Evidence map›Paper›PMID 33256612›Full record

ArticleBMC genomics2020

Competitive mapping allows for the identification and exclusion of human DNA contamination in ancient faunal genomic datasets.

Tatiana R Feuerborn, Eleftheria Palkopoulou, Tom van der Valk, Johanna von Seth, Arielle R Munters, Patrícia Pečnerová, Marianne Dehasque, Irene Ureña, Erik Ersmark, Vendela Kempe Lagerholm and 5 more

Abstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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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

17 citing papers in PubMed.

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  7. Unravelling reference bias in ancient DNA datasets.Bioinformatics (Oxford, England) · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Tatiana R FeuerbornGlobe Institute, University of Copenhagen, Copenhagen, Denmark. tatianafeuerborn@palaeome.org.
Eleftheria PalkopoulouDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
Tom van der ValkDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
Johanna von SethDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
Arielle R MuntersDepartment of Organismal Biology, Human Evolution, Uppsala University, Uppsala, Sweden.
Patrícia PečnerováDepartment of Biology, University of Copenhagen, Copenhagen, Denmark.
Marianne DehasqueDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
Irene UreñaDepartment of Animal Breeding, INIA, Madrid, Spain.
Erik ErsmarkDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
Vendela Kempe LagerholmArchaeological Research Laboratory, Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden.
Maja KrzewińskaArchaeological Research Laboratory, Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden.
Ricardo Rodríguez-VarelaArchaeological Research Laboratory, Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden.
Anders GötherströmArchaeological Research Laboratory, Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden.
Love DalénDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
David Díez-Del-MolinoDepartment of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden. diez.molino@gmail.com.ORCID http://orcid.org/0000-0002-9701-5940

Funding

Carl Tryggers Stiftelse för Vetenskaplig Forskning CTS17:109H2020 Marie Skłodowska-Curie Actions 676154Svenska Forskningsrådet Formas 2015-676Swedish Research Council VR 2012-3869Velux Fonden 210119/Z/18/Z
6 · The paper itself

Abstract

backgroundAfter over a decade of developments in field collection, laboratory methods and advances in high-throughput sequencing, contamination remains a key issue in ancient DNA research. Currently, human and microbial contaminant DNA still impose challenges on cost-effective sequencing and accurate interpretation of ancient DNA data.

resultsHere we investigate whether human contaminating DNA can be found in ancient faunal sequencing datasets. We identify variable levels of human contamination, which persists even after the sequence reads have been mapped to the faunal reference genomes. This contamination has the potential to affect a range of downstream analyses.

conclusionsWe propose a fast and simple method, based on competitive mapping, which allows identifying and removing human contamination from ancient faunal DNA datasets with limited losses of true ancient data. This method could represent an important tool for the ancient DNA field.

Indexed as

DNA ContaminationGenomeDNA, AncientGenomicsHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNADNA, AncientAncient DNACompetitive mappingDNA contamination removalPalaeogenomics

Identifiers

PMID33256612
PMCPMC7708127

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LicenceCC BY
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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.