I've just finished my first shot at assembling a metagenome sample derived from a marine environment using Velvet, VelvetOptimizer and Metavelvet. Running the assembly with the recommendations from VelvetOptimizer (kmer size of 31), I was getting very short contigs ~100-400 bp. Increasing the kmer size beyond this to 37 resulted in longer contigs 100-3K. When I started analyzing the coverage and reads for several contigs, I noticed that some short contigs i.e. 90bp had about 10K reads and a coverage of 20X for example. Some of the longer contigs 1K or 2K had less reads (200) and lower coverage. My question is if there are certain steps I can take now to filter out contigs that might not be useful in the annotation step for example, or that could be chimeric? I'm not sure how to further proceed. Before I try using a different assembler I'd like to understand how these results could be further analyzed before proceeding to the annotation step.
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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, detection...Today, 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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