Home > Publications database > A practical guide to identifying associations between tandem repeats and complex human traits using consensus genotypes from multiple tools. > print

001     304286
005     20250907022521.0
024 7 _ |a 10.1038/s41596-025-01231-y
|2 doi
024 7 _ |a pmid:40890532
|2 pmid
024 7 _ |a 1754-2189
|2 ISSN
024 7 _ |a 1750-2799
|2 ISSN
024 7 _ |a altmetric:180883213
|2 altmetric
037 _ _ |a DKFZ-2025-01826
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Lujumba, Ibra
|0 0000-0001-9937-1255
|b 0
245 _ _ |a A practical guide to identifying associations between tandem repeats and complex human traits using consensus genotypes from multiple tools.
260 _ _ |a Basingstoke
|c 2025
|b Nature Publishing Group
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1756819001_26696
|2 PUB:(DE-HGF)
|x Review Article
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a #LA:B330# / epub
520 _ _ |a Tandem repeats (TRs) are highly variable loci in the human genome that are linked to various human phenotypes. Accurate and reliable genotyping of TRs is important in understanding population TR variation dynamics and their effects in TR-trait association studies. In this protocol, we describe how to generate high-quality consensus TR genotypes for population genomics studies. In particular, we detail steps to: (i) perform TR genotyping from short-read whole-genome sequencing data by using the HipSTR, GangSTR, adVNTR and ExpansionHunter tools, (ii) perform quality control checks on TR genotypes by using TRTools and (iii) integrate TR genotypes from different tools by using EnsembleTR. We further discuss how to visualize and investigate TR variation patterns to identify population-specific expansions and perform TR-trait association analyses. We demonstrate the utility of these steps by analyzing a small dataset from the 1000 Genomes Project. In addition, we recapitulate a previously identified association between TR length and gene expression in the African population and provide a generalized discussion on TR analysis and its relevance to identifying complex traits. The expected time for installing the necessary software for each section is ~10 min. The expected run time on the user's desired dataset can vary from hours to days depending on factors such as the size of the data, input parameters and the capacity of the computing infrastructure.
536 _ _ |a 312 - Funktionelle und strukturelle Genomforschung (POF4-312)
|0 G:(DE-HGF)POF4-312
|c POF4-312
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
700 1 _ |a Adam, Yagoub
|0 0000-0001-6874-2543
|b 1
700 1 _ |a Ziaei Jam, Helyaneh
|b 2
700 1 _ |a Isewon, Itunuoluwa
|0 0000-0001-9653-8929
|b 3
700 1 _ |a Monnakgotla, Nomakhosazana
|b 4
700 1 _ |a Li, Yang
|0 0000-0001-5714-0416
|b 5
700 1 _ |a Onyido, Blessing
|b 6
700 1 _ |a Fredrick, Kakembo
|b 7
700 1 _ |a Adegoke, Faith
|0 0000-0003-3835-590X
|b 8
700 1 _ |a Emmanuel, Jerry
|b 9
700 1 _ |a Adeyemi, Jumoke
|0 0009-0008-0420-9502
|b 10
700 1 _ |a Ibitoye, Olajumoke
|0 0000-0001-8598-3584
|b 11
700 1 _ |a Owusu-Ansah, Samuel
|b 12
700 1 _ |a Akanle, Matthew Boladele
|b 13
700 1 _ |a Joseph, Habi
|0 0000-0001-6445-8721
|b 14
700 1 _ |a Nsubuga, Mike
|0 0009-0004-7668-3917
|b 15
700 1 _ |a Galiwango, Ronald
|0 0000-0002-5962-151X
|b 16
700 1 _ |a Okitwi, Martin
|0 0000-0003-2712-2174
|b 17
700 1 _ |a Magdalene, Namuswe
|b 18
700 1 _ |a Walter, Odur
|0 0009-0004-3818-4949
|b 19
700 1 _ |a Mngadi, Zama
|b 20
700 1 _ |a Adebiyi, Marion
|b 21
700 1 _ |a Oyelade, Jelili
|0 0000-0002-5476-4992
|b 22
700 1 _ |a Nel, Melissa
|0 0000-0002-9698-992X
|b 23
700 1 _ |a Jjingo, Daudi
|b 24
700 1 _ |a Gymrek, Melissa
|0 0000-0002-6086-3903
|b 25
700 1 _ |a Adebiyi, Ezekiel Femi
|0 P:(DE-He78)e66b15b8b7489783bf2775306fd04f0c
|b 26
|e Last author
|u dkfz
773 _ _ |a 10.1038/s41596-025-01231-y
|0 PERI:(DE-600)2244966-8
|p nn
|t Nature protocols
|v nn
|y 2025
|x 1754-2189
909 C O |o oai:inrepo02.dkfz.de:304286
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 26
|6 P:(DE-He78)e66b15b8b7489783bf2775306fd04f0c
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-312
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Funktionelle und strukturelle Genomforschung
|x 0
914 1 _ |y 2025
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2024-12-18
|w ger
915 _ _ |a DEAL Nature
|0 StatID:(DE-HGF)3003
|2 StatID
|d 2024-12-18
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2024-12-18
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-18
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b NAT PROTOC : 2022
|d 2024-12-18
915 _ _ |a IF >= 10
|0 StatID:(DE-HGF)9910
|2 StatID
|b NAT PROTOC : 2022
|d 2024-12-18
920 2 _ |0 I:(DE-He78)B330-20160331
|k B330
|l Angewandte Bioinformatik
|x 0
920 1 _ |0 I:(DE-He78)B330-20160331
|k B330
|l Angewandte Bioinformatik
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)B330-20160331
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21