As of March 21st I have successfully defended my thesis, containing chapters on speciation genomics, mouse lemur phylogeography, mutation rate, and sperm gene evolution (the latter two coming soon). I’m excited to begin work as a postdoc in the Tung Lab, beginning post haste!
We just published a review of speciation in the genomic era, both recapping recent exciting work and providing some thoughts on the future of the field. It is out now in BJLS, thanks to both Anne and Jelmer for co-authoring it with me!
I have received a Bass Fellowship to design and teach my own course within the Biology Department here at Duke: Methods in Computational Biology & Genomics. From my course description:
This hands-on, methods course will introduce students to biological software, the statistics that underlie these tools, and how to combine both of these to test a wide range of biological questions. Topics covered will include basic command line programming, next generation sequencing methods & experimental genomics (RNAseq). The course will culminate with the implementation of these tools to complete a project re-analyzing publicly available data. Prerequisites include BIO201 or BIO202, STA101/higher or BIO204, and some coding background in any language.
If you know of any undergrads eager to get some hands on computational experience have them sign up or reach out with questions! c.ryan.campbell”at”duke.edu and visit the lab website for info as it comes available.
I recently developed a module for teaching some basic ideas about genome assembly for an assignment in “Teaching College Biology”. The module involves a short intro to genome assembly as well as the various platforms presently available (I characterize them in 3 categories: short, long, and ultra-long).
The students then form small groups and attempt to assemble a small sequence in the form of a famous speech (MLK’s “I have a dream” or Winston Churchill’s “We shall…”). Each speech has a repetitive element that makes assembly difficult, illustrating the effect of input data on assembly success.
On my github (you can find a few slides, the two text files (mentioned above) and a script to randomly generate a given number of illumina or pacbio “reads” from the text files.