CristinaSolana

1. Clone your fork:

git clone [email protected]:YOUR-USERNAME/YOUR-FORKED-REPO.git

2. Add remote from original repository in your forked repository:

cd into/cloned/fork-repo
git remote add upstream git://github.com/ORIGINAL-DEV-USERNAME/REPO-YOU-FORKED-FROM.git
git fetch upstream

phoboslab

import sys
import time
import win32api

if (len(sys.argv) < 4):
	print "Usage: python mousemove.py dx dy speed"
	sys.exit()

current = win32api.GetCursorPos()
cx = sx = current[0]

nhoffman

#!/usr/bin/env python3

"""A simple python script template.

"""

import os
import sys
import argparse

hoffrocket

#!/usr/bin/env python

from multiprocessing import Process, Pool
import time
import urllib2

def millis():
  return int(round(time.time() * 1000))

def http_get(url):

mgalardini

#!/usr/bin/python
'''
Launch codeml on all the alignments

Marco Galardini 2012
University of Florence
GPL v3.0
'''
from optparse import OptionParser, OptionGroup
from time import strftime

sidderb

library(shiny)
library(deSolve)
library(cummeRbund)

# load cuffDiff data, must be in top dir and called cuffData.db:
cuff = readCufflinks()

shinyServer(function(input,output) {
    
	getData = reactive(function() {

astrofrog

import os
import random
import string
import tempfile
import subprocess

def random_id(length=8):
    return ''.join(random.sample(string.ascii_letters + string.digits, length))

TEMPLATE_SERIAL = """

rxaviers

People

:bowtie:	😄 :smile:	😆 :laughing:
😊 :blush:	😃 :smiley:	☺️ :relaxed:
😏 :smirk:	😍 :heart_eyes:	😘 :kissing_heart:
😚 :kissing_closed_eyes:	😳 :flushed:	😌 :relieved:
😆 :satisfied:	😁 :grin:	😉 :wink:
😜 :stuck_out_tongue_winking_eye:	😝 :stuck_out_tongue_closed_eyes:	😀 :grinning:
😗 :kissing:	😙 :kissing_smiling_eyes:	😛 :stuck_out_tongue:

trestletech

library(shiny)
library(ggplot2)

# Get the current day of the month
dom <- 25

# Define the target for salespeople in our organization.
salesTarget <- 15000

# Set the seed so we always get the same data.

jdblischak

Differential expression analysis with edgeR

This is a tutorial I have presented for the class Genomics and Systems Biology at the University of Chicago. In this course the students learn about study design, normalization, and statistical testing for genomic studies. This is meant to introduce them to how these ideas are implemented in practice. The specific example is a differential expression analysis with edgeR starting with a table of counts and ending with a list of differentially expressed genes.

Past versions:

• Tuesday, April 26, 2016