Our lab is performing single cell RNAseq and mapping the reads back to an existing genome. We are running paired-end sequencing on a NextSeq 500 to analyze differential expression patterns between cell types. I am having difficulty deciding how narrow a range to size select for (using Pippin Prep) after adding adapter sequences. I am aware that tighter size selection reduces bias during bridge amplification, and that the bioinformatics are typically happier with narrower size ranges, but I want to make sure that my size distribution is broad enough to capture a representative sample. What size ranges are people using in their research? Do people feel that selecting transcripts in the 250-300 bp size range would be representative, or should I go tighter/broader? My Covaris sheared libraries currently span 50-1000 bp with the peaks around 300 bp. Any feedback is greatly appreciated!
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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