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The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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http://dx.doi.org/10.1089/cmb.2012.0021 | DOI Listing |
Sci Adv
September 2025
Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
Breastfeeding is essential for reducing infant morbidity and mortality, yet exclusive breastfeeding rates remain low, often because of insufficient milk production. The molecular causes of low milk production are not well understood. Fresh milk samples from 30 lactating individuals, classified by milk production levels across postpartum stages, were analyzed using genomic and microbiome techniques.
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September 2025
Department of Cell & Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Somatic mitochondrial DNA (mtDNA) mutations are frequently observed in tumors, yet their role in pediatric cancers remains poorly understood. The heteroplasmic nature of mtDNA-where mutant and wild-type mtDNA coexist-complicates efforts to define its contribution to disease progression. In this study, bulk whole-genome sequencing of 637 matched tumor-normal samples from the Pediatric Cancer Genome Project revealed an enrichment of functionally impactful mtDNA variants in specific pediatric leukemia subtypes.
View Article and Find Full Text PDFBioinformatics
September 2025
Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
Motivation: RNA velocity has become a powerful tool for uncovering transcriptional dynamics in snapshot single-cell data. However, current RNA velocity approaches often assume constant transcriptional rates and treat genes independently with gene-specific times, which may introduce biases and deviate from biological realities. Here, we present InterVelo, a novel deep learning framework that simultaneously learns cellular pseudotime and RNA velocity.
View Article and Find Full Text PDFMol Omics
September 2025
Laboratory of Structural Bioinformatics and Computational Biology, Federal University of Rio Grande do Sul, Av. Bento Gonçalves, 9500, Porto Alegre 91501-970, RS, Brazil.
The integration of multimodal single-cell omics data is a state-of-art strategy for deciphering cellular heterogeneity and gene regulatory mechanisms. Recent advances in single-cell technologies have enabled the comprehensive characterization of cellular states and their interactions. However, integrating these high-dimensional and heterogeneous datasets poses significant computational challenges, including batch effects, sparsity, and modality alignment.
View Article and Find Full Text PDFIEEE Trans Comput Biol Bioinform
September 2025
The rapid advancement of single-cell sequencing technology has generated vast amounts of multi-omics data, presenting unprecedented opportunities for single-cell multi-omics clustering analysis. However, existing single-cell clustering algorithms focus on extracting shared representations, overlooking the interactions and correlations among cells. This oversight inevitably leads to biased or confounded cell clustering results.
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