Aphaenogaster sample Genomic-tip DNA extraction day 2.
Nandrop results terrible!!! No idea why - saw beautiful strands of DNA at isopropanol precipitation stage and followed exact same protocol as previous extraction with Pogo after that.
- Re-precipitated sample (500 ul) with 750 ul 70% EtOH. Centrifuged 10 min top speed. Air-dry. Re-hydrate in 200 ul Buffer AE and Nanodrop in morning.
- I had saved Genomic-tip for this event. Added 1 ml Buffer QF. Precipitated in EtOH and centrifuged. Air-dry. Re-hydrate in 200 ul Buffer AE and Nanodrop in morning.
While setting up jekyll for static website on xubuntu laptop, decided to write quick notes on install process:
Install jekyll, requires an up-to-date version of ruby
sudo apt-get install ruby1.9.1-dev
sudo gem install jekyll
# Need `pandoc-ruby` gem for pandoc compatability
sudo gem install pandoc-ruby
Clone the website and build or serve locally!
git clone https://github.com/johnstantongeddes/johnstantongeddes.org.git jekyll serve
Of course, this is for an install of my own website…a new website would require some more steps.
De Mita, S., Thuillet, A.-C., Gay, L., Ahmadi, N., Manel, S., Ronfort, J. & Vigouroux, Y. (2013). Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations. Molecular Ecology, 22, 1383–1399.
- challenging to detect loci under selection using molecular data
- authors evaluate 3 correlation-based and 5 differentiation-based methods using simulated data with different sampling schemes and migration patterns
- all methods perform well when selection is strong
- logistic-regression based methods haver higher false-positive rates
- correlation-based methods have greater power when selection is weak
- CWDRP (Coop et al 2010 Genetics) method has best power when selection is weak with low false positive rate
- deviation from island model (e.g. isolation by distance) increases false positive rate for logistic regression based methods
- selfing reduces power for differentiation-based methods and increases false positive rate for logistic-regression methods
- sampling more than one individual per population increases false positives in logistic regression. Differentiation-based methods (especially FLK) improved with more samples per pop
- CWDRP method computationally-slow and requires population-level frequency data
- differentiation-based methods require a large number of populations (48) and 8-10 samples per pop
- more thoughts on the implications of this paper for our Medicago work in next post