Discover and read the best of Twitter Threads about #singlecell

Most recents (24)

Excited to share that our @NatureBiotech paper with Aviv Regev on Multicellular Programs (MCPs) is now out with a fully automated data-driven method to identify MCPs from #singlecell or spatial data #behindthepaper:… (1/19)
Gene programs are often studied within a cell, with each cell considered an “independent entity”. However, cells from the same niche/tissue/organism are not independent, but share external signals, genetic background/lineage, and can directly impact one another. (2/19)
Here we define “Multicellular Programs (MCPs)” as different sets of genes working in concert across different cell types. (3/19)
Read 19 tweets
Announcing TopOMetry, a dimensional reduction (DR) tool to learn #SingleCell data phenotypic topology. Finds >100 CD4 #Tcells in public blood data with very specific marker genes. You can use any method for visualization, such as MDE (@akshaykagrawal):


Pre-print just now on BioRxiv:…

I'm still learning a lot, as I did this mostly on my own during my clinical rounds in pandemic Brazil. If you spot any mistakes or have comments, please be kind to reach out. I plan on improving.

In a nutshell: dimensional reduction happens in 'steps' (i.g. kNN, affinity learning, decomposition, optimizing layouts). TopOMetry assumes phenotypic topology (i.e. manifold hypothesis) and approximates the Laplace-Beltrami Operator (LBO) at each of these steps.

Read 21 tweets
Really chuffed to share our latest work from Sanjana Lab out in @nature today (…).

We tested >12,000 genes to find positive regulators of T cell proliferation to be used for next-gen #immunotherapies.

A thread...
(2/28) T cell therapies have shown the potential to cure patients from #cancer – but even in B cell cancers, relapses outnumber cures… One of the problems is limited T cell persistence. #celltherapy #CARTcell
(3/28) We wanted to find new genes (including genes never expressed in T cells) that could improve T cell persistence. Now, the question was: should we use #crispr activation or directly deliver target genes on a #lentivirus?
Read 30 tweets
Thrilled to announce my 1st paper from @stevens1lab is now published @NatureNeuro. “Dissection of Artifactual and Confounding Glial Signatures by scRNA-seq of Mouse and Human Brain”. Why is it important? a 🧵👇 #singlecell #microglia #methodsmatter 1/n…
While the title frames this work in terms of brain, a KEY takeaway from new data in this version is that this is broadly applicable across basically all scRNA-seq (and RNA-seq) studies (especially in immunology)... 2/n
...and the artifact we discuss is unfortunately highly prevalent in current literature. So stick around even if brain isn’t your thing 😉. We thoroughly characterize the issue and provide a robust flexible solution to eliminate it as well. 3/n
Read 36 tweets
Are you interested in how we can learn more human biology by integrating #singlecell genomics and #GWAS?

Please check out our preprint:
#V2F mapping at single-cell resolution through network propagation…

Led by @fulong_yu! A short 🧵 (1/n)
#GWAS have identified innumerable variants associated with disease, as shown in this recent @GWASCatalog plot, yet our understanding of the function of most variants is lacking. #V2F (2/n)
With the increasing availability of #singlecell genomic atlases, such as the @humancellatlas, there are tremendous opportunities to systematically map variants to functional regulatory elements, which can be defined by accessible chromatin or epigenomic marks. (3/n)
Read 16 tweets
Finally published in @naturemethods: CellRank for directed #SingleCell fate mapping, our take on studying cellular dynamics using RNA velocity. Fantastic collab between labs of @dana_peer @sloan_kettering and @fabian_theis @HelmholtzMunich, read at 1/17
Motivation: scRNA-seq is great to study cellular heterogeneity, but its application to continuous processes is limited by the fact that cells are destroyed upon sequencing. Hence, we obtain many genes across many cells, but only through static snapshots. 2/17
Trajectory inference algorithms have been developed to reconstruct dynamics from static snapshots. They order cells according to similarity and even detect branches. But what about the direction? Often unclear, esp. in perturbed settings like regeneration, reprogramming etc. 3/17
Read 17 tweets
1/ Excited to share how T cell therapies kill #leukemia!! multi-omics + new #computational #singlecell tools for longitudinal analysis 👉unexpected answer!…

*👏* @elhamazizi! 🙏 @dpeer Cathy Wu @MDAndersonNews @CPRITTexas @ColumbiaBME @sloan_kettering
2/ We studied donor lymphocyte infusion (DLI) - an #Immunotherapy for relapsed #leukemia after #BMT & the #og of #celltherapy. Previously, we showed DLI reversed T cell exhaustion - but didn't know why/how/which T cells were responsible...…
3/ To address these ?'s, we modeled intraleukemic T cell dynamics by integrating longitudinal, multimodal data from ~100K T cells (!) during response (R) or resistance (NR: nonresponder) to DLI.
Read 18 tweets
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.
Read 6 tweets

Discovered @alchemytoday over the weekend

He's a JHU PhD who is now a P.I. at ULisbon. Focuses on #singlecell microbiology🦠

He picked up on some *NOTABLE* details in 175 page short report released by 🦂 last week

Will curate his posts in this🧵…
On the possible psychology behind the design of the document (see formatting)


More on the possible psychology behind the design of the document (see formatting)


Read 20 tweets
So exciting to see our work at the @hoheyn lab published in @genomeresearch !!
"A single-cell tumor immune atlas for precision oncology"…
And so my first #tweetorial begins (1/9)⬇️

#SingleCellCNAG #SingleCell
We created a single-cell atlas of the tumor immune microenvironment that contains over 300000 immune cells from 13 cancer types and over 200 patients. We were able to annotate over 25 immune populations.
We were able to separate the patients into 6 different groups according to the predominant subtype of cells in their tumor immune microenvironments.
Read 9 tweets
Absolutely thrilled to share our VASA-seq pre-print on #biorxiv today: Droplet-based single-cell total RNA-seq reveals differential non-coding expression and splicing patterns during mouse development 🧵…
VASA-seq captures most parts of the transcriptome (total RNA) of a #singlecell rather than just a portion. It was expertly developed by Fredrik Salmen, a postdoc in @AlexandervanOu1's lab at the @_Hubrecht and partner in crime for this project 🕵️ (1/n).
The method fragments the entire RNA payload of a cell and polyadenylates each fragment which makes them compatible with all poly(T) based barcoding methods, enabling UMI-tagging and retaining strand-specificity (2/n) 🧑‍🔬👨‍🔬
Read 14 tweets
In #biotech #stocks today, I highlight $BLI Berkeley Lights which is currently down -11%. The trend is still looking downwards since Dec 2020 when it had a remarkable burst of what I would call "frothiness" and since then it's been on a gentle downwards trajectory.
Sometimes these big short hikes are not entirely rational, and as of late, with the emergence of the meme stock phenomenon, normal decent-looking #biotech companies can be hijacked by pump-and-dumpers that don't even care at all about what they invest in.
This is nowadays magnified by the Robin Hood's of the world of investing, which act as an amplifier of the crowd behaviour that is decoupled from any logical thinking.
Read 6 tweets
Saved my 1st tweet for my 1st paper and very excited to share what I’ve been working on with @ShirleyGreenba1 and @Inna_Averbukh in @MikeAngeloLab! We assembled the 1st spatio-temporal protein tissue atlas of the human maternal-fetal interface at single-cell resolution 🧵[1/9]
In pregnancy, fetal cells invade the mother’s uterus. They remodel arteries and replace part of the artery lining 🤯 This is an immunological mystery and it’s *required* for healthy pregnancy. Impaired invasion and remodeling are implicated in many pregnancy complications [2/9] Image
Which cells participate? How does this evolve with 1) gestational age and 2) artery remodeling? All unanswered Qs. To examine these, we used #MIBITOF to simultaneously profile 37 proteins in archival tissue from 66 patients, analyzing >500k cells and almost 600 arteries [3/9] ImageImage
Read 10 tweets
We are very excited to share our work in @Nature on developing scRibo-seq, a method for #singlecell ribosome profiling! With @jervdberg, Amanda Andersson-Rolf, @HansClevers, and @AlexandervanOu1… 1/15
Ribosome profiling is a technique used to provide a high-resolution and instantaneous view of translation by sequencing ribosome-protected footprints
By directly integrating the footprint generation with library construction, we were able to dramatically increase the sensitivity and scalability so that we could perform ribosome profiling on single cells.
Read 15 tweets
In the #biotech #stocks #NGS field, there is a company that's recently IPOed and has now presented an update of their plans: $OMIC Singular Genomics @SingularGenomi1…
Their two planned instruments, the G4 and the PX, look physically a lot like competitors to the #Illumina NextSeq and NovaSeq, or the #MGI #DNBSEQ G400 and T7 instruments. But the PX is more of a multi-omics play rather than a higher throughput #NGS machine.
It seems we are about 1 year or 1.5 years away from Early Access / Commercial Launch for the PX, maybe around 6 months earlier for the G4 instrument.
Read 9 tweets
A post on the current #singlecell biology technology space.
Most of the information is my personal opinion after having followed the field first-hand or from comments I gathered from experts on either the wet-lab side or the data analysis side.
The largest player so far is 10X Genomics: in technological terms, they were the second to be able to apply the kind of high-throughput level to the problem of single-cell assays. Initially, they got into trouble with IP due to the fact that some of the founders were involved
in developing the technology in another company, which ended up being gobbled up by a larger player with big pockets and plenty of lawyers on retainer. Although never certain, it seems from the last 1-2 years of news that the IP issues have subsided, so now it's a play on tech.
Read 21 tweets

Topic: $SRNGU/ $SRNG and potential Ginkgo Bioworks SPAC deal. Specifically, $20B valuation mentioned by Bloomberg

Will walk through some mkt data on chart below

Comments encouraged

^Will preface this w list of most interesting things in $SRNGU/ $SRNG S-1

1). HUGE cash trust: $1.5B

2). Mostly entertainment experts (they SPAC'd DraftKings), but sector agnostic

3). Criteria: "High growth +FCF potential"

2). One bio link: $ALLO $KRON @Vida_Ventures @bt_prop
Let's also establish

i). Ginkgo is IP creation biz (a #synbio $TXN/ $INTC/ $AMD) housed in automated CRO (see $PPD $WUXAY $CRL) "on steroids." That gets paid in cash+ stock/royalties

ii). Biology inherently hard to scale, but part of revenue magic of Ginkgo is code reuseability
Read 23 tweets
Is it possible to predict signaling in single cell? 🤔
Our @attila_gbr with Marco Tognetti, @BodenmillerLab group, @tanevski, and @Sagebio designed a @DR_E_A_M challenge to crowdsource this question and our manuscript is out 🎊…. Here is what we learnt🧑‍🎓
we used this… rich dataset from the @BodenmillerLab and @Picotti_Lab labs: 80 millions of #singlecell from 67 #breastcancer cell lines, 36 measured markers, 5 kinase inhibitors, time courses #CyTOF + #proteomics , transcriptomics and genomics
Did the antibody stop working or you cannot measure a node? We can predict it’s activity from other measured nodes. Predictions correlate strongly with test data and are accurate across time and conditions. Watch out for rare signaling patterns though.
Read 6 tweets
My highlights of the RNGS21 @MGI_BGI Satellite Workshop talks:…
Talk on AMR genes by @johnpenders at Maastricht UMC+ (I hope it's the right one), and how these increase/decrease for example with intercontinental travel patterns. Travelers to South-Eastern Asia acquire the mcr-1 gene.
Mcr-1 gene is identified and well-known from 2015, but the patterns of AMR migration started earlier
Read 20 tweets
My highlights of the @10xGenomics #Xperience2021 event. The list of products keeps growing, I would highlight Chromium Connect as an underappreciated tool to bring the products up another level of throughput. Important as with #NGS, it won't take long to go from n=1 to n=96+. Image
#CellPlex species-agnostic multiplexing up to 12 samples: not dissimilar to products such as TotalSeq, but baked-in so that it's been tested to work with the rest of the workflow. Image
Going close to 1M cells, the #ChromiumX brings about 100x fold throughput increase, all marked with 'HT' in the Kits. I'd be interesting to know how the different #BodyAtlas projects embrace this and for what. ImageImage
Read 31 tweets
Did you know #lipids control cell identity? Yes, they do! Happy to share our first preprint on #singlecell #lipidomics in collaboration with @gio_dangelo and a fabulous team led by @CapolupoLaura and Irina Khven.… Image
We used #MALDI imaging mass spectrometry to measure the single-cell lipidomes of hundreds of individual human dermal #fibroblasts. We identify specific lipid metabolic pathways that display cell-to-cell variability. Unexpectedly, single cells clustered by lipid composition! Image
It took a lot of experiments to convince us, but now we can say it confidently: there is such a thing as a #lipotype!! First of all, toxin-based lipid staining validated the existence of the different populations of dermal fibroblasts both in vitro and in vivo. Image
Read 10 tweets
Today, I’m proud to share our latest work published in @NatureBiotech describing MELD, a #MachineLearning algorithm for #SingleCell perturbation analysis.

Read this #tweetorial to learn about the work led by @dbburkhardt and Jay Stanley 🥳🎉🧪…
Before we get into the details of the paper, I want to give a shout out to our excellent collaborators: @david_van_dijk, Guy Wolf, @giraldezlab, and Kevan Herold. This work was possible thanks to countless discussions, experimental support, and input along the way (2/16)
I also want to share a link to software for the paper. @dbburkhardt with help from @scottgigante wrote a Python 🐍 package following the @scitkit_learn API. It’s available right now on GitHub and PyPi. Couldn't be easier:

$ pip install meld…

Read 16 tweets
I sometimes see #SingleCell papers where the authors treat some dimensionality reduced plot as ground truth. Here's a quick, simple example showing why that can be problematic. 1/n
Here are three random distributions plotted at the vertices of an equilateral triangle. As you can see, the mean distance from any two clusters is equal. 2/n ImageImage
Right now we're using two dimensions. What if we want to reduce down to 1-D? Well, one simple solution would be to just get rid of the y values. The distance between cluster 3 & 1, and 3 & 2 are about equal, but now 1 & 2 are further apart. Not great. 3/n ImageImage
Read 7 tweets
Excited to share first preprint from my postdoc work in Stevens lab: “Single Cell Sequencing Reveals Glial Specific Responses to Tissue Processing & Enzymatic Dissociation in Mice and Humans” a thread below #singlecell #microglia #methodsmatter 1/n…
What started as small internal pilot in the lab, turned into full-fledged paper. I’ll detail some of the key findings in thread below. But first want to take a second and thank all of our fantastic colleagues and collaborators without whom this project wouldn’t be possible 2/n
Help from many fantastic members of Stevens lab @thammondglia , Lasse, Alec, @ConnorDufort , Sarah, @soyonhonglab and of course my mentor @stevenslab1. Continuing fantastic collaboration and advice from @macosko and his lab Tushar, Chuck, @Abdul_Squared , Naeem, and Velina. 3/n
Read 39 tweets

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