eclarke

import sqlite3
import multiprocessing

store_results_sql = """ some sql code here """
select_results_sql = """ some other sql code here """

def find_enriched(**kwargs):
    # do some heavy computation task here
    results = enrichment_analysis(**kwargs)
    # sqlite is not ideal for parallel processing, but with a timeout it should be fine

eclarke

#!/usr/bin/env python

import re
import json
import clint

def import_go(gofile='go.json'):
    try:
        return json.loads(json.load(open(gofile)))
    except IOError:

eclarke

        postParams.add(new BasicNameValuePair("longestOnly","false"));
        postParams.add(new BasicNameValuePair("wholeWordOnly","true"));
        postParams.add(new BasicNameValuePair("filterNumber", "true"));
        postParams.add(new BasicNameValuePair("stopWords","protein,gene,disease,disorder,cell,syndrome,CAN"));
        postParams.add(new BasicNameValuePair("withDefaultStopWords","true"));
        postParams.add(new BasicNameValuePair("isTopWordsCaseSensitive","false"));
        postParams.add(new BasicNameValuePair("mintermSize","3"));
        postParams.add(new BasicNameValuePair("scored", "true"));
        postParams.add(new BasicNameValuePair("withSynonyms","true")); 
        postParams.add(new BasicNameValuePair("ontologiesToExpand", ""));

eclarke

public static String fixLinks(String src, Wiki target) {
    
    // add a marker to all the links so we can iterate through them (except the ones that point to wikipedia)
    String src2 = src.replaceAll("\\[\\[(?!(wikipedia))", "[[%");
    
    try {
        while (src2.contains("[[%")) {
            
            // extract the link text
            int a = src2.indexOf("[[%")+3;  // left inner bound

eclarke

alpha_diversity <- function(df, group.col, freq.col) {
  # Returns a variety of diversity indices, including the Gini-Simpson index,
  # the inverse Simpson index, and the Shannon-Weaver index. The SW index is 
  # calculated using the natural logarithm.
  #
  # Arguments:
  # df: a data frame where the rows are species, with a column containing the 
  #   grouping variable and another column containing the proportional 
  #   abundances of each species
  # group: the name of the column defining the grouping variable

eclarke

>denovo1793
GGAGTCTGGGCCGTGTCTCAGTCCCAGTGTGGCCGATCACCCTCTCAGGTCGGCTATGTATCGTCGCCTTGGTGAGCCGTTACCCCACCAACTAGCTAATACAACGCAGGTCCATCTGGTAGTGATGCAATTGCACCTTTTAATTGACTATCATGCAATAGTCAATATTATGCGGTATTAGCTATCGTTTCCAATAGTTATCCCCCGCTACCAGGCAGGTTACCTACGCGTTACTCACCCGTTCGCAACTCATCCAGAGAAGCAAGCTCCTCCTTCAGCGTTCTACTTGCATGTATTAGGCACGCCGCCAGCGTTCGTC
>denovo2518
GGAGTTTGGGCCGTGTCTCAGTCCCAATGTGGCCGATCACCCTCTCAGGTCGGCTATGCATCACGGCCTTGGTGAGCCGTTACCTCACCAACTAGCTAATGCACCGCGGGTCCATCCATCAGCAGAAGCTTGCGCCTCTTTTCCTCTTCAAACCATGCGGTTCGAAGACCTATGCGGTTTTAGCATCCGTTTCCGAATGTTATCCCCCTCTGATGGGCAGGTTACCCACGTGTTACTCACCCGTTCGCCACTAGATTGACCAGTGCAAGCACCGGTCGCTCTCGTTCGACTTGCATGTATTAGGCACGCCGCCAGCGTTCGTC
>denovo271
GGAGTCTGGGCCGTGTCTCAGTCCCAGTGTGGCCGATCACCCTCTCAGGTCGGCTATGTATCGTCGCCTTGGTGAGCCGTTACCCCACCAACTAGCTAATACAACGCAGGTCCATCTGGTAGTGATGCAATTGCACCTTTTAAGCAAATGTCATGCAACATTTACTGTTATGCGGTATTAGCTATCGTTTCCAATAGTTATCCCCCGNTACCAGGCAGGTTACCTACGCGTTACTCACCCGTTCGCAACTCGTCCAGAAGAGCAAGCTCTCCCTTCAGCGTTCTACTTGCATGTATTAGGCACGCCGCCAGCGTTCGTC
>denovo3052
GGAGTCTGGTCCG

eclarke

# -*- coding: utf-8 -*-
"""
Uses a context manager to provide a dictionary as a 'namespace' of sorts,
allowing you to use dot notation to work with the dictionary. Example:

d = {'a': 5, 'b': 10}
with named(d) as n:
  # prints 5
  print n.a
  # reassignment changes both n and d

eclarke

<2014-09-25 Thu>

Reading this (Wang et al. 2010), in particular Supp. report 4. Has to do with bootstrapping population estimates using the different enzymes used to find integration sites.

<2014-09-26 Fri>

Notes on (Wang et al. 2010) :popest:petersen:intsites:

eclarke

Erik’s Lab Notebook

<2014-09-25 Thu>

Reading this [@Wang:2010fh], in particular Supp. report 4. Has to do with bootstrapping population estimates using the different enzymes used to find

eclarke

tell application "Papers"
	set outFile to "path_to_notebook_folder/library.bib"
	export ((every publication item) as list) to outFile
end tell