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Biology subjects

Javaid, H.

Publications and source records attributed to Javaid, H..

3 recordsLinked to original sources

Open-source, Hardware-Independent GPU Acceleration for Scalable Nanopore Basecalling with Slorado and Openfish

Nanopore sequencing technologies are used widely in genomics research and their adoption continues to accelerate. 'Basecalling' is an essential step in the nanopore sequencing workflow, during which raw electrical signals are translated into nucleotide sequences. The current state-of-the-art basecaller, Oxford Nanopore Technologies (ONT) software 'Dorado,' relies on proprietary, platform-specific NVIDIA GPU optimisations bundled in the closed-source 'Koi' library. As a result, practical, high-speed basecalling is effectively restricted to a narrow class of supported hardware, limiting accessibility, portability, and innovation. We present (1) 'Openfish,' an open-source GPU-accelerated nanopore basecaller decoding library that provides a competitive alternative to ONT's proprietary Koi library; and (2) Slorado, a fully open-source basecalling framework that supports both DNA and RNA with equivalent accuracy to Dorado. Together, Openfish and Slorado remove the hardware lock-in that currently limits high-performance nanopore basecalling. Our framework scales efficiently across heterogeneous computing environments, from low-power embedded devices to GPU-equipped datacenters, without sacrificing speed or accuracy. Openfish and Slorado are available as free open-source packages for basecalling research, optimisation and deployment beyond the constraints of proprietary software and hardware ecosystems: Openfish: https://github.com/warp9seq/openfish, Slorado: https://github.com/BonsonW/slorado.

bioinformatics↗

A novel framework to build saliva-based DNA methylation biomarkers: quantifying systemic chronic inflammation as a case study

Accessible and non-invasive biomarkers that measure human ageing processes and the risk of developing age-related disease are paramount in preventative healthcare. In this study, we describe a novel framework to train saliva-based DNA methylation (DNAm) biomarkers that are reproducible and biologically interpretable. By leveraging a reliability dataset with replicates across tissues, we demonstrate that it is possible to transfer knowledge from blood DNAm data to saliva DNAm data using DNAm proxies of blood proteins (EpiScores). We then apply these methods to create a new saliva-based epigenetic clock (InflammAge) that quantifies systemic chronic inflammation (SCI) in humans. Using a large blood DNAm human cohort with linked electronic health records and over 18,000 individuals (Generation Scotland), we demonstrate that InflammAge significantly associates with all-cause mortality, disease outcomes, lifestyle factors and immunosenescence; in many cases outperforming the widely used SCI biomarker C-reactive protein (CRP). We propose that our biomarker discovery framework and InflammAge will be useful to improve our understanding of the molecular mechanisms underpinning human ageing and to assess the impact of gero-protective interventions.

bioinformatics↗

A spatially resolved single cell genomic atlas of the adult human breast

The adult human breast comprises an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue. While previous studies have mainly focused on the breast epithelial system, many of the non-epithelial cell types remain understudied. Here, we constructed a comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics data profiled 535,941 cells from 62 women, and 120,024 nuclei from 20 women, identifying 11 major cell types and 53 cell states. These data revealed abundant pericyte, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Our spatial mapping using three technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells in the ducts and lobules, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide an unprecedented reference of adult normal breast tissue for studying mammary biology and disease states such as breast cancer.

genomics↗