#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.
The error profile starts low, very low actually, and then it hikes up after cycle 50-100+. In the slide below, they've been naughty and put a textbox on top of their error blue line, trying to hide it: don't think we won't notice these tricks! 😉
They say they've placed or booked more than 110 instruments so far (does that count early access?). All this is based on a 10K GS111 Sequencer + 10K Sequencing Prep instrument. They show long term plans for a GENIUSPrep (high throughput sample prep), but also ...
... but also bigger chips (500MM / 1000MM chip), as well as an Integrated System (zoom in).
Details of the 50M Chip. They seem to have gone from 100bp to 150bp standard now, but raw accuracy still placed at 99.9% at position 125bp. This may be the actual 144M chip but with standard Poisson loading, rendering a bit over 50M reads, or 8Gb per run, which is impressive...
... with a $20K capital investment, comparing the 50M @Genapsys at 8Gb ($54/Gb) and the #Illumina#iSeq100 at 1.2Gb ($542/Gb), that's roughly 8x better yield for Genapsys, and 10x better price per Gb. It makes the #iSeq100 look rather underwhelming in comparison.
The slide about 2021 plans changes the naming from 144M chip to "G4-50M and G4-100M", so this could mean that the nomenclature changes to reads per run rather than the size of the chip. Maybe both based on the 144M chip, but with better loading giving the 50M->100M jump in reads?
No reference to paired-end reads, only indications that 150bp may not be the end of it, and they may be able to go longer than that. Good news about the G4-100M, as it seems they have scope of improvement in loading.
Bonus picture of a "Personalize Genomics!" lab, or lab-at-home.
#JPM2021#BiologicalDynamics@BiodynSD My Highlights: I'll cover this from the point of view of #LiquidBiopsy and #Epigenomics profiling, which is where my interest lies: their next-gen multiomics intro is about exosomes (and EVs, exosomal vesicles?)
The slide about Verita Biomarker Isolation Platform seems to be about isolating cells, with the right-most image showing "Visualized EV", which I presume is exosome vesicles
Later on, they do mention methylation markers, above the exosomes image, so I wonder if it's only DNA inside or bound to the exosomes?
#JPM2021#ExactSciences#LiquidBiopsy My highlights: I will focus on the liquid biopsy / #epigenomics profiling side of the presentation, which is where my interest lies: Exact described the data from Thrive multi-cancer screening, based on 'mutation+protein'
The details they gave on their other recent acquisition, #BaseGenomics are illuminating: they will use their bisulfite-free methylation profiling method for their Cologuard 2.0 test for CRC, but also for the multi-cancer test, and possibly the MRD test as well.
So this means that #ExactSciences intend to upgrade their tech in two steps: from current Cologuard 1.0 to a new test that includes Thrive's tech, and then a second upgrade using the #BaseGenomics#Epigenomics profiling tech.
Some stats and facts about the #Takifugu#rubripes assembly by @genomeark: this is the third iteration of the assembly. The first was completed in 2002. There was another iteration done in 2011. Why was the pufferfish sequenced so early? A lot has got to do with Sydney Brenner...
Indeed, as we can see in this archived version of @ensembl, the Fugu genome was the 5th vertebrate genome to be completed, after human/mouse/rat and zebrafish. Even though zebrafish is widely used as a model organism, Sydney Brenner argued that Fugu was worth sequencing ...
... The reason is that Sydney Brenner was passionate (obsessed?) with gene duplications and functional diversification. I.e. a gene duplicates in two copies, and over time, each copy can specialize in doing something slightly different. ...
#JPM2021@TwistBioscience My Highlights: back to the #DNAWrite field. TwistBio chip: 1M oligos but only as centralised factory setting.
Expanding to a new factory in Portland (roadmap 2022) to reduce TAT. Also mentioned the "long tail" of Clonal Ready Gene Fragments.
They have a few slides on #DNAasStorage with a denser chip in prototype phase where they think they can archive 1Tb for $100 (pay once, archive forever*) which, if my calculations are correct, would allow for 10-12 years of @awscloud Deep Glacier or similar mth/GB=0.00099*12*1E3
#JPM2021#LiquidBiopsy notable by their absence, which is more than excusable in these pandemic times: @freenome, Biocartis, Biodesix, Epic Sciences, ArcherDx (not by this name anyway). Worth following developments for them. In my book, worth following #Freenome of the ones here.
Smaller #LiquidBiopsy#Oncology#Diagnostics players also not at #JPM2021 but important in the field: Personalis, Inivata, Exosome Diagnostics, Epigenomics Ag, Personal Genome Diagnostics, Foundation Medicine, Singlera, Cambridge Epigenetix, and Bluestar Genomics.
Their T-Detect method is aiming at #MRD monitoring, here shown in a slide that relates it to their ImmunoSEQ T-MAP Cancer mapping tool, and their Identification of clinical TCR candidates.
They stress the T-cell Diagnostics angle in different slides. I recall only @freenome explicitly mentioning immune-profiling from the group of companies in early cancer diagnostics and #epigenomics profiling (Grail/GH/Thrive/Freenome/BioStar/CEGX/etc.)