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#!/bin/env perl

### [email protected]

### Generates contigs (in FastA) and scaffolding information (in AGP) from Velvet 'contigs.fa' supercontigs file

### Use entirely at you own risk!! There may be bugs!

### modified by [email protected] 2010/09/13
### add flags -i -size -o

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Setting up a cloud-based multi-user teaching server using conda

Setup steps

1. Apply for an allocation at NECTAR-RDS
2. Setup 2 key-pairs (one will be for 'root-designated' login and the other for 'general-user' login), download the private keys to a secure location. If you're planning to use KiTTY or PuTTY to login to the server from Windows, you'll need to convert the .pem key file to a .ppk, as explained here. You can (and should) password-protect this key (can be done in PuTTYgen when converting the key from the default .pem format to a PuTTY-supported .ppk).
3. Setup a customised security group to allow remote access (open port 22 for ssh logins and any addi

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#! /bin/bash
# Ask user for sudo password (to be used when needed)
read -s -p "Enter Password for sudo: " sudoPW

# update CRAN repository below if needed
REPO="'https://cran.rstudio.com/'"

# Based on the instructions on Dean Attali's website:
# https://deanattali.com/2015/05/09/setup-rstudio-shiny-server-digital-ocean/#user-libraries

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Windows Registry Editor Version 5.00 

[HKEY_CURRENT_USER\Software\SimonTatham\PuTTY\Sessions\Default%20Settings]
"Colour0"="217,230,242"
"Colour1"="217,230,242"
"Colour2"="14,27,48"
"Colour3"="14,27,48"
"Colour4"="14,27,48"
"Colour5"="217,230,242"
"Colour6"="0,0,0"

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# Run this script in a directory containing zip files from fastqc. It aggregates images of each type in individual folders
# So looking across data is quick.

zips=`ls *.zip`

for i in $zips; do
    unzip -o $i &>/dev/null;
done

fastq_folders=${zips/.zip/}

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Goal

• To create UniRef90 protein databases for NCBI blast and Diamond Blast
• To create a tab delimited taxid mapping file with two columns : sequenceID\tNCBITaxonID

Steps:

Download the uniref90 xml file first (warning - this is ~15 GB, will take a while)

IdoBar

Setting up a new computer for scientific and bioinformatics data analysis

Follow these instructions to setup a new computer with commonly used tools and software for scientific data analysis (with emphasis on bioinformatics)

Windows machine

Use https://ninite.com/ to install the following open source software:

1. FileZilla - FTP file transfer
2. Firefox - web browser, add cliget addon for easy curl/wget download links
3. PuTTY - remote shell access
4. Java 8
5. .NET - framework needed for Paint.net

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#!/bin/bash

_usage() {
cat <<EOF
$*
        Usage: $0 <[options]>
        Options:
                 -i --in       input fasta file. If not specified will defaults to stdin [-]
                 -o --out      output combined results file. If not specified will defaults to stdout [-]
                 -p --parts    how many parts to break to input fasta into [default:5000]

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# If loading in an environment that doesn't respect my RPATH environment
# variable, set it here
sourceDir <- file.path(path.expand("~"), "R", "source")
if (Sys.getenv("RPATH") == "") {
	if (!file.exists(sourceDir)) dir.create(sourceDir)
	Sys.setenv(RPATH=sourceDir)
}

# Load commonly used functions and packages

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# util.R:
# Utilities to make R a happier place
# Originally created by Brendan O'Connor, brenocon.com/code
# Edited by Ido Bar.
# Source the file directly from this gist using `devtools::source_gist("7f63547158ecdbacf31b54a58af0d1cc", filename = "util.R")`


########################################
## Put everything into an environment, to not pollute global namespace
util = new.env()