In #JPM2023 news, $PACB PacBio presented on January 11, 2023. Christian Henry, President and CEO announcing that Revio already has 76 orders in the books.
PacBio has already sold more than 1,000 sequencers. I wonder given the turnaround of the technology, if that makes it the biggest NGS company in turn-around of their instruments.
Basic slide explaining how long-read HiFi works, and the Omniome short-read SBB sequencing technology for Q40+ read quality.
A slide describing the different fields and how long-reads and short-reads play different roles in each of them. I wonder how much $ILMN Illumina would have liked to be in this position today: having succeeded in acquiring PacBio HiFi technology as a complement to SBS.
The company has 512 Sequel II/IIe instruments installed, which they will quickly be replaced by the Revio instrument, which has much higher throughput and favourable price per Gb.
An interesting slide that details some partners in the Revio instrument: Corteva for automated ways to prepare the sample for long-read sequencing. Also $TWST Twist Bio for targeted sequencing panels.
The slide summarising the tech specs for the new Revio long-reads instrument: 1,300 HiFi WGS per year, sub $1,000 human HiFi genome, 25M ZMW SMRT Cell, 24-hour cycle time. Load-in-advance capability that takes less than 1 minute to perform.
Some stats on the Revio performance based on 29 recent internal runs with human, plant, animal, and plasmid samples. Quotes here for greater or equal than Q30 reads, so it seems like the mark for a HiFi read is at Q30, although presumably a fraction of that is above.
Onso (Omniome SBB technology) expected to ship in Q2 2023, with 200 and 300 cycle kits. Beta program at places like the Broad institute and Corteva. Pricing at $15/Gb, which I believe is the first time this has been publicly listed.
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On library prep at #Nanoporeconf, a description for PCR-free methods showing the difference between ligation (max output) and rapid mode (10minutes, minimal lab equipment needed). Ultralong reads (ULR) also enabled, all Kit14.
Rapid ULR. Current record is about 4 megabases.
PCR expansion kits enable the use of samples with low input amount.
I did a deep dive on the different workflow management (WFM) tools for #Bioinformatics Data Analysis a few years ago, and since then there have been a few extra entrants in this segment, still mostly concentrated in serving the Next-Generation Sequencing field.
A few years ago, there were two communities dominating the open-source WFM ecosystem in NextFlow and SnakeMake, and two platforms dominating the the commercial offerings in DNAnexus and Illumina BaseSpace.
Since then, a company out of the founders of Nextflow has started offering enterprise support for Nextflow workflows in the cloud: Seqera Labs. They offer the extra level of support that some organizations require to run Nextflow on their Data Analysis setups.
More interesting Next-Generation Sequencing knowledge in the ASeq Discord channel (by @new299). Illumina patterned flowcells and the etching process to "print" the wells into the flowcell. Could be down to 350nm diameter for some flowcell configurations now.
If I remember correctly, Illumina started with a 600nm diameter for the patterned flowcell, in the HiSeq X and then later on in the evolution of the platform that used these patterned flowcells.
They then said to have gone down to 500nm, and what you are showing seems to indicate that it's at 350nm now, at least for the NextSeq 2000? I am not sure if they claimed that for NovaSeq X?
There have been some acquisitions in #CancerDiagnostics and #CancerScreening recently, some of which signify a trend towards consolidation that is worth describing:
$A Agilent is moving towards some more vertical integration in Cancer Dx and Cancer screening
by recently acquiring both announcing a partnership with Akoya Bio and announcing the acquisition of Avida Biomed.
Some may ask: isn’t $A Agilent too small to go into this field? Would they be able to compete against $ILMN Illumina/GrailBio or $GH Guardant Health or $EXAS Exact Sciences?
It is likely that as Spatial Biology tools become more robust and user-friendly, they will become increasingly popular and widely adopted in the scientific community.
This may lead to a shift in the balance between single-cell and Spatial Biology approaches, with the latter eventually becoming more prevalent.
Additionally, as more and more datasets are generated using Spatial Biology techniques, the field of Machine Learning and Artificial Intelligence will likely play an increasingly important role in analysing and interpreting this data.