We are working with a novel plant transcriptome (no reference genome). After annotating the assembly, will removing irrelevant contigs effect read mapping statistics, in a good way, when we perform RNA-Seq analysis? Many of our contigs annotate as retrotransposons, bacterial/viral contaminants (metagenomic leftovers), or have no match to any annotated proteins in public databases. I assume contaminants should be removed, but what about genes of no interest to our research (e.g. transposable elements)? Will our results be more accurate if the our transcriptome only contains known and relevant protein coding contigs?
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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 -
Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.
We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing...