Introduction to Python for biologists (IPYB04)
27 November 2017 - 1 December 2017£260.00 - £575.00
Python is a dynamic, readable language that is a popular platform for all types of bioinformatics work, from simple one-off scripts to large, complex software projects. It gives an overview of the language with an emphasis on practical problem-solving, using examples and exercises drawn from various aspects of bioinformatics work. After completing the workshop, students should be in a position to (1) apply the skills they have learned to tackle problems in their own research and (2) continue their Python education in a self-directed way. In biology Python is often applied to sequence analysis and data manipulation e.g. calculating base composition statistics, removing adapter sequences, translating DNA to protein, counting kmers, filtering tables etc. In this course we use these applications as examples during the exercises as a way of illustrating how to use the tools that Python has because it makes sense given the background of most of the people who attend. However, it should be possible to apply what you learn to any type of programming problem.
This workshop is aimed at all researchers and technical workers with a background in biology who want to learn programming. The syllabus has been planned with complete beginners in mind.
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, dinner, refreshments, minibus to and from meeting point and accommodation. Accommodation is multiple occupancy (max 3 people) single sex en-suite rooms. Arrival Sunday 26th November and departure Friday 1st December PM.
To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.
Other payment options are available please email firstname.lastname@example.org
Cancellation policy: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact email@example.com Failure to attend will result in the full cost of the course being charged. In the unfortunate event that PRinformatics must cancel this course due to unforeseen circumstances a full refund for the course will be credited. However PRinformatics cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.
The workshop is delivered over nine half-day sessions (see the detailed curriculum below). Each session consists of roughly a one hour lecture followed by two hours of practical exercises, with breaks at the organizer’s discretion. There will also be plenty of time for students to discuss their own problems and data.
Assumed quantitative knowledge
Students should have enough biological background to appreciate the examples and exercise problems (i.e. they should know about DNA and protein sequences, what translation is, and what introns and exons are).
Assumed computer background
No previous programming experience or computer skills (beyond the ability to use a text editor) are necessary.
Equipment and software requirements
A laptop/personal computer with Python installed.
It is essential that you come with all necessary software and packages already installed (you will be sent a list of packages prior to the course) internet access may not always be available.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Meet at Margam Discovery Centre approx. 18:30
Monday 27th – Classes from 09:00 to 17:00
Module 1: Introduction.
We will start with a general introduction to Python and explain why it is useful and how learning to program can benefit your research. Some time will be taken to explain the format of the course. We will outline the edit-run-fix cycle of software development and talk about how to avoid common text editing errors. In this session, we also check that the computing infrastructure for the rest of the course is in place. Core concepts introduced: source code; text editors; whitespace; syntax and syntax error; and Python versions.
Module 2: Output and text manipulation.
This session will show students how to write very simple programs that produce output to the terminal and in doing so become comfortable with editing and running Python code. This session also introduces many of the technical terms that we’ll rely on in future sessions. We will run through some examples of tools for working with text and show how they work in the context of biological sequence manipulation. We also cover different types of errors and error messages and learn how to go about fixing them methodically. Core concepts introduced: terminals; standard output; variables and naming; strings and characters; special characters; output formatting; statements; functions; methods; arguments; comments.
Tuesday 28th – Classes from 09:00 to 17:00
Module 3: File IO and user interfaces.
We will discuss about the importance of files in bioinformatics pipelines and workflows during this session, and we then explore the Python interfaces for reading from and writing to files. This involves introducing the idea of types and objects and a bit of discussion about how Python interacts with the operating system. The practical session is spent combining the techniques from session 2 with the file IO tools to create basic file-processing scripts. Core concepts introduced: objects and classes; paths and folders; relationships between variables and values; text and binary files; newlines.
Module 4: Flow control 1: loops.
A discussion of the limitations of the techniques learned in session 3 quickly reveals that flow control is required to write more sophisticated file-processing programs, at this point we will progress on to the concept of loops. We look at the way in which Python loops work, and how they can be used in a variety of contexts. We explore the use of loops and lists together to tackle some more difficult problems. Core concepts introduced: lists and arrays; blocks and indentation; variable scoping; iteration and the iteration interface; ranges.
Wednesday 29th – Classes from 09:00 to 17:00
Module 5: Flow control 2: conditionals.
We will use the idea of decision-making in session 5 as a way to introduce conditional tests and outline the different building-blocks of conditions before showing how conditions can be combined in an expressive way. We look at the different ways that we can use conditions to control program flow, and how we can structure conditions to keep programs readable. Core concepts introduced: Truth and falsehood; Boolean logic; identity and equality; evaluation of statements; branching.
Module 6: Organizing and structuring code.
In session 6 we will discuss functions that we would like to see in Python before considering how we can add to our computational toolbox by creating our own. We examine the nuts and bolts of writing functions before looking at best-practice ways of making them usable. We also look at a couple of advanced features of Python – named arguments and defaults. Core concepts introduced: argument passing; encapsulation; data flow through a program.
Thursday 30th – Classes from 09:00 to 17:00
Module 7: Regular expressions.
A range of common problems in bioinformatics can be described in terms of pattern matching; we will discuss these and give an overview of Python’s regex tools. We look at the building blocks of regular expressions themselves, and learn how they are a general solution to the problem of describing patterns in strings, before practising writing some specific examples of regular expressions. Core concepts introduced: domain-specific languages; sessions and namespaces.
Module 8: Dictionaries.
We discuss a few examples of key-value data and see how the problem of storing them is a common one across bioinformatics and programming in general. We learn about the syntax for dictionary creation and manipulation before talking about the situations in which dictionaries are a better fit that the data structures we have learned about thus far. Core concepts introduced: paired data types; hashing; key uniqueness; argument unpacking and tuples.
Friday 1st – Classes from 09:00 to 16:00
Module 9: Interaction with the file system.
In the final session e discuss the role of Python in the context of a bioinformatics workflow, and how it is often used as a language to “glue” various other components together. We then look at the Python tools for carrying out file and directory manipulation, and for running external programs – two tasks that are often necessary in order to integrate our own programs with existing ones. Core concepts introduced: processes and sub-processes; the shell and shell utilities; program return values.