@sbarnettARK Epigenomic biomarkers are becoming more established for #LiquidBiopsy and #CancerScreening, and we have seen the big players positioning themselves in this #epigenomics race recently.

Catching signs of #cancer early is crucially important to the disease management and survival rates, so the question is: how can we find out if there is something wrong going on early enough?

The first generation of high-throughput technologies was predicated on finding mutated (tumor) DNA in the individual's body (somatic), different from their (normal) DNA. Tumor/Normal (T/N) comparisons of the individual's samples, biopsies or ctDNA will indicate if there

are signs of cancer already underway. So why do we need #epigenomic profiling if we can do all this with the detection of mutations? Well, the argument is that if you can see sufficient mutated copies of DNA, cancer may already have progressed beyond the initial stages.

Then people asked the question: is there an earlier mark that we can detect for earlier stages of cancer before the Tumor/Normal mutations signal amps up? Here is where #epigenomics profiling took hold.

#JPM2021 @GenapSys My Highlights: I think it's fair to say I am more excited than most about this #NGS company, as I see them as an example of how to enter the market while keeping a small profile ($249M raised so far).

They now are aiming at 2021 to ship two new chips: 50MM read chip and 144MM sensor chip (not sure what the difference is between read/sensor).

They show a slide of price per Gb with #Illumina products as a reference, and their products now lined up, I think, for the first time with price per Gb info. Lowest will be the 144MM chip at ~$27/Gb.

As their technology is closer to the #IonTorrent than to the cycle-by-cycle SBS-based sequencing methods, they should have microindel errors in their profile. These look much better, almost null, than the S5 data they show in comparison.

The next slide, also about error rates, either for each base as the run progresses or sliced in GC% windows, has a lot of info, but difficult to read. I think the summary is that the @Genapsys profile shows a bit of microindel error but otherwise comparable to 100bp ILMN data.