Searching journal content for articles similar to Zhang et al. 35 (12): 2781.

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  1. Method: High-fidelity, large-scale targeted profiling of microsatellites
    • Caitlin A. Loh,
    • Danielle A. Shields,
    • Adam Schwing,
    • and Gilad D. Evrony
    Genome Res. July 2024 34: 1008-1026; Published in Advance July 16, 2024, doi:10.1101/gr.278785.123
    ...tools enables high-fidelity, large-scale profiling of microsatellites, which may find utility in diverse applications such as lineage tracing, population genetics, ecology, and forensics.Microsatellites, also known as short tandem repeats, are genomic sequences composed of tandem repeats of short (1...
  2. Method: Secure discovery of genetic relatives across large-scale and distributed genomic data sets
    • Matthew M. Hong,
    • David Froelicher,
    • Ricky Magner,
    • Victoria Popic,
    • Bonnie Berger,
    • and Hyunghoon Cho
    Genome Res. September 2024 34: 1312-1323; Published in Advance August 7, 2024, doi:10.1101/gr.279057.124
    ...-Relate on the UK Biobank and All of Us data sets. On a data set of 200,000 individuals split between two parties, SF-Relate detects 97% of third-degree or closer relatives within 15 h of runtime. Our work enables secure identification of relatives across large-scale genomic data sets.Collaborative studies that aim...
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  3. Method: Pangenome-based genome inference using integer programming
    • Ghanshyam Chandra,
    • Md Helal Hossen,
    • Stephan Scholz,
    • Alexander T. Dilthey,
    • Daniel Gibney,
    • and Chirag Jain
    Genome Res. December 2025 35: 2661-2670; Published in Advance August 21, 2025, doi:10.1101/gr.280567.125
    ...relevant to the target using a k-mer-based greedy heuristic (Sirén et al. 2024).Low-coverage sequencing, combined with genotyping and phasing, is a cost-effective approach to conduct large-scale genetic studies (Davies et al. 2021; Li et al. 2021; Martin et al. 2021; Rubinacci et al. 2021). In this paper...
  4. Research: Large-scale investigation of species-specific orphan genes in the human gut microbiome elucidates their evolutionary origins
    • Nikolaos Vakirlis and
    • Anne Kupczok
    Genome Res. June 2024 34: 888-903; Published in Advance July 8, 2024, doi:10.1101/gr.278977.124
    ...: In this window In a new window Figure 2. Large scale-identification of species-specific orphan genes (SSOGs) in the human gut microbiome. (A) The main steps of the computational workflow of similarity searches. (B) Distribution of the SSOG proportion in a given species’ pan. The red dashed line denotes...
  5. Mini-Review: Large-scale genomic analysis of the domestic dog informs biological discovery
    • Reuben M. Buckley and
    • Elaine A. Ostrander
    Genome Res. June 2024 34: 811-821; Published in Advance July 2, 2024, doi:10.1101/gr.278569.123
    ..., morphology, and disease susceptibility. We explore the limitations of current data sets for variant interpretation, tradeoffs between sequencing strategies, and the burgeoning role of long-read s for capturing structural variants. In addition, we consider how large-scale collections of whole- sequence data...
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  6. Method: High-resolution genotype-free mapping of genetic variation with CRI-SPA-Map
    • Sheila Lutz,
    • Megan Lawler,
    • Samuel Amidon,
    • and Frank W Albert
    Genome Res. March 23, 2026 gr.281514.125; Published in Advance March 23, 2026, doi:10.1101/gr.281514.125
    ...the genomic outcomes of CRI-SPA-Map engineering, we whole- sequenced 185 555 CRI-SPA-Map isolates (typically four local and two distal isolates; Supplemental Table S2) 186 created from the 92 YKO strains. We analyzed genotype calls at 8,257 high-quality variants 187 across the (7,954 SNVs and 303 indels...
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  7. Method: Fast and accurate out-of-core PCA framework for large scale biobank data
    • Zilong Li,
    • Jonas Meisner,
    • and Anders Albrechtsen
    Genome Res. September 2023 33: 1599-1608; Published in Advance August 24, 2023, doi:10.1101/gr.277525.122
    ...a window-based optimization scheme that enables accelerated convergence while improving the accuracy. Additionally, PCAone incorporates out-of-core and multithreaded implementations for the existing Implicitly Restarted Arnoldi Method (IRAM) and RSVD. Through comprehensive evaluations using multiple large-scale...
  8. Method: Large-scale detection and characterization of inter-chromosomal rearrangements in normozoospermic bulls using massive genotype and phenotype data sets
    • Jeanlin Jourdain,
    • Harmonie Barasc,
    • Thomas Faraut,
    • Anne Calgaro,
    • Nathalie Bonnet,
    • Camille Marcuzzo,
    • Amandine Suin,
    • Anne Barbat,
    • Chris Hozé,
    • Florian Besnard,
    • Sébastien Taussat,
    • Cécile Grohs,
    • Claire Kuchly,
    • Carole Iampietro,
    • Cécile Donnadieu,
    • Alain Pinton,
    • Didier Boichard,
    • and Aurélien Capitan
    Genome Res. July 6, 2023 ; Published in Advance July 6, 2023, doi:10.1101/gr.277787.123
    ...Large-scale detection and characterization of interchromosomal rearrangements in normozoospermic bulls using massive genotype and phenotype data sets Jeanlin Jourdain,1,2 Harmonie Barasc,3 Thomas Faraut,3 Anne Calgaro,3 Nathalie Bonnet,3 Camille Marcuzzo,4 Amandine Suin,4 Anne Barbat,2 Chris Hozé,1...
  9. Method: Robust and efficient annotation of cell states through gene signature scoring
    • Laure Ciernik,
    • Agnieszka Kraft,
    • Florian Barkmann,
    • Josephine Yates,
    • and Valentina Boeva
    Genome Res. March 2026 36: 630-644; Published in Advance February 18, 2026, doi:10.1101/gr.280926.125
    ...score ranges. Although other Tirosh-based methods showed high information quantity, they suffered from large-scale imbalances, likely owing to biased control gene selection and lack of score normalization.It is important to emphasize that gene signature scoring is only as reliable as the provided...
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  10. Research: Genotype imputation from low-coverage data for medical and population genetic analyses
    • Simone Andrea Biagini,
    • Sara Becelaere,
    • Mio Aerden,
    • Tatjana Jatsenko,
    • Laurens Hannes,
    • Philip Van Damme,
    • Jeroen Breckpot,
    • Koenraad Devriendt,
    • Bernard Thienpont,
    • Joris Robert Vermeesch,
    • Isabelle Cleynen,
    • and Toomas Kivisild
    Genome Res. September 2025 35: 1929-1941; Published in Advance July 22, 2025, doi:10.1101/gr.280175.124
    ...to the genotype called from the high coverage data. This motivated us to carry out systematic revisions of conflicts between the GT and GP values, which could be characteristic only for ultralow coverage data, and to focus our search for optimal solutions in the GDI design on the combination of INFO score, GP...
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