Imran S. Haque Profile picture
Apr 25 10 tweets 5 min read Twitter logo Read on Twitter
Tweetorial time! We @RecursionPharma mapped consequences of #CRISPR screening of >17K human genes, found a systematic bias confounding all CRISPR screens, traced its molecular cause, and propose a debiasing algorithm. Image
“But Imran,” you say, “I’d rather read your thrilling 41-page manuscript than read tweet threads!”

I can’t blame you, it’s great! (I may be a biased source.) Here ya go: biorxiv.org/content/10.110…
In this first tweetorial, I’ll share some of the foundations of the similarity-based “maps” we build @RecursionPharma as background for what we found out about CRISPR by building a map over the whole genome.
We use CRISPR to knock out individual genes and measure the consequences by “phenomics”: imaging analysis of cellular morphology and intracellular organization.

This “maps” biology: knockouts of related genes produce similar phenotypic consequences!
Here you see a similarity map of ~50 KOs of genes in conserved pathways, showing that related genes cluster with each other. This works for a lot of therapeutically interesting pathways, and we can do it not just for KOs but also for chemical treatments for drug discovery. ImageImageImageImage
To use maps for drug discovery, you may start with a single gene, and then ask the map which other genes (or compounds) look similar to identify interesting starting points or targets. You would like similarities to be biologically meaningful, and that’s what we see above.
But if we show all the gene knockouts ordered by genomic position, a curious pattern emerges: CRISPR knockouts look more similar to KOs on the same chrom. arm than to KOs on other arms –producing a striking image of a genome-wide CRISPR map in which genome structure is obvious! Image
Hmm, you say. That’s weird.

Yes, it is! And tomorrow I’ll dig into what it means.
This was a big team effort: @nathanlazar, @houndcl, @johnurbanik, @GenRoberts_PhD, @willboneferroni, @RecursionChris, and several folks not on Twitter: Safiye Celik, Marta Fay, Jon Irish, James Jensen, and Conor Tillinghast. Proud to work with this @RecursionPharma team!

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More from @ImranSHaque

Apr 26
More tweetorial! Let’s dig into the “proximity bias” we found @RecursionPharma confounding #CRISPR screens, what it means, and where it comes from.

You can always read along in the preprint here: biorxiv.org/content/10.110… Image
If you missed the first tweetorial in the series, click here to understand what the red-and-blue heatmaps here mean, and how we use them to map the functions of genes at a genome-wide level:
To recap: if you knock out each gene in the genome, plot all their pairwise similarities, and sort by genomic position, a curious pattern emerges in which #CRISPR knockouts look more similar to KOs on the same chromosome arm than to KOs on other arms.
Read 10 tweets
Aug 10, 2020
Happy Monday! In today's #tweetorial on our recent preprint describing @RecursionPharma's platform (biorxiv.org/content/10.110…), I'll explain the unusual 2-D drug response plots we use there and in our COVID-19 screen data at covid19.rxrx.ai..

in terms of jumping cat gifs.
A primer: the @RecursionPharma platform takes images of cells under different conditions (disease agent, disease+drug, control, etc.), and feeds the images through a custom deep network to derive a high-dimensional (128-1024D) "embedding".
Instead of measuring say, two parameters like viral titer and cell count, we measure 100s-1000s of parameters describing the morphology of cells in a plate. This information captures a lot of biology, as @i_draw_hexagons described in his tweetorial:
Read 20 tweets
Apr 26, 2020
Very proud to be part of the team @RecursionPharma working on #Covid_19 and of our preprint today: biorxiv.org/content/10.110…. Brief #tweetorial :

We developed a human cell model of SARS-CoV-2 infection, compared it to the field-standard monkey cell model, and screened ~1700 drugs.
Also: the entire cellular image dataset (~450GB of 5-channel microscopy) is available at rxrx.ai/rxrx19. 305,520 5-ch pics @ 1Mpx licensed CC-BY. Want some big image data for ML to help with the pandemic? Here it is. We've also released the DL image embeddings.
Now on to the paper. If you missed @zavaindar's explainer from Friday, it's a great one to start with. I'll provide my own insights into the work here.

Read 23 tweets

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