA, 94132, USA.
Evan HoSan Francisco State University; Department of Biology; San Francisco, CA, 94132, USA.
Niquo CeberioSan Francisco State University; Department of Biology; San Francisco, CA, 94132, USA.
Kamillah FelixSan Francisco State University; Department of Biology; San Francisco, CA, 94132, USA.
Hannah Mariko ThornerGeorge Washington University; Department of Forensic Sciences - Forensic Molecular Biology; Washington, DC, 20007, USA.
Miguel GuardadoUniversity of California, San Francisco; Biological and Medical Informatics Graduate Program; San Francisco CA, 94143, USA.
Matt PaunovichSan Francisco State University; Department of Biology; San Francisco, CA, 94132, USA.
Chris GodekSan Francisco State University; Department of Mathematics; San Francisco, CA, 94132, USA.
Carina KalaydjianSan Francisco State University; Department of Mathematics; San Francisco, CA, 94132, USA.
Rori RohlfsSan Francisco State University; Department of Biology; San Francisco, CA, 94132, USA.

Funding

SFSU MBRS - RISER25GM059298 · NIGMS · SAN FRANCISCO STATE UNIVERSITY · PI BAIRD, TEASTER T, BAYLISS, FRANK T · 1999 to 2021
$21.0M
UPGRADE OF COMMUNICATIONS INFRASTRUCTURET34GM008574 · NIGMS · SAN FRANCISCO STATE UNIVERSITY · PI BAYLISS, FRANK T, ESQUERRA, RAYMOND M. · 1996 to 2021
$14.5M
NIGMS NIH HHS R25 GM059298NIGMS NIH HHS T34 GM008574
6 · The paper itself

Abstract

Forensic investigation of DNA samples from multiple contributors has become commonplace. These complex analyses use statistical frameworks accounting for multiple levels of uncertainty in allelic contributions from different individuals, particularly for samples containing few molecules of DNA. These methods have been thoroughly tested along some axes of variation, but less attention has been paid to accuracy across human genetic variation. Here, we quantify the accuracy of DNA mixture analysis over 244 human groups. We find higher false inclusion rates for mixtures with more contributors, and for groups with lower genetic diversity. Even for two-contributor mixtures where one contributor is known and the reference group is correctly specified, false inclusion rates are 1e-5 or higher for 56 out of 244 groups. This means that, depending on multiple testing, some false inclusions may be expected. These false positives could be lessened with more selective and conservative use of DNA mixture analysis.

Identifiers

PMID37745566
PMCPMC10515773

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.