The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
gargammel: a sequence simulator for ancient DNA
Abstract
Summary: Ancient DNA has emerged as a remarkable tool to infer the history of extinct species and past populations. However, many of its characteristics, such as extensive fragmentation, damage and contamination, can influence downstream analyses. To help investigators measure how these could impact their analyses in silico, we have developed gargammel, a package that simulates ancient DNA fragments given a set of known reference genomes. Our package simulates the entire molecular process from post-mortem DNA fragmentation and DNA damage to experimental sequencing errors, and reproduces most common bias observed in ancient DNA datasets. Availability and Implementation: The package is publicly available on github: https://grenaud.github.io/gargammel/ and released under the GPL. Supplementary information: Supplementary data are available at Bioinformatics online.
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Quantitative assessment of damage and contamination followed by explicit simulation can help establish robustness of conclusions.
“Quantitative assessment of damage and contamination followed by explicit simulation 180 can help establish the robustness of the conclusions.”
From Ancient DNA analysis (2021) · cites this paper as [180]
The Methods describe simulations with specified contamination rates and damage models, and the Features section says these simulations can evaluate the robustness of analyses. The paper does not describe a prior quantitative assessment of damage and contamination followed by simulation as a distinct workflow. (LLM, conf=0.82)
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Cites
mapDamage2.0: fast approximate Bayesian estimates of ancient DNA damage parameters
Jónsson, H., Ginolhac, A., Schubert, M., Johnson, P. L. F., & Orlando, L. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt193 · Cited by 1,669
Self-citationThe genome of a Late Pleistocene human from a Clovis burial site in western Montana
Rasmussen, M., Anzick, S. L., Waters, M. R., Skoglund, P., DeGiorgio, M., Stafford, T. W., Rasmussen, S., Moltke, I., Albrechtsen, A., Doyle, S. M., et al. (2014) · Nature · doi:10.1038/nature13025 · Cited by 562
Self-citationImproving ancient DNA read mapping against modern reference genomes
Schubert, M., Ginolhac, A., Lindgreen, S., Thompson, J. F., AL-Rasheid, K. A., Willerslev, E., Krogh, A., & Orlando, L. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-178 · Cited by 325
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Research works printed but not linked: 6
- Briggs, 2007, Patterns of damage in genomic DNA sequences from a Neandertal, Proc. Natl. Acad. Sci. U. S. A, 104, 14616, 10.1073/pnas.0704665104 · DOI · Paper page
- Durand, 2011, Testing for ancient admixture between closely related populations, Mol. Biol. Evol, 28, 2239, 10.1093/molbev/msr048 · DOI · Paper page
- Green, 2009, The Neandertal genome and ancient DNA authenticity, EMBO J, 28, 2494, 10.1038/emboj.2009.222 · DOI · Paper page
- Huang, 2012, ART: a next-generation sequencing read simulator, Bioinformatics, 28, 593, 10.1093/bioinformatics/btr708 · DOI
- Leonardi, 2016, Evolutionary patterns and processes: lessons from ancient DNA, Syst. Biol, syw059., 10.1093/sysbio/syw059 · DOI
- Seguin-Orlando, 2013, Ligation bias in Illumina next-generation DNA libraries: implications for sequencing ancient genomes, PLOS One, 8, e78575., 10.1371/journal.pone.0078575 · DOI · Paper page
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Orlando, L., Allaby, R., Skoglund, P., Der Sarkissian, C., Stockhammer, P. W., Ávila-Arcos, M. C., Fu, Q., Krause, J., Willerslev, E., Stone, A. C., et al. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-020-00011-0 · Cited by 411
Self-citationEstimating genetic kin relationships in prehistoric populations
Monroy Kuhn, J. M., Jakobsson, M., & Günther, T. (2018) · PLOS ONE · doi:10.1371/journal.pone.0195491 · Cited by 330
Günther, T., & Nettelblad, C. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008302 · Cited by 228
Martiniano, R., Garrison, E., Jones, E. R., Manica, A., & Durbin, R. (2020) · Genome Biology · doi:10.1186/s13059-020-02160-7 · Cited by 128
“We then added different levels of deamination into simulated reads using gargammel [23], based on empirically estimated post-mortem damage in a dataset of 102 ancient genomes [22].”
MethodInfluentialJoint estimates of heterozygosity and runs of homozygosity for modern and ancient samples
Renaud, G., Hanghøj, K., Korneliussen, T. S., Willerslev, E., & Orlando, L. (2019) · Genetics · doi:10.1534/genetics.119.302057 · Cited by 101
Self-citationSystematic benchmark of ancient DNA read mapping
Oliva, A., Tobler, R., Cooper, A., Llamas, B., & Souilmi, Y. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab076 · Cited by 63
Assessing DNA sequence alignment methods for characterizing ancient genomes and methylomes
Poullet, M., & Orlando, L. (2020) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2020.00105 · Cited by 61
Self-citationQuantifying and reducing spurious alignments for the analysis of ultra-short ancient DNA sequences
de Filippo, C., Meyer, M., & Prüfer, K. (2018) · BMC Biology · doi:10.1186/s12915-018-0581-9 · Cited by 53
Unravelling reference bias in ancient DNA datasets
Dolenz, S., van der Valk, T., Jin, C., Oppenheimer, J., Sharif, M. B., Orlando, L., Shapiro, B., Dalén, L., & Heintzman, P. D. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae436 · Cited by 33
“The proportion of mismapped reads was calculated by searching for reads whose mapping coordinates did not match their known coordinates of origin that were retained in the read header by Gargammel.”
MethodSelf-citationMoreno-Mayar, J. V., Korneliussen, T. S., Dalal, J., Renaud, G., Albrechtsen, A., Nielsen, R., & Malaspinas, A.-S. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz660 · Cited by 21
Self-citationXu, W., Lin, Y., Zhao, K., Li, H., Tian, Y., Ngatia, J. N., Ma, Y., Sahu, S. K., Guo, H., Guo, X., et al. (2021) · Ecology and Evolution · doi:10.1002/ece3.7056 · Cited by 20
Metadata
- Authors
- Renaud, G., Hanghøj, K., Willerslev, E., & Orlando, L.
- Affiliations
- Center for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-11-21
- Volume
- 33
- Issue
- 4
- Pages
- 577-579
- ISSN
- 1367-4803
- 1367-4811
- PMC
- PMC5408798
- Cited by
- 150
- References
- 3
- Language
- en
- Funders
- Danish Council for Independent Research, Natural Sciences (4002-00152B)
- Danish National Research Foundation (DNRF94)
- Villum Fonden
- Initiative d’Excellence Chaires d’attractivité, Université de Toulouse
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