jnhutchinson

library(XML)
address="Boston"
url = paste( "http://www.google.com/ig/api?weather=", URLencode(address), sep="" )
xml = xmlTreeParse(url, useInternalNodes=TRUE) # take a look at the xml output:
# Get the required informations:
condition=xpathSApply(xml,"//xml_api_reply/weather/current_conditions/condition",xmlGetAttr,"data")
temp_c=xpathSApply(xml,"//xml_api_reply/weather/current_conditions/temp_c",xmlGetAttr,"data")
humidity=xpathSApply(xml,"//xml_api_reply/weather/current_conditions/humidity",xmlGetAttr,"data")
cat( paste("The Weather in ", address, " is ", condition, ". The temperature is ", temp_c, "°C. Humidity is ", humidity, "%.") )

jnhutchinson

library(XML)
address="Boston"
url = paste( "http://www.google.com/ig/api?weather=", URLencode(address), sep="" )
xml = xmlTreeParse(url, useInternalNodes=TRUE) # take a look at the xml output:
# Get the required informations:
condition=xpathSApply(xml,"//xml_api_reply/weather/current_conditions/condition",xmlGetAttr,"data")
temp_c=xpathSApply(xml,"//xml_api_reply/weather/current_conditions/temp_c",xmlGetAttr,"data")
humidity=xpathSApply(xml,"//xml_api_reply/weather/current_conditions/humidity",xmlGetAttr,"data")
cat( paste("The Weather in ", address, " is ", condition, ". The temperature is ", temp_c, "°C. Humidity is ", humidity, "%.") )

jnhutchinson

source("http://bioconductor.org/biocLite.R") #adds bioconductor site as a package source
BiocLite(“pheatmap”) #downloads and install pheatmap package from bioconductor
library(pheatmap) #loads pheatmap package

install.packages(“RColorBrewer”) #donwnloads and installs a package with useful color themes 
Library(RColorBrewer) #load RcolorBrewer package

#LOAD DATA
data=read.delim(“KO-WT-OV-3way.sig.batch.exprs.xls”) #read in expression values for significantly correlated probesets
data=data[,1:6] #subsets data remove the gene symbols, names or EntrezIDs

jnhutchinson

## 2012-05-08 - first draft
## 2012-05-14 - got rid of repetitive parts of script
## 				added RNA-seqQC prep
###jnhutchinson
###bash script to run tophat alignments for WP-rna-seq

###hard coded

#basedataDir	---untrimmed
#				---trimmed

jnhutchinson

library(plyr)
library(Rsamtools)
library(GenomicRanges)
library(Biostrings)
library(knitr)

matcher <- function(pattern, x) {
  ind = gregexpr(pattern, x)[[1]]
  start = as.numeric(ind)
  end = start + attr(ind, "match.length")- 2

jnhutchinson

  <style type="text/css">
table.sourceCode, tr.sourceCode, td.lineNumbers, td.sourceCode {
  margin: 0; padding: 0; vertical-align: baseline; border: none; }
table.sourceCode { width: 100%; }
td.lineNumbers { text-align: right; padding-right: 4px; padding-left: 4px; color: #aaaaaa; border-right: 1px solid #aaaaaa; }
td.sourceCode { padding-left: 5px; }
code > span.kw { color: #007020; font-weight: bold; }
code > span.dt { color: #902000; }
code > span.dv { color: #40a070; }
code > span.bn { color: #40a070; }

jnhutchinson

### KNITR SETUP

```{r setup, echo=FALSE}
opts_chunk$set(tidy=TRUE, cache=FALSE, highlight=TRUE, figalign="center", warning=FALSE,  error=FALSE, message=FALSE, fig.height=11, fig.width=11)
```

### EXAMPLE CHUNK
```{r libraries}
library(ggplot2)
library(xtable)

jnhutchinson

wait.on.lsf() { ## wait on jobs{
    n=`bjobs -P $projectID | awk 'NR>1' | wc -l`
    while [ $n -ne 0 ]
    do
        n=`bjobs -P $projectID | awk 'NR>1' | wc -l`
        # number of running
        echo "Running: "`bjobs -P $projectID | grep RUN | wc -l`
        # number of pending
        echo "Pending: "`bjobs -P $projectID | grep PEND | wc -l`
        sleep 60 ##raising this to 120 will cause LSF to drop the script

jnhutchinson

## Rory's kickass annotated dataframe function
annotate_df = function(d) {
  require(biomaRt)
  ensembl = useMart('ensembl', dataset = ensembl_gene)
	a = getBM(attributes=c(filter_type, gene_symbol, "description"),
		filters=c(filter_type), values=d[, 'id'],
		mart=ensembl)
	m = merge(d, a, by.x='id', by.y=filter_type)
	return(m)
}

jnhutchinson

# annotations
heatmap.annots <- pData(mic.norm.eset)[,c("ID", "study", "stage", "gender")]
heatmap.annots <- as.data.frame(apply(heatmap.annots, 2, unlist))
row.names(heatmap.annots) <- heatmap.annots$ID
heatmap.annots$ID <- NULL
# annotation colors
study_colors <- c("#FF0000","#00FF00", "#0000FF", cbPalette )
names(study_colors) <- unique(unlist(pd$study))
stage_colors <- c("white", "darkgrey", "black")
names(stage_colors) <- unique(unlist(pd$stage))