GeneDrift Wiki

beginning_python_for_bioinformatics

2009-05-22T11:29:23-04:00

The posts from Beginning Python for Bioinformatics are and will be included here, allowing for a better experience when reading the entries. Beginning the begin This website uses as a premise the book: Beginning Perl for Bioinformatics by James Tisdal

bioinformatics_workshop_2010_-_department_of_pathology_and_molecular_medicine

2010-08-18T09:26:44-04:00

Thursday August 5th Topics covered: Basic Linux/Unix commands: cd - ls - mkdir - wc - grep Introduction to the BASH shell - online book Simple for loops in BASH Simple FASTA file manipulation in BASH BioMart - Martview Blast+ - Blast book, based on the legacy version but still relevant

gd_wiki

2010-08-05T19:39:54-04:00

This wiki will contain entries from Beginning Python for Bioinformatics and some information about software projects. Beginning Python for Bioinformatics Software Bioinformatics Workshop 2010 - Department of Pathology and Molecular Medicine

part1

2010-01-24T13:51:27-04:00

Part 1 Hands on code: Sequences and strings 1 As pointed in Beginning Perl for Bioinformatics, a large percentage of bioinformatics procedures deals with strings, especially DNA and amino acids sequence data. As is largely known DNA is composed of four different nucleotides: A, C, T and G and proteins can contain up to 20 amino acids. Each one of these elements have one letter of the alphabet assigned to them. In the DNA case some letters represent one or more nucleotides that can be present a…

part10

2009-05-14T12:14:52-04:00

"Cutting" chromosomes with Python: a fast approach Last couple of posts we started with some functional programming aspects of Python. I was away last week and couldn't create anything related to FP in the meantime, so I decided to post about a quick way to “cut”, or extract segments, from chromosomes stored as FASTA files.

part11

2009-12-04T14:38:50-04:00

Python sets This time we will check how set works in Python. set is another object type available in Python (version 2.3 and up) that brings a lot of features to the language. From the Python Library Reference: “A set object is an unordered collection of immutable values. Common uses include membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.” Yep, all these are possible with set, and …

part12

2009-05-20T11:41:41-04:00

Generating reverse complement of DNA sequences As shown in the GenBank DNA parser script, it is really useful to have the ability to get the reverse complement of some DNA sequences. The reverse complement of a 5'-3' DNA sequence is on its complementary strand. Using our fasta module it is easy to implement a function to generate the antiparallel sequence

part13

2009-05-20T16:58:36-04:00

Python sets and intersections This time we will see a different example of set usage that includes some methods available for this type of objects. The initial problem was how to determine which genomes are represented in protein/DNA clusters obtained with CD-HIT. Basically CD-HIT uses a multiple fasta file to generate clusters of proteins/DNA using their sequence identity. It clusters the sequences, keeping their fasta title and assigning an ID for each cluster obtained. We won't see how is C…

part14

2009-05-21T11:23:42-04:00

1 This part is based on the conversion of some small C++ programs I developed in the past. These small programs (I call them modules because they were part of a larger application) were used to count motifs, short nucleotide words up to 10-12 base pairs, and then calculate statistical overrepresentation of these words by comparing a foreground set of DNA sequences against a background set.

part15

2009-05-22T11:28:24-04:00

1 We created a very elegant script in Python that efficiently counts words in FASTA sequences and then using a basic statistical method, calculates the significance of each word and output the overrepresented ones. Our script used a little bit less than 50 lines, and if you include the imported fasta module, it won't top 100. But the number of lines is not important. The efficiency, clarity and speed are key here. At the same time, running a script from the command line is not something every…

part16

2009-05-22T11:36:18-04:00

1 Let's check some database topics in Python. I was asked to create a simple database to organize wet-lab stuff. No relationships needs, no relational tables required. Just a simple table with determined columns, and a nice GUI to go with it so people can edit, search and use.

part2

2009-05-11T11:38:07-04:00

Flow control in Python We start following the fifth chapter of BPB. The first item is about flow control and code layout, which are very relevant for our tutorial. We already introduced briefly both aspects in past entries on the site, but it is always good to check. As the book, I will start with flow control.

part3

2009-05-11T11:50:20-04:00

Debugging in Python Beginning the third section in our tutorial/guide, we are going to see the chapter six of BPB. This chapter discusses the topics of creating subroutines (in Python's case functions) and debugging the code. We are going to start by the end. In Python, code debugging can be done as in any other programming language: Perl has pdb, C/C++ has gdb, etc. Python also has a pdb module that can be imported and run to check for errors in your code. Using this command line:

part4

2009-05-14T11:38:34-04:00

Randomization We start section 4 with a very short introduction to randomization. Chapter 7 of BPB discuss the use of randomization to obtain mutations in DNA and protein sequences. The example given in the book is at the same time simple and interesting, as it creates a paragraph from random selections of nouns, adjectives, verbs and other grammar elements. Here we are going to to create a very (stress on very) simple dice game, where each time you run the script it will throw two dices for yo…

part5

2009-05-12T10:29:42-04:00

Genetic code The Python dictionary data-type is like hash in Perl. It is a very similar structure, where each element in the variable is composed of two values, more specifically a key-value pair. This is the ideal data type to store the genetic code. As you might know the genetic code governs the translation of DNA into proteins, where each codon (3 bases or nucleotides in the DNA sequence) correspond to an amino acid in the protein sequence. So for every sequence of 3 nucleotides (key) will r…

part6

2010-02-11T05:21:20-04:00

Finding motifs: IUPAC and RegEx, an overview For anyone also following the book there will be a jump at the end of chapter 8, so we are not touching the final script that deals with different reading frames here. We are going straight, or almost, to another take of Regular Expressions. We are going to check some aspects of restriction enzymes, but first we are going to touch base with motif finding in DNA sequences.

part7

2009-05-20T11:34:35-04:00

GenBank files: take one This part deals with the manipulation of GenBank files. These files are used by NCBI to store information about RNA, DNA and protein sequences. It is usually composed of an annotation section, that gives information about the sequence present in the particular file. I won't spend much time explaining the GenBank format, because it is not the goal of the site. The perl book has some good explanation about it and you can also find more information here. Also, we are goin…

part8

2009-05-13T10:36:08-04:00

Splitting a multiple sequence FASTA file We will see the easiest way to split a FASTA file. There are many ways to name each file after the split, and we will use a simple original filename + number. We also going to use the FASTA class and functions defined previously in fasta.py. To refresh our memories here is the code

part9

2009-05-14T11:49:11-04:00

Functional programming in Python: using map First we need to define what is functional programming. Quoting Wikipedia: “is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids state and mutable data. It emphasizes the application of functions, in contrast with the imperative programming style that emphasizes changes in state.”

start

2009-04-28T13:57:25-04:00

This pages will contain information regarding the Beginning Python for Bioinformatics blog and bioinformatics software and projects. To see more click the links below: Beginning Python for Bioinformatics Software Projects