[linux] "Most high-throughput bioinformatics work these days takes place on the Linux command line"

[Hans Paijmans]

(Ik heb twee dochters die biologie hebben gedaan, en eentje is al 
helemaal Linux. Ze promoveert volgende maand dan ook op bioinformatica).


Glasgow.LINUXworkflows.Aug15-19

Course:  Introduction to LINUX workflows for biologists

Instructor: Dr. Martin Jones

This course will run from 15th – 19th August 2016 at SCENE (the
Scottish Centre for Ecology and the Natural Environment), Loch Lomond
National Park, Glasgow.

Course overview: Most high-throughput bioinformatics work these days
takes place on the Linux command line. The programs which do the
majority of the computational heavy lifting — genome assemblers, read
mappers, and annotation tools — are designed to work best when used
with a command-line interface. Because the command line can be an
intimidating environment, many biologists learn the bare minimum needed
to get their analysis tools working. This means that they miss out on
the power of Linux to customize their environment and automate many
parts of the bioinformatics workflow. This course will introduce the
Linux command line environment from scratch and teach students how to
make the most of its tools to achieve a high level of productivity when
working with biological data.

Availability: 15 places total.

Course programme

Monday 15th – Classes from 09:00 to 17:00 (approximately)

● Session 1 - The design of Linux

In the first session we briefly cover the design of Linux: how is it
different from Windows/OSX and how is it best used? We'll then jump
straight onto the command line and learn about the layout of the Linux
filesystem and how to navigate it. We'll describe Linux's file
permission system (which often trips up beginners), how paths work, and
how we actually run programs on the command line. We'll learn a few
tricks for using the command line more efficiently, and how to deal
with programs that are misbehaving. We'll finish this session by
looking at the built in help system and how to read and interpret
manual pages.

● Session 2 - System management

We'll first look at a few command line tools for monitoring the status
of the system and keeping track of what's happening to processor power,
memory, and disk space. We'll go over the process of installing new
software from the built in repositories (which is easy) and from source
code downloads (which is trickier). We'll also introduce some tools for
benchmarking software (measuring the time/memory requirements of
processing large datasets).

Tuesday 16th - Classes from 09:00 to 17:00 (approximately)

● Session 3 - Manipulating tabular data

Many data types we want to work with in bioinformatics are stored as
tabular plain text files, and here we learn all about manipulating
tabular data on the command line. We'll start with simple things like
extracting columns, filtering and sorting, searching for text before
moving on to more complex tasks like searching for duplicated values,
summarizing large files, and combining simple tools into long commands.

● Session 4 - Constructing pipelines

In this session we will look at the various tools Linux has for
constructing pipelines out of individual commands. Aliases, shell
redirection, pipes, and shell scripting will all be introduced here.
We'll also look at a couple of specific tools to help with running
tools on multiple processors, and for monitoring the progress of long
running tasks.

Wednesday 17th - Classes from 09:00 to 17:00 (approximately)

● Session 5 – EMBOSS

EMBOSS is a suite of bioinformatics command-line tools explicitly
designed to work in the Linux paradigm. We'll get an overview of the
different sequence data formats that we might expect to work with, and
put what we learned about shell scripting to biological use by building
a pipeline to compare codon usage across two collections of DNA
sequences.

● Session 6 – Using a Linux server

Often in bioinformatics we'll be working on a Linux server rather than
our own computer— typically because we need access to more computing
power, or to specialized tools and datasets. In this session we'll
learn how to connect to a Linux server and how to manage sessions.
We'll also consider the various ways of moving data to and from a
server from your own computer, and finish with a discussion of the
considerations we have to make when working on a shared computer.

Thursday 18th - Classes from 09:00 to 17:00 (approximately)

● Session 7 – Combining methods

In the next two sessions — i.e. one full day — we'll put everything we
have learned together and implement a workflow for next-gen sequence
analysis. In this first session we'll carry out quality control on some
paired-end Illumina data and map these reads to a reference genome.
We'll then look at various approaches to automating this pipeline,
allowing us to quickly do the same for a second dataset.

● Session 8 – Combining methods

The second part of the next-gen workflow is to call variants to
identify SNPs between our two samples and the reference genome. We'll
look at the VCF file format and figure out how to filter SNPs for read
coverage and quality. By counting the number of SNPs between each
sample and the reference we will try to figure out something about the
biology of the two samples. We'll attempt to automate this analysis in
various ways so that we could easily repeat the pipeline for additional
samples.

Friday 19th - Classes from 09:00 to 16:00 (approximately)

● Session 9 – Customization

Part of the Linux design is that everything can be customized. This can
be intimidating at first but, given that bioinformatics work is often
fairly repetitive, can be used to good effect. Here we'll learn about
environment variables, custom prompts, soft links, and ssh
configuration —  a collection of tools with modest capabilities, but
which together can make life on the command line much more pleasant. In
this last session there will also be time to continue working on the
next-gen sequencing pipeline.

The afternoon of Friday 19th is reserved for finishing off the next-gen
workflow exercise, working on your own datasets, or leaving early for
travel.

The cost is £500 including lunches and course materials. An
all-inclusive option is also available at £710; this includes
breakfast, lunch, dinner, refreshments, accommodation and course
materials. Participants will need a laptop with a recent version of
Python installed.

Please send inquiries tooliverhooker op prstatistics.com  or visit the
websitewww.prstatistics.com

Please feel free to distribute this information anywhere you think
suitable

-- 
Dr. J.J. Paijmans
Houwenberg 2A, 5985 PE Grashoek (L)          077 888 05 77
http://paijmans.net          GSM: +31 621 961 083
v.a. Macbook