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Lecture: String definitions and Python examples

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Algoritmos Aplicado ao Sequenciamento de DNA

Universidade Johns Hopkins

4.8 (424 classificações) | 17K alunos inscritos

Curso 4 de 8 no Análise de Dados GenômicosAnálise Genômica Programa de cursos integrados

We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.

Visualizar o programa do curso

Habilidades que você aprenderá

Bioinformatics Algorithms, Algorithms, Python Programming, Algorithms On Strings

Avaliações

4.8 (424 classificações)

5 stars
346 ratings
4 stars
62 ratings
3 stars
14 ratings
2 stars
1 ratings
1 star
1 ratings

MD

Nov 10, 2016

This was really fun. Really enjoyed the a-ha of the algorithms and the fun of solving the alignment and assembly problems. Feel mildly powerful after assembling a virus genome.

LK

Mar 12, 2016

Excellent intro to the computational challenges in analyzing genomic sequences.\n\nLectures and programming exercises explain algorithms very clearly even for beginners.

Na lição

DNA sequencing, strings and matching

This module we begin our exploration of algorithms for analyzing DNA sequencing data. We'll discuss DNA sequencing technology, its past and present, and how it works.

Module 1 Introduction1:32

Lecture: Why study this?4:29

Lecture: DNA sequencing past and present3:08

Lecture: Genomes as strings, reads as substrings5:02

Lecture: String definitions and Python examples3:33

Practical: String basics 7:14

Practical: Manipulating DNA strings 7:00

Practical: Downloading and parsing a genome 6:29

Lecture: How DNA gets copied3:37

Optional lecture: How second-generation sequencers work 7:10

Optional lecture: Sequencing errors and base qualities 6:37

Lecture: Sequencing reads in FASTQ format4:39

Practical: Working with sequencing reads 11:11

Practical: Analyzing reads by position 6:58

Lecture: Sequencers give pieces to genomic puzzles5:41

Lecture: Read alignment and why it's hard3:09

Lecture: Naive exact matching10:18

Practical: Matching artificial reads 6:53

Practical: Matching real reads 7:24

Ministrado por

Ben Langmead, PhD
Assistant Professor
Jacob Pritt

Transcrição

So since we'll be working so much with strings and

with Python, I want to introduce some string vocabulary, and

then also some Python syntax for working with strings.

So a String S is a finite sequence of characters, and

those characters are drawn from an alphabet which we'll call sigma.

So since we're usually working with DNA in this class,

sigma will often just be the set that contains A, C, G and T.

S with vertical bars around it denotes the length of S,

the number of characters in S.

So in Python,

we obtain the length using the built in len function like you see here.

We'll use the symbol epsilon to represent the empty string,

the string that has length zero.

And in Python, in order to represent the empty string, you simply use two quotes,

one after the other.

Two quotes with nothing in between them.

When we want to refer to a particular position within a string,

we use an offset.

And we use the convention that the leftmost offset,

the offset of the leftmost character in the string, is 0.

So, in this example, we're getting

the character at offset 0 within the string s.

That character is A.

And here we're getting the character at offset 2, which is 0.2,

which is G, as you can see here.

The concatenation of two strings consists of the characters of the first string

followed by the characters of the second string.

So we're just gluing the two strings together, in this example s followed by t.

And in Python, we can use the plus operator to concatenate two strings.

A substring is just a shorter string that occurs within a longer string.

So for example here, we have a longer string s, and

we use this bracket notation to get the sub string of s that starts it offset 2,

up 2, but not including offset 6.

So it gets the length four substring,

starting at offset two C C G G.

A prefix of a string is

the substring of that string that begins at the beginning of it.

So for example, this string S, if we take this string, s, and we use bracket

notation to take the substring that goes from offset 0 up to but not including

offset 6, we get this string, and since it begins at offset 0, we call it a prefix.

It's aligned with the left-hand side of the string that it came from.

This syntax you see down here where the zero is omitted, and we just say :6 inside

the square brackets, is just another way of saying what we said up here.

So, if the zero is omitted, there's an implied zero.

A suffix is a substring that ends at the end of the longer string.

So, for example, if this is our string S and

we take the substring from offset 4 up to but not including offset 8,

we get the screen GGTT, which is a suffix as you can see here.

This is another way of saying the same thing.

We put -4:, and then omit what comes after the colon.

That's another way of saying we want to start four positions to the left of

the end of the string, and then go to the end of the string.

So it's another way of saying what we said up here.

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