I would like to phase whole-genome datasets, some of which are single-end read datasets and some of which are paired-end datasets. Does anyone have experience with this? Should I simply generate a list of SNPs and feed it to existing phasing algorithms? Is there software that can take the raw read data into account (IE SNPs that appear on the same read)?
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NGS has revolutionized clinical microbiology by offering new ways to identify and surveil pathogens without prior knowledge of the target. One popular approach is 16S rRNA and ITS amplicon sequencing, which targets specific microbial markers. But studies are increasingly incorporating shotgun metagenomics, a technique that sequences all DNA from a sample without targeting specific microbial markers. This approach allows more detailed taxonomic classification,...10-30-2026, 06:46 AM -
Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?
Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating...10-14-2026, 09:55 AM
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