I will say, box plots / dynamite plots are a terrible way to display data and too many people still use them. But people make a lot of poor choices in their figures. Since you've come this far I'll share this ultimate useless figure... enjoy Figure 1... jstor.org/stable/2291148…
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There is a lot of focus on the importance of reproducible science for facilitating replication of published research. That's all good, but reproducible science has another benefit: when adopted by a group it is an incredible accelerant for research *in that group*. 2/
Consider the paper we wrote on whole animal multiplexed #scRNAseq. The @GoogleColab notebooks Tara Chari wrote for the analyses were a monumental effort, but she did not start from scratch. 3/
The design is simple and elegant. A single motor drives the shaft of the tube rack, which is coupled to the dispenser arm via a spiral track. This ensures both rotate in tandem. 2/
The device is easy to 3D print and build, and can be assembled from off-the-shelf parts in less than an hour for $67.02. This low cost, and the straightforward assembly, is possible thanks to the design around a single motor. Amazing work by @annekylosaurus & @sinabooeshaghi. 3/
Universal Health Services @UHS_Inc is the largest facility-based behavioral health provider in the country. Its mission statement includes "To provide..healthcare services that..INVESTORS seek for long-term returns."
We show #scRNAseq can be used for "reverse genomics" to conduct low-cost *experiments*. Instead of sequence first ask questions later, we ask questions first & then sequence. We illustrate the approach w/ a starvation experiment using the emerging model Clytia hemisphaerica. 2/
We performed multiplexed #scRNAseq using the ClickTag approach developed in our lab by @JaseGehring (w/@sisichen, Matt Thomson, Jeff Park). The chemical multiplexing can be used on any tissue/animal and facilitates experiments with little batch effect. 3/ nature.com/articles/s4158…
In 2006 I went on a year-long sabbatical to @UniofOxford from @UCBerkeley. My grants were just ending and I thought I'd reset by doing some math after several years of genome consortia (I didn't have a biology mentor to tell me R01s can be renewed, so I didn't know & didn't try).
At @UniofOxford I was hosted by Philip Maini in Maths and @JotunHein in the Stats. It was a fun year in which I met @satijalab who was a student at the time. We ended up writing a paper on phylogenetics, alignment and annotation: academic.oup.com/bioinformatics…
The first database I curated by hand was for my Ph.D. thesis. It consisted of a database of 117 orthologous human and mouse genes (this was in the late 90s before either genome was sequenced!). It's still up: cb.csail.mit.edu/cb/crossspecie…
Compiling this database was hard. It required combing through GENBANK, performing alignments to check for orthology, examine proteins for homology etc. The database was generated for benchmarking a gene prediction tool, but I found that the curation had much more value than that.
The process of compiling the database taught me a ton about the state of gene sequences in GENBANK, challenges in sequence alignment, functional annotation etc. I learned a lot making this database. Also others found it useful in derivative work: korflab.ucdavis.edu/~genis/documen….