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.
The main sticking point for running open-source WFM at scale is setting them up in cloud platforms like Amazon AWS, Microsoft Azure and Google Cloud Platform. This is still not a ‘one-click’ setup solution, and optimizing cost can still be a challenge.
Thus efforts from the likes of Seqera Labs in making the cloud elasticity available to all sort of customers, from large pharma to small biotech start-ups, is attractive.
Snakemake has also made some documents available for users to set it up on cloud providers, but not to the same extend, at the moment.
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.
A new post on Single Cell, Spatial Biology Omics and In situ Imaging on the URL in the image. Behind the curtain, some speculative thoughts on possible Mergers and Acquisition moves, including $TXG $NSTG and related companies such as $ILMN $GH $EXAS $RHHBY $ADAP $TMO $BDX , etc.
In recent years, methods for encapsulating individual cells and analysing their DNA, RNA or protein contents have become more established, with commercial support from Biotech and Life Science Tool providers
similar to what Next-Generation Sequencing received over the past decade or so. There is now a growing effort to transform academic lab-developed tools for Spatial Biology,
The regular Mass Spec market is being challenged by a new wave of companies whose technologies aim to disrupt the well-established market of large Mass Spec instrument vendors. These regular MS instruments tend to be expensive to buy, although not that expensive to run.
There are limitations in the type of analysis one can perform with regular Mass Spec. One of the biggest limitations is that performing 'de novo' protein sequencing in MS is not straightforward: the most common way is to digest the proteins into small peptides, and then
compare the MS signal for each of them with a reference database of know peptides. This works well as long as all your peptides have already been seen before, but not if you are performing MS on a sample that contains novel peptides. What type of samples can contain novel
10x Genomics is a biotechnology company that develops and markets solutions for omics analysis of single cell and spatial biology samples. The company offers several product lines:
The Chromium platform is used for single-cell gene expression analysis, immune profiling, and genome sequencing. It allows researchers to study gene expression at the single-cell level, which can provide insights into cell behavior and disease progression.