Evidence map›Paper›PMID 33750289›Full record

ArticleBMC bioinformatics2021

Y-LineageTracker: a high-throughput analysis framework for Y-chromosomal next-generation sequencing data.

Hao Chen, Yan Lu, Dongsheng Lu, Shuhua Xu

Abstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

45 citing papers in PubMed.

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  3. High-coverage ancient genomes reveal divergent population histories and prehistoric starch-related genetic variation in Japan.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  18. A draft UAE-based Arab pangenome reference.Nature communications · 2025
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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

4 authors.

Hao Chen *Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
Yan Lu *Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
Dongsheng LuKey Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
Shuhua XuKey Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China. xushua@picb.ac.cn.ORCID http://orcid.org/0000-0002-1975-1002

Funding

Key Research Program of Frontier Sciences of the Chinese Academy of Sciences QYZDJ-SSW-SYS009National Natural Science Foundation of China 31525014National Natural Science Foundation of China 31771388National Natural Science Foundation of China 31961130380National Natural Science Foundation of China 32030020National Natural Science Foundation of China 32041008Science and Technology Commission of Shanghai Municipality 2017SHZDZX01Strategic Priority Research Program of the Chinese Academy of Sciences XDB38000000
6 · The paper itself

Abstract

backgroundY-chromosome DNA (Y-DNA) has been used for tracing paternal lineages and offers a clear path from an individual to a known, or likely, direct paternal ancestor. The advance of next-generation sequencing (NGS) technologies increasingly improves the resolution of the non-recombining region of the Y-chromosome (NRY). However, a lack of suitable computer tools prevents the use of NGS data from the Y-DNA studies.

resultsWe developed Y-LineageTracker, a high-throughput analysis framework that not only utilizes state-of-the-art methodologies to automatically determine NRY haplogroups and identify microsatellite variants of Y-chromosome on a fine scale, but also optimizes comprehensive Y-DNA analysis methods for NGS data. Notably, Y-LineageTracker integrates the NRY haplogroup and Y-STR analysis modules with recognized strategies to robustly suggest an interpretation for paternal genetics and evolution. NRY haplogroup module mainly covers haplogroup classification, clustering analysis, phylogeny construction, and divergence time estimation of NRY haplogroups, and Y-STR module mainly includes Y-STR genotyping, statistical calculation, network analysis, and estimation of time to the most recent common ancestor (TMRCA) based on Y-STR haplotypes. Performance comparison indicated that Y-LineageTracker outperformed existing Y-DNA analysis tools for the high performance and satisfactory visualization effect.

conclusionsY-LineageTracker is an open-source and user-friendly command-line tool that provide multiple functions to efficiently analyze Y-DNA from NGS data at both Y-SNP and Y-STR level. Additionally, Y-LineageTracker supports various formats of input data and produces high-quality figures suitable for publication. Y-LineageTracker is coded with Python3 and supports Windows, Linux, and macOS platforms, and can be installed manually or via the Python Package Index (PyPI). The source code, examples, and manual of Y-LineageTracker are freely available at https://www.picb.ac.cn/PGG/resource.php or CodeOcean ( https://codeocean.com/capsule/7424381/tree ).

Indexed as

Chromosomes, Human, YHigh-Throughput Nucleotide SequencingPolymorphism, Single NucleotideGenetics, PopulationHaplotypesHumansMicrosatellite RepeatsNGSNRY haplogroupPopulation geneticsY-chromosome DNAY-STR

Identifiers

PMID33750289
PMCPMC7941695

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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.