Evidence map›Paper›PMID 41861831›Full record

ArticleAmerican journal of human genetics2026

Best practices for improving alignment and variant calling on human sex chromosomes.

Angela M Taravella Oill, Seema B Plaisier, Tanya N Phung, Melissa A Wilson

Abstract read
In one paragraph

Article in American journal of human genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Angela M Taravella OillCenter for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA; School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA.
Seema B PlaisierCenter for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA; School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA; Comparative Genomics and Reproductive Health Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20852, USA.
Tanya N PhungCenter for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA; School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA.
Melissa A WilsonCenter for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA; School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA; Comparative Genomics and Reproductive Health Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20852, USA. Electronic address: melissa.wilson3@nih.gov.

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

Sex chromosome complement is the largest karyotypic variation observed in humans. X and Y chromosomes were once a pair of homologous autosomes. Although chromosome X and Y differentiated from one another, they still share high sequence similarity in some regions, such as the pseudoautosomal regions (PARs) and X-transposed region (XTR). The sex chromosomes violate some assumptions of autosomes but are not always processed separately in genomics. We undertook a simulation study to assess the effects of standard autosomal versus sex chromosome complement (SCC)-informed alignment, variant calling, and filtering strategies on variants detected on the sex chromosomes. We find that aligning samples to a reference genome informed by the SCC of the sample increases the number of true positives called in the PARs, and, in XX samples only, also the XTR. In contrast, in XY samples, masking the XTR during alignment results in a 10-fold higher rate of false positives (FPs). We further find that haploid calling on the sex chromosomes in XY samples reduces the number of FPs compared to diploid calling but does not decrease the number of false negatives. Improving the accuracy of variant calling results in detection of variants that could be relevant to studies of health and disease, including variants we recovered in genes implicated in cardiomyopathy, immunodeficiency, and Alzheimer disease. We recommend future genomic analyses implement the following best practices for detecting variants: aligning samples to versions of the human reference genome informed by the SCC of the sample and using accurate ploidy when calling variants.

Indexed as

Chromosomes, Human, XChromosomes, Human, YGenetic VariationSequence AlignmentSex ChromosomesFemaleGenome, HumanHumansMalealignmentfalse positivesex chromosomessimulationtrue positivevariant callingvariant filteringVCFX chromosomeY chromosome

Identifiers

PMID41861831
PMCPMC13087457

What Socratic holds

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Registered trials

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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 Socratic graph.