kcha

#!/usr/bin/perl

# KH: This is modified from the original lastjoboutput script.
# 
# Shows the output of the last N jobs that finished running on the cluster
# with an exit status OTHER THAN ZERO.
# Convenience function to avoid having to find the most recent job output file

use strict;
use warnings;

kcha

#!/usr/bin/env python
# encoding: utf-8

import sys
import fileinput
from optparse import OptionParser, OptionGroup
import multiprocessing
import time
from itertools import izip_longest, izip, repeat

kcha

# Sample code for performing hierarchical clustering

# install.packages("gplots")
library(gplots)
library(RColorBrewer)

##### Use iris dataset ####
# See ?iris for more info

data <- as.matrix(iris[,1:4])

kcha

# $Date: 2010-10-29 16:09:50 -0400 (Fri, 29 Oct 2010) $
# Filename: stats.py
#
# A bunch of math/stats functions
import math

'''calculate average'''
def calcAvg(ls):
    n, mean = len(ls), 0.0

kcha

# Rprofile.site file

.First <- function() {
    #.libPaths(c("~/lib/R/3.0", .libPaths()))
    if (Sys.getenv("TERM") == "xterm-256color") {
        library("colorout")
    }
}

.Last <- function() {

kcha

#install if necessary
source("http://bioconductor.org/biocLite.R")
biocLite("seqLogo")
biocLite("Biostrings")

library(seqLogo)
library(Biostrings)

strings <- c("GATTACA", "GATAACA", "GATAAAA", "GATTAGA")

kcha

# these examples rely on the R/qtl package, www.rqtl.org
# install R/qtl package, within R, by typing install.packages("qtl")

all: knitr_example.html knitr_example_asciidoc.html knitr_example.pdf markdown_example.html

R_OPTS=--no-save --no-restore --no-init-file --no-site-file # vanilla, but with --environ

knitr_example.html: knitr_example.Rmd
	R ${R_OPTS} -e 'library(knitr);knit2html("knitr_example.Rmd")'

kcha

#!/bin/bash
 
check_exit_status() {
    # Checks the latest exit status and exits if status is non-zero
    # usage: check_exit_status $? "my_function"
    EXITSTAT=$1
    FUNC=$2
    if [ "$EXITSTAT" -ne "0" ]; then
        echo "=> ["`date`"] $FUNC failed"
        exit $EXITSTAT

kcha

N=4     # Chunk size
C=0     # Counter

for i in {1..12};
do
    # submitjob here...
    echo $i
  
    ((C=C+1))
    if [[ `expr $C % $N` == 0 ]]; then

kcha

library(readr)
library(dplyr)
library(tm)
library(wordcloud)
library(SnowballC)
library(RColorBrewer)

m <- read_csv("node_table.csv.gz") %>% 
  filter(EM1_fwer_qvalue_dataset1 < 0.5, EM1_gs_size_dataset1 > 95)