I created an example showing how to use mygene.info with typeahead.js. It is possible to autocomplete gene names and retrieve every annotation you can think of (GO, Kegg, Ensembl, position, homologs, etc.).
It turns out that sympy and scipy have the slowest implementations of the binomial mass function. A pure Python version is just 30 times slower than C in my benchmark. Feel free to copy the code from the IPython notebook and test it for yourself.
After performing many tests for statistical significance, the next step is to check if any results are more significant than we would expect by random chance. One way to do this is by comparing the distribution of p-values from our tests to the uniform distribution with a quantile-quantile (QQ) plot. Here’s a function to create such a plot with ggplot2.
Here are a few tips to use
ssh more effectively. Login to your server using
public key encryption instead of typing a password. Use the
file to create short and memorable aliases for your servers. Also, use aliases
to connect through a login server into a work server.
Use Python to count the coding base pairs in each Gencode gene. Here, the count is reported by gene rather than by transcript, so overlapping exons from multiple transcripts are merged before counting the base pairs.