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Albert Vilella Profile picture
@AlbertVilella
Nov 5, 2021 • 6 tweets • 3 min read • Read on X
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MGI Tech has given a presentation on their updated DNBSeq CoolMPS (#NGS) technology. Some highlights below:
Their DNBSEQ-Tx sequencing factory, with dip-immersion reagent delivery and 4 high-throughput imagers, can produce >50K WGS annually. Technology being upgraded from PE100 to PE150 (2021Q3)
A presentation from a user shows how #singlecell 10X Genomics libraries can be inputted into the MGI machines. Small difference between FASTQ files, but tools available to transform.
After that, then back to DNBSEQ CoolMPS technology. Main difference to Illumina is that there is essentially no Index Hopping, due to the nature of the affixed position in the patterned flowcells, and also low duplication rates.
The CoolMPS sequencing technique is based on anibodies, with low signal loss due to "Scarless synthesis".
End of this month or next month will be the official release of the new longer Paired-End kits

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More from @AlbertVilella

Albert Vilella Profile picture
May 18, 2023
The tech update from Oxford @nanopore #NanoporeConf now ongoing with @The__Taybor now presenting:
Duplex: 1.5% of the time, the complement strand follows the first strand naturally.
Initially, modified the adapters and reached 30% duplex rate. Image
Stereo base caller uses similar ML approaches as ChatGPT, Image
Read 9 tweets
Albert Vilella Profile picture
May 17, 2023
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. Image
Rapid ULR. Current record is about 4 megabases. Image
PCR expansion kits enable the use of samples with low input amount. Image
Read 10 tweets
Albert Vilella Profile picture
Apr 21, 2023
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.
Read 7 tweets
Albert Vilella Profile picture
Apr 21, 2023
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. Image
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?
Read 8 tweets
Albert Vilella Profile picture
Apr 20, 2023
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. Image
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?
Read 4 tweets
Albert Vilella Profile picture
Apr 20, 2023
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.
Read 6 tweets

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