wilkox

#Load libraries
library(wilkoxmisc)
library(ggplot2)

#Read OTU table
OTUTable <- read.tidy("./yangyang_OTU_table.txt")

#Add relative abundance
OTUTable <- add.relative.abundance(OTUTable)

wilkox

#Load wilkoxmisc
library(wilkoxmisc)

#OTU Table with taxonomy
OTUTableWithTaxonomy <- "PUT-PATH-HERE"

#List of blank samples
BlankSamples <- c("Blk", "Blk2")

#Read in OTU table and select blank

wilkox

#!/usr/bin/perl

use Modern::Perl 2014;
use autodie;
$|++;

open FAILED, "<", "./aligned/rep_set_failures.fasta";
open OUT, ">", "rep_set_failures.tidy.txt";
say OUT "OTU";
say "Reading failed rep set sequences...";

wilkox

#Load wilkoxmisc
library(wilkoxmisc)

#List of paths
OTUTablePath <- "PUT-PATH-HERE"
ContaminantsPath <- "PUT-PATH-HERE"
ChimerasPath <- "PUT-PATH-HERE"
FailedAlignmentPath <- "PUT-PATH-HERE"
OutputPath <- "PUT-PATH-HERE"
OutputPathWithTaxonomy <- "PUT-PATH-HERE"

wilkox

#!/usr/bin/perl

use Modern::Perl 2014;
use autodie;
use File::CountLines qw(count_lines);
$|++;

my $readsFile = 'PUT-PATH-HERE'; #This is the input read set e.g. forward.fasta
my $prefilterFile = 'PUT-PATH-HERE'; #This is the list of PyNAST failures, something like forward_failures.txt
my $mc1 = 'PUT-PATH-HERE'; #This is final_otu_map.txt

wilkox

#Required libraries
library(wilkoxmisc)
library(ggplot2)

#Files
BreakdownStatisticsFile <- "PUT-PATH-HERE"

#Read in breakdown
Breakdown <- read.tidy(BreakdownStatisticsFile)

wilkox

#!/bin/bash
#
#PBS -l nodes=1:ppn=16
#PBS -j oe
#PBS -k oe

date

#Set base dir
if [ `hostname` == "Davids-MacBook-Air.local" ]; then

wilkox

#Load wilkoxmisc
library(wilkoxmisc)

#Read in OTU table
OTUTable <- read.tidy("final_otu_table_mc2_w_taxonomy.clean.tidy.txt")

#Separate bacteria and archaea
Bacteria <- OTUTable[which(OTUTable$Kingdom == "Bacteria"), ]
Archaea <- OTUTable[which(OTUTable$Kingdom == "Archaea"), ]

wilkox

#Files
CleanOTUTablePath <- "PUT-PATH-HERE"
CastCleanOTUTablePath <- "PUT-PATH-HERE" #This will be the output file

#Load libraries
library(wilkoxmisc)
library(reshape2)

#Read in OTU table
OTUCounts <- read.tidy(CleanOTUTablePath)

wilkox

#!/bin/sh
biom convert -i CAST_OTU_TABLE -o OUTPUT_PATH --table-type="otu table"