Prasun Dutta
@prasundutta87
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Bioinformatician at @HumanGeneticsOx (@NDMOxford,@UniofOxford),Computational Genomics scientist, @EdinburghUni alumni (MSc,PhD)
Oxford, Edinburgh, Reading
Joined February 2014
If you’d like to dive deeper into this work and explore the details, you can read the full preprint here. I’d be glad to hear your thoughts and feedback.
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All raw & processed data are shared via the Genomics England Research Environment to accelerate future novel disease gene discovery. Thanks to all who contributed to this work!.
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🔹 Pathogenic/Likely pathogenic de novo SVs discovered in/near DLX5/6, AUTS2, FN1. 🔹 Diagnostic odyssey resolved for at least 2 families.
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Key highlights:. 🔹 60,022 structural variants (SVs) detected. 🔹 minimap2+sniffles2 found to be optimal for family-based SV calling. 🔹 ~400 variants were prioritised using a custom structural variant calling and prioritisation bioinformatics pipeline.
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Excited to share our latest preprint from the Scottish Genomes Partnership (SGP)! In SGP, Oxford Nanopore long-read whole genome sequencing was applied to 24 undiagnosed rare-disease families:. MedRxiv Preprint-
medrxiv.org
Background Whole-genome sequencing (WGS) projects for rare disease diagnosis typically yield a diagnostic rate of approximately 25-40%, dependent particularly on patient selection and the extent of...
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RT @HaoYin20: tidyplots. Time to say goodbye to ggplot2?🫡. "a significant reduction of code complexity" vs ggplot2. .
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RT @marianattestad: Investigating structural variants? I just released a tutorial video showing how I do this quickly and intuitively using….
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RT @tallphil: It's in! You can now hit "Browse libraries" in @excalidraw and find a bunch of icons for drawing @nextflowio / @nf_core / @Mu….
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RT @EtienneSollier: Figeno, my visualization tool for genomics🎨🧬, is now published in Bioinformatics! .It can gener….
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RT @AJHGNews: 📢New from @alistairp2011 & colleagues.📰The impact of inversions across 33,924 families with rare disease from a national geno….
cell.com
By analyzing genome sequencing data for 33,924 families from a heterogeneous rare-disease cohort, Pagnamenta et al. identified 45 families where inversions likely explain the etiology. In six...
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RT @tallphil: This is big. Grab an image with any combination of tools, available as Docker & Singularity (native) and linux/amd64 & arm64….
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RT @tuuliel_lab: We’re recruiting for multiple positions in my lab in New York and Stockholm, at MSc and PhD levels. If you’re interested i….
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RT @razoralign: VCF2PCACluster: a simple, fast and memory-efficient tool for principal component analysis of tens of millions of SNPs https….
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RT @MazdakS: Train PhD students to be thinkers not just specialists
nature.com
Nature - Many doctoral curricula aim to produce narrowly focused researchers rather than critical thinkers. That can and must change, says Gundula Bosch.
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RT @sproul_lab: Help us understand how DNA methylation patterns are regulated at the single-molecule level using @nanopore sequencing. PhD….
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RT @tangming2005: The CUT&RUN suspect list of problematic regions of the genome | Genome Biology | Full Text
genomebiology.biomedcentral.com
Background Cleavage Under Targets and Release Using Nuclease (CUT&RUN) is an increasingly popular technique to map genome-wide binding profiles of histone modifications, transcription factors, and...
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RT @jsantoyo: ggcoverage: an R package to visualize and annotate genome coverage for various NGS data #GenomeCoverage #NGS @BMCBioinfo .htt….
bmcbioinformatics.biomedcentral.com
Background Visualizing genome coverage is of vital importance to inspect and interpret various next-generation sequencing (NGS) data. Besides genome coverage, genome annotations are also crucial in...
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