Evidence map›Paper›PMID 31289836›Full record

ArticleGigaScience2019

Identifying, understanding, and correcting technical artifacts on the sex chromosomes in next-generation sequencing data.

Timothy H Webster, Madeline Couse, Bruno M Grande, Eric Karlins, Tanya N Phung, Phillip A Richmond, Whitney Whitford, Melissa A Wilson

Abstract read
In one paragraph

Article in GigaScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 1 pooled it
–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

64 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Observational
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  12. Sex Bias in Autoimmunity: New Findings and New Opportunities.JID innovations : skin science from molecules to population health · 2025
    Review
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4 more citing papers are in PubMed but not listed here.

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

8 authors.

Timothy H WebsterSchool of Life Sciences, Arizona State University, 427 E Tyler Mall, Tempe, AZ 85281, USA.
Madeline CouseUniversity of British Columbia, 2329 West Mall, Vancouver, BC, V6T 1Z4, Canada.
Bruno M GrandeDepartment of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada.
Eric KarlinsDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, MSC 9776, Bethesda, MD 20892, USA.
Tanya N PhungInterdepartmental Program in Bioinformatics, UCLA, 621 Charles E. Young Drive South, Los Angeles, CA 90095-1606, USA.
Phillip A RichmondBC Children's Hospital Research Institute, 950 W 28th Avenue, Vancouver, BC, V5Z 4H4, Canada.
Whitney WhitfordSchool of Biological Sciences, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.
Melissa A WilsonSchool of Life Sciences, Arizona State University, 427 E Tyler Mall, Tempe, AZ 85281, USA.

Funding

Population dynamics and medical consequences of sex chromosome evolutionR35GM124827 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI WILSON, MELISSA A · 2017 to 2024
$2.7M
NIGMS NIH HHS R35 GM124827
6 · The paper itself

Abstract

backgroundMammalian X and Y chromosomes share a common evolutionary origin and retain regions of high sequence similarity. Similar sequence content can confound the mapping of short next-generation sequencing reads to a reference genome. It is therefore possible that the presence of both sex chromosomes in a reference genome can cause technical artifacts in genomic data and affect downstream analyses and applications. Understanding this problem is critical for medical genomics and population genomic inference.

resultsHere, we characterize how sequence homology can affect analyses on the sex chromosomes and present XYalign, a new tool that (1) facilitates the inference of sex chromosome complement from next-generation sequencing data; (2) corrects erroneous read mapping on the sex chromosomes; and (3) tabulates and visualizes important metrics for quality control such as mapping quality, sequencing depth, and allele balance. We find that sequence homology affects read mapping on the sex chromosomes and this has downstream effects on variant calling. However, we show that XYalign can correct mismapping, resulting in more accurate variant calling. We also show how metrics output by XYalign can be used to identify XX and XY individuals across diverse sequencing experiments, including low- and high-coverage whole-genome sequencing, and exome sequencing. Finally, we discuss how the flexibility of the XYalign framework can be leveraged for other uses including the identification of aneuploidy on the autosomes. XYalign is available open source under the GNU General Public License (version 3).

conclusionsSex chromsome sequence homology causes the mismapping of short reads, which in turn affects downstream analyses. XYalign provides a reproducible framework to correct mismapping and improve variant calling on the sex chromsomes.

Indexed as

Sequence Homology, Nucleic AcidArtifactsChromosomes, Human, XChromosomes, Human, YContig MappingFemaleHigh-Throughput Nucleotide SequencingHumansMaleSequence AlignmentSequence Analysis, DNAaneuploidygenomicsmappingploidyvariant callingX chromosomeY chromosome

Identifiers

PMID31289836
PMCPMC6615978

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Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.