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Ceberio, N.

Publications and source records attributed to Ceberio, N..

2 recordsLinked to original sources

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

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. HIGHLIGHTSO_LIGroups with lower genetic diversity have higher mixture analysis false positive rates. C_LIO_LIAnalyses with mis-specified references have somewhat higher false positive rates. C_LIO_LIMixture analysis accuracy decreases with more mixture contributors. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/554311v2_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@157c28aorg.highwire.dtl.DTLVardef@a4ff05org.highwire.dtl.DTLVardef@62caa0org.highwire.dtl.DTLVardef@1e4ce92_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

SCIP: A self-paced, community-based summer coding program creates community and increases coding confidence

In 2020, many students lost summer opportunities due to the COVID-19 pandemic. We wanted to offer students an opportunity to learn computational skills and be part of a community while they were stuck at home. Because the pandemic was very isolating, it was important to support students to learn and build community online. We used lessons learned from literature and our own experience to design, run and test an online program for students called the Science Coding Immersion Program (SCIP). In our program, students worked in small teams for 8 hours a week spread over the week, with one participant as the team leader and Zoom host. Teams worked on an online R or Python class at their own pace with support on Slack from the organizing team. For motivation and career advice, we hosted a weekly webinar with guest speakers. We used pre- and post-program surveys to determine how different aspects of the program impacted students. We were able to recruit a large and diverse group of participants who were happy with the program, found community in their team, and improved their coding confidence. We hope that our work will inspire others to start their own version of SCIP.

scientific communication and education↗