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Complex genetic variation in nearly complete human genomes

Nature(2025)10.1038/s41586-025-09140-6Source: DataRank Database

Complex genetic variation in nearly complete human genomes is a dataset published in Nature (2025). On theSindex it has a DataRank of 0.862, placing it in the top 43.3% of the data-sharing corpus. It has been cited 67 times, with 50 citing works in its 1-hop citation network. Its calibrated FAIR score is 61/100.

Top 43%percentile
0.862DataRank
0.862Top 43%
Dataset Open Access67 citations · base score 3.7
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (median continuity of 130 Mb), closing 92% of all previous assembly gaps1,2 and reaching telomere-to-telomere status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8 and AMY1/AMY2, and fully resolve 1,852 complex structural variants. In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in α-satellite higher-order repeat array length and characterize the pattern of mobile element insertions into α-satellite higher-order repeat arrays. Although most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference3 to a median quality value of 45. Using this approach, 26,115 structural variants per individual are detected, substantially increasing the number of structural variants now amenable to downstream disease association studies.

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (1/2)
  • Open Access
Interoperable (0/2)
    Reusable (1/3)
    • Dataset classification

    FAIR checklist signals are shown for context only and do not affect DataRank scoring.

    61FAIR score
    F Findable
    78
    A Accessible
    80
    I Interoperable
    38
    R Reusable
    50
    Top 7% by FAIRLLM-assessed✓ full text read

    Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →

    DataRank Breakdown

    Base Score 64%Citation Network 36%

    Base Score Contribution

    0.553

    From this paper's citation signal

    Citation Network Contribution

    0.309

    From 15 citing papers with measurable signal

    Learn more about DataRank methodology →

    Top 5 citers driving the network score

    Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.

    1. The Sequence Alignment/Map format and SAMtools
      Bioinformatics200966,179 citationsDataRank 1.7
    2. MUSCLE: multiple sequence alignment with high accuracy and high throughput
      Nucleic Acids Research200446,160 citationsDataRank 1.6
    3. PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses
      The American Journal of Human Genetics200735,753 citationsDataRank 1.6
    Why this DataRank?

    DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 64% comes from its base citations and 36% from the citation network (15 citing papers contributed measurable signal).

    Base score B(p)
    log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
    Network N(p)
    Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
    Damping factor d = 0.85
    DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
    Self-citations excluded
    Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

    Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

    Read the full methodology →

    Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

    Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank

    Authors (67)

    Related Papers (5)

    Bioinformatics(2019)
    co-cited
    10.1093/bioinformatics/btz264
    Nucleic Acids Research(1999)
    co-cited
    10.1093/nar/27.2.573