grassa

#!/usr/bin/perl -w
use strict;

# Given properly formatted herbarium records, this script will produce two
# datasets of equal size for two time periods.  From these, for each species,
# the mean value of each time period is calculated.  The script outputs a
# tab-delimited table of columns for species, mean value of the first time 
# period, and the mean value of the second time period.  This table can be used
# to perform classical statistical tests in R.  Justification for the technique 
# is provided below.

grassa

## read in our data
data<-read.table("binned.ele",head=T)
## how are our variables named?
names(data)
## attach them
attach(data)
## are the sample variances significantly different?
var.test(BEFORE,AFTER)
## they're not, so we can't use a t-test
## we use the wilcoxon's rank test

grassa

[1] "SPECIES" "BEFORE"  "AFTER"  

	F test to compare two variances

data:  BEFORE and AFTER 
F = 1.0636, num df = 45555, denom df = 45555, p-value = 4.796e-11
alternative hypothesis: true ratio of variances is not equal to 1 
95 percent confidence interval:
 1.044220 1.083289 
sample estimates:

grassa

#!/usr/bin/perl
use warnings;
use strict;

my $readsA = '5';
my $readsT = '4';
my $readsG = '0';
my $readsC = '0';
my $error_rate = '0.001';

grassa

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

/* The block below is included so that the program will compile on the macintosh, which lacks gnu's getline. Compilation produces a non-fatal warning*/
/* This code is public domain -- Will Hartung 4/9/09 -from http://stackoverflow.com/questions/735126/are-there-alternate-implementations-of-gnu-getline-interface*/
size_t getline(char **lineptr, size_t *n, FILE *stream) {
    char *bufptr = NULL;
    char *p = bufptr;
    size_t size;

grassa

#include <stdio.h>
#include <math.h>
long fact(int n){
	if(n == 0){
		return 1;	
	}
	else{
		return n * fact(n-1);	
	}
}

grassa

#!/usr/bin/Rscript
args <- commandArgs(trailingOnly = TRUE)
lg<-args[1]
infile<-args[2]
assembly<-args[3]
bpmax<-as.integer(args[4])
genesinfile<-args[5]
pngout<-paste(infile,".genes.png",sep="")
header<-paste(lg,"",sep="\n")
dat<-read.table(infile,head=T)