Searching journal content for articles similar to Ball et al. 34 (1): 145.

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  1. ...are needed in order to properly capture the genetic composition of populations. Here, we explore deep learning techniques, namely, variational autoencoders (VAEs), to process genomic data from a population perspective. We show the power of VAEs for a variety of tasks relating to the interpretation...
  2. ...-ε’s univariate clustering (Cheng et al. 2020) to a multivariate scenario and using an infinite mixture model solved by variational inference, our method enables the exploration of complex multitrait association patterns. Our method aggregates SNP-level effects and association clustering results at the gene level...
  3. ...annotation databases offer limited functional insights for sSNVs. Here, we present SynMall, a comprehensive resource designed to decipher the functional impact of synonymous variation. SynMall catalogs 25 million potential human sSNVs and integrates evolutionary and population information of sSNVs from 45...
  4. ...are proposed to achieve robust interomics embedding alignment and to preserve the variation in original omics features (referred as intraomics alignment). We compare scSHEFT with scNym (Kimmel and Kelley 2021), Portal (Zhao et al. 2022), Concerto (Yang et al. 2022), scGCN (Song et al. 2021), Seurat (Hao et al...
  5. ...read-level copy number and motif composition data for STR loci, whereas many other methods do not, enabling analysis of intra-allele variation in STR copy number and motif composition. The approach fills a niche in the STR genotyping software ecosystem and opens up new possibilities for association...
  6. ...-nucleotide variations (SNVs) are, however, much harder to identify with low sequencing depth due to sequencing errors. Here, we present Nanopore Rolling Circle Amplification (RCA)-enhanced Consensus Sequencing (NanoRCS), which leverages RCA and consensus calling based on -wide long-read nanopore sequencing to enable...
  7. ...variants, which constitute the primary data used for inferring cell lineage trees. The primary class of genomic variants studied in this paper is the single nucleotide variant (SNV). We do not consider more complex variants such as copy number variations (CNVs) for cell lineage tree inference (see...
  8. ...genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associated variants. Here, we used a highly controlled system of F1 crosses with extensive genetic diversity to profile allele-specific binding of four TFs at several time points...
  9. ...-Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing 100051, China; 6Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana 46202, USA; 7Victorian Clinical Genetics Service, Royal Children's Hospital and Department of Pediatrics...
  10. ...Optical mapping enables accurate testing of large repeat expansions Bart van der Sanden1, Kornelia Neveling1, Syukri Shukor2, Michael D. Gallagher2, Joyce Lee2, Stephanie L. Burke2, Maartje Pennings1, Ronald van Beek1, Michiel Oorsprong1, Ellen Kater-Baats1, Eveline Kamping1, Alide A. Tieleman3...
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