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 bioinformatics paper describing a benchmark of kallisto-bustools and Salmon-Alevin-fry likewise relied on previous reproducible work. @sinabooeshaghi relied on his own notebooks from previous projects, and on reproducible R by @LambdaMoses. 5/
The fraction collector by @sinabooeshaghi, @annekylosaurus et al. was not started from scratch, but with a blueprint from the poseidon project. Making sure poseidon was reproducible in hardware and software was hard work. That work has paid off. 6/
@GorinGennady's work on an exact stochastic simulation algorithm for a transcriptional system benefited from reproducibility standards employed in his previous projects, e.g.
All of this work benefited from reproducible work by others as well. So while the timing of these preprints was coincidental, their shared foundations are not. Being thoughtful about working reproducibly facilitates progress in science, not just for others, but for oneself. 8/8
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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….