cbare

library(RJSONIO)

# locations will be an array of objects in JSON
# expected serialization: {"locations": [ {"path":"https://s3.amazonaws.com/foo/bar/", "type":"awss3"} ]}
e1 <- list(locations=list(list(path="https://s3.amazonaws.com/foo/bar/",type="awss3")))
e2 <- fromJSON(toJSON(e1))

if(!(names(e2) == 'locations'))
  stop("Roundtrip R->JSON->R failed names")

cbare

Predictive Modeling: Drug Response in Cancer Cell Lines
======================================================= 

This is a demo of **Knitr**, an R package for authoring executable documents, documents that mix formatted text, source code and graphical output. I've used In Sock's demos of drug response in [CCLE][1] data, but I've probably gotten most of the analysis mixed up. Apologies to In Sock.

Analysis of cancer cell lines for drug sensitity using:
  * [Cancer Cell Line Encyclopedia][1]
  * [Gene Set Enrichment Analysis][2]

Workflow

cbare

## Compute the intersection of all combinations of the
## elements in the list of vectors l. Might be useful
## for generating Venn/Euler diagrams.
## There might be better ways to do this!
overlap <- function(l) {
  results <- list()
  
  # combinations of m elements of list l
  for (m in seq(along=l)) {
    

cbare

library(MASS)

CreateSigma <- function(rho, p) {
  aux1 <- matrix(rep(1:p, p), p, p)
  aux2 <- matrix(rep(1:p, each = p), p, p) 
  rho^abs(aux1 - aux2)
}

rho <- 0.5
p <- 3

cbare

library(MASS)
library(synapseClient)

## create a matrix with defined correlation structure
cm <- matrix(c(1.0,0.5,0.25,0.125, 0.5,1,0.5,0.25, 0.25,0.5,1,0.5, 0.125,0.25,0.5,1), nrow=4, ncol=4)
m <- mvrnorm( 100, rep(0.0, 4), cm)
cor(m)

d <- Data(parentId=1493172, name='matrix100x4')
d <- storeEntity(d)

cbare

#!/usr/bin/python
 
# crontab -e
# */20 * * * * /home/ubuntu/checkpoint.py > /home/ubuntu/checkpoint.log 2>&1
 
import os

hosts = []
with open('/usr/local/Rmpi/hostfile.plain') as f:
    for line in f:

cbare

system('cp ../rssd.10x.node* .')
dfs <- lapply( list.files('.','rssd.10x.*'), function(fn) { read.delim(fn, sep="\t", header=T) } )
df <- do.call(rbind, dfs)
dim(df)
all(is.na(df$error))

cbare

#!/usr/bin/env ruby

require 'rubygems'
require 'fileutils'
require 'right_aws'
require 'optparse'
require 'pp'

cbare

{
   "AWSTemplateFormatVersion":"2010-09-09",
   "Description":"Start up a parallel Bioconductor cluster with ssh access. **WARNING** This template creates Amazon EC2 instances. You will be billed for the AWS resources used if you create a stack from this template.",
   "Parameters":{
       "BiocVersion" : {
         "Description" : "Bioconductor Version. 2.11 is recommended.",
         "Type" : "String",
         "Default": "2.11",
         "AllowedValues": ["2.11"],
         "ConstraintDescription": "Must be 2.11"

cbare

## Demonstrate following redirects with POST using urllib2.
##
## Note: This is an experiment and may not be the best way
##       to go about doing this. For example, why not just
##       change the endpoints and issue a new request? Do
##       we really want to be redirected on every request?
############################################################

import urllib2
import json