Bioinformatics articles within Nature Genetics

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  • Technical Report
    | Open Access

    MuSiCal is a mutational signature analysis tool combining minimum-volume nonnegative matrix factorization with other algorithmic innovations. Applied to PCAWG data, MuSiCal gives more accurate results, including resolving ambiguous flat signatures.

    • Hu Jin
    • , Doga C. Gulhan
    •  & Peter J. Park

  • Article
    | Open Access

    ancIBD identifies identity-by-descent regions in ancient DNA using a hidden Markov model optimized for these low-coverage data. Analysis of 4,248 individuals demonstrates that ancIBD can identify up to sixth-degree relatives and provides genealogical insights into ancient populations.

    • Harald Ringbauer
    • , Yilei Huang
    •  & David Reich

  • Article
    | Open Access

    A modified framework leveraging a protein language model (ESM1b) is used to predict all possible 450 million missense variant effects in the human genome and shows potential for generalizing to more complex genetic variations such as indels and stop-gains.

    • Nadav Brandes
    • , Grant Goldman
    •  & Vasilis Ntranos

  • Technical Report |

    Linked-read analysis is a method for analyzing single-cell DNA-sequencing data that accurately identifies somatic single-nucleotide variants by using read-level phasing with nearby germline variants, enabling the characterization of mutational signatures and estimation of somatic mutation rates in single cells.

    • Craig L. Bohrson
    • , Alison R. Barton
    •  & Peter J. Park

  • Article |

    David Page and colleagues report the sequence of the chicken W sex chromosome and compare ancestral W-linked genes across bird species. They find that the W chromosome did not acquire genes expressed exclusively in reproductive tissue, but retained genes through selection to maintain appropriate dosage levels of broadly expressed genes.

    • Daniel W Bellott
    • , Helen Skaletsky
    •  & David C Page

  • News & Views |

    Pancreatic cancers consist of a heterogeneous amalgam of assorted cell types, making it challenging to develop a classification system that groups these tumors according to common molecular features. A new study tackles this important issue using bioinformatics approaches to decipher gene expression signatures derived specifically from either tumor cells or nonmalignant stromal cells that predict patient outcome and may inform personalized treatments.

    • Filippos Kottakis
    •  & Nabeel Bardeesy

  • News & Views |

    A major challenge in human genetics is pinpointing which non-coding genetic variants affect gene expression and disease risk. A new study in this issue describes a broadly applicable approach for this task that explicitly models cell type–specific regulatory motifs and generates variant effect predictions that are more accurate and interpretable than those of alternative tools.

    • Martin Kircher
    •  & Jay Shendure

  • Article |

    Nadav Ahituv and colleagues use a massively parallel reporter assay to test 4,970 synthetic regulatory element sequences, containing patterns of 12 known liver transcription factor binding sites, in mice and in HepG2 cells. They systematically test the impact of binding site copy number, spacing, combination and order on gene expression.

    • Robin P Smith
    • , Leila Taher
    •  & Nadav Ahituv

  • Article |

    Simon Harris and colleagues report whole-genome sequencing of 36 Chlamydia trachomatis representative strains from temporally and geographically diverse sources and use this to construct a genome-wide phylogeny of the species. They find that epidemic spread can be driven by clonal expansion from a single source and also report evidence for recombination in recent clinical strains both within and between biovars.

    • Simon R Harris
    • , Ian N Clarke
    •  & Nicholas R Thomson

  • News & Views |

    Diversification and specialization of high-throughput technologies demand assay-specific treatment of data for reliable interpretation. A new study shows that data generated using the Hi-C approach contain hidden features of interchromosomal DNA interactions, which are revealed through analysis with an integrated probabilistic model that corrects for multiple sources of bias in the data.

    • Myong-Hee Sung
    •  & Gordon L Hager

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