Journal
Elife
Publication Date
2022
Volume
11
First Page
e73577
Document Type
Open Access Publication
DOI
10.7554/eLife.73577
Rights and Permissions
eLife 2022;11:e73577 DOI: 10.7554/eLife.73577. © 2022, Bergeron et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Recommended Citation
Bergeron, Lucie A.; Turner, Tychele; and et al, "The Mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates." Elife. 11, e73577 (2022).
https://digitalcommons.wustl.edu/open_access_pubs/11408
elife-73577-fig3-data1-v2.xlsx (12 kB)
Figure 3—source data 1 PCR validation of the candidate DNMs found by the various pipelines during the Mutationathon. TP means validated as true positive DNM and FP appeared as false positive. The genotypes of all individuals as shown by the PCR validation are presented.
elife-73577-fig3-data2-v2.pdf (2083 kB)
Figure 3—source data 2 Sanger sequencing chromatograms of the 39 DNM candidate sites that were successfully amplified for the four individuals, i.e. father (Noot), mother (M), offspring (Heineken), and second-generation offspring (Hoegaarde). For each alignment, the candidate germline mutation position is located under the black square. The last six chromatograms (surrounded by red boxes) are the candidates that were detected as false-positive candidates.
elife-73577-fig4-data1-v2.xlsx (7 kB)
Figure 4—source data 1 Number of candidate DNMs, estimated callable genome and per generation mutation rate by each researcher group.
elife-73577-fig5-data1-v2.xlsx (9 kB)
Figure 5—source data 1 Details on the number of candidate DNMs, the number of false positive calls, the size of the callable genome, the false negative rate and the final estimated mutation rate using various individual filters.
elife-73577-supp1-v2.docx (55 kB)
Supplementary file 1 Four supplementary tables with details on the methods used in the literature, Genome Analysis ToolKit (GATK) site filters, site-specific and sample-specific filters used in the literature, and the PCR experiment.
elife-73577-transrepform1-v2.docx (108 kB)
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