Reading, processing, and writing high throughput sequencing data

18 April 2013

Why sequencing data?

Only half of the class expressed an interest in using Python for sequence analysis. Why should I care?

high throughput sequence is big data
it's also multi-dimensional
your data of interest might also be mostly strings
it's what your instructor knows best

FASTQ format

FASTQ: it's like FASTA, except with quality scores for each base call

@HWI-EAS179_0001:5:1:7:119#0/1
CAGGGCGCGAATGNTTTGAGAGGGANATTGGAAANNNNNGATAGANNGGNCTATNNTGNNNNNNNNNNNNNNNNNN
+HWI-EAS179_0001:5:1:7:119#0/1
HIHHHGHHHFDHH#EHHH?HHHDH>#[email protected]@?##########################################

Lines 1-4 are
1. read name
2. base calls
3. strand (+/-) and optional read name
4. quality scores
These quality scores are encoded as ASCII (American Standard Code for Information Interchange)
- to decode, convert from ASCII to numeric and subtract 33

Reading all at once

import sys

with open('1000_reads.fastq', 'rU') as f:
    data = f.readlines()
    
bytes = sys.getsizeof(''.join(data))
kbytes = float(bytes) / 1024
mbytes = kbytes / 1024
print mbytes

## 2.10134029388

Our small sample file takes up 2.1013 MB on disk and 2.1013 MB in memory.

Uh oh! My exome sequence is 10.5 GB. Do I need 10.5 GB of RAM?

Instead of reading in our entire data at once (like ordering a super-size value meal) we can grab and use only as much as we need at once (like making multiple trips to the salad bar).

In Python, this type of interaction is known as a generator object.

How to make a generator?

def countTo(n):
    """ Count to n in increments of one """
    num, nums = 0, []
    while num <= n:
        nums.append(num)
        num += 1
    return nums

counting = countTo(5)
print counting

## [0, 1, 2, 3, 4, 5]

Let's turn this function into a generator:

def countTo(n):
    """ Count to n in increments of one """
    num = 0
    while num <= n:
        yield num
        num += 1

counting = countTo(5)
print counting
print [i for i in counting]

## <generator object countTo at 0x1039a2410>
## [0, 1, 2, 3, 4, 5]

We can treat the generator like a list and get our results as we iterate.

Explicit iteration

def countTo(n):
    """ Count to n in increments of one """
    num = 0
    while num <= n:
        yield num
        num += 1

counting = countTo(5)
print [i for i in counting]

counting = countTo(5)
print iter(counting).next()
print iter(counting).next()
print iter(counting).next()
print iter(counting).next()
print iter(counting).next()
print iter(counting).next()

## [0, 1, 2, 3, 4, 5]
## 0
## 1
## 2
## 3
## 4
## 5

Each iteration yields a result when you request it. That way you never make the entire list in memory.

Reading a file as a generator object

class fastqReader:
    """ 
    A class to read the name, sequence, strand and qualities from a fastq file

    file = the file name of a fastq file
    """
    def __init__(self, file):
        self.file = open(file, 'rU')
        self.read = read

    def __iter__(self):
        """ 
        Return read class: (name, sequence, strand, qualities).
        """
        for i, line in enumerate(self.file):
            if i % 4 == 0:
                name = line.strip()[1:]
            elif i % 4 == 1:
                sequence = line.strip()
            elif i % 4 == 2:
                strand = line.strip()
            elif i % 4 == 3:
                qualities = line.rstrip('\n\r')
                yield self.read(name, sequence, strand, qualities)

    def __enter__(self):
        return self

    def __exit__(self, *args):
        self.file.close()

% = "modulus", more commonly known as the remainder after division

A class to store sequencing data

class read(object):
    """
    A class to hold features from fastq reads.
    """

    def __init__(self, name, seq, strand, qual):
        self.name = name
        self.seq = seq
        self.strand = strand
        self.qual = qual
        self.dict = {'A':'T', 'T':'A', 'C':'G', 'G':'C', 'N':'N'}

    def __getitem__(self, key):
        return self.__class__(self.name, self.seq[key], self.strand, self.qual[key])

    def __repr__(self):
        return 'name: {0}\nseq: {1}\nstrand: {2}\nqual: {3}\n'.format(\
        self.name, self.seq, self.strand, self.qual)

    def seqlen(self):
        return len(self.seq)

    def reverse(self):
        """ Reverse the order of self """
        return self.__class__(self.name, self.seq[::-1], self.strand, self.qual[::-1])

    def complement(self):
        """ Take the compliment of read.seq """
        compseq = ''.join(map(lambda x: self.dict[x], self.seq))
        return self.__class__(self.name, compseq, self.strand, self.qual)

Iterating through a fastqReader generator object

import sys
import lecture12
with lecture12.fastqReader('1000_reads.fastq') as fq:
    read = iter(fq).next()
    print read
    read = iter(fq).next()
    print read
    bytes = sys.getsizeof(read.__repr__())
    kbytes = float(bytes) / 1024
    mbytes = kbytes / 1024
    print mbytes

## name: HWI-EAS179_0001:5:1:7:119#0/1
## seq: CAGGGCGCGAATGNTTTGAGAGGGANATTGGAAANNNNNGATAGANNGGNCTATNNTGNNNNNNNNNNNNNNNNNN
## strand: +HWI-EAS179_0001:5:1:7:119#0/1
## qual: HIHHHGHHHFDHH#EHHH?HHHDH>#[email protected]@?##########################################
## 
## name: HWI-EAS179_0001:5:1:7:191#0/1
## seq: GAATCGATGAAGTNCGGCTTTTTGTNGATGATGTNNNNNATGCGGNNGCNCTGTNNGTNNNNNNNNNNNNNNNNNN
## strand: +HWI-EAS179_0001:5:1:7:191#0/1
## qual: G=EFHHDHF=9D<#D9:[email protected];HH=H0#B6?B##############################################
## 
## 0.000264167785645

Every time we iterate over our fastqReader object, we receive a new read object. Instead of using 2.1013 MB of memory, now we use only 0.0024 MB of memory! That leaves us plenty of to make our program useful.

Accessing specific base positions within a read

import lecture12
from textwrap import fill
with lecture12.fastqReader('1000_reads.fastq') as fq:
    starts = []
    for read in fq:
        starts.append(read.seq[0])
    print fill(''.join(starts))

## CGTAGTCTTCAATCGTTTAGTAGGGCGACTTATGTTACAGTAGCTATCAAGAACTAAGGGGGACATGAAT
## TACAAAGGGTCCGAAGTAGATGCTAAAAGTAACCACTGGTCCAGGAGGATAAAGGATCTGTAGAAGCTTG
## TTCCTTTTTACCACTGGGAGTCTCAAACTTTGTGGCTAGAGGAAGCTAAAATAAGACGTTCTGGCAGATA
## GAGGGTCTCATTCAGAGATGAAATAGTTTAGTTATGATTTGTGAGAGCGATGACATGACAAAAGTAATAC
## AAATCTATCCTTAAGTAAACTCTTGCACTGAGCCTGAGCCGTTTAATAGAGAGCAGTTGCAGAAGGGGCA
## ACCGGCATCTCTTAGTCGCTGACGGACTGAGAGATTGCAGTTACCTGGTGAGTGCGAAATTGGTCGCAAA
## TGATAAGACATTCACTTGGAATCCATCCCTTTAAACTCGTGCTAGTAGTGGACGGTGGATGCCTAATGGT
## GTGCACCCAACAACCATACGTTAGGGTGAGGGTACTGGACCCGAGCCCAATCCGGTTGGATATGGACCGG
## TAGTGTTGTATCGGCAAAATGCACTGCGGTATTTAATTTCAGGACTTAGCTAGTAGTATGAACCAAAGGA
## CGCATTACTATAGTAGAGGAGACTTTGAATTCGATTTTTGCGANAGAAGTATGTAACGAAATCGAGAAAC
## GGGGGGCAAAGTGGTTATATCTGAGAATACCGCCGTGATCTAGTATCGATTTTGCCGAGGCCCCCGTGAG
## ACCAAAGGACCATGAATCANTGCGCAGGCGGGTTCCACGCCAGCAAGAATGTAGATTACGGACTTTGACC
## TTAAATTGTTATGAATTTTGAAAGATTAGCTGTGTGTGAAGAACTGTTATAATAGTTACAGTAGAAGCTT
## GGGCGCGCACGAGACCTTAATGTTGGTCAGAGTTACGAGTAGCTATGTGCGTTGGGAGAGCGGGAGGGTA
## CTAAAAAGATAGATATTAAGACAGTAGAAACAGCGAGATTAGATTACTAAGCGACCGAGCAATCGGAGCG
## GGGTAGCAGGACGAAAACAACTAAAGACCGAGTGACAGAAGTTTTGAATCGAGGATTTGCATGCGAGCCC
## TAAGAAACCCTAAGACTGCACTTAGAAGGAGTCAATAATAAGNGACCTCCCAGCGGTGGATTCGCGGTAG
## TCCGTGCAAAGCAAAAAACAAATACTCAATGAATCAGACCGGTGGGACCGATAATAGACCATATGATTTG
## AATGTGGATCCACTGGCTGAGATATGAAAAGAGACTCTCTTTTTAGGGTGGCGCAGTCTCCAAGAGGTAT
## TCGCCGTAGCTGAAGGTAAGCAGCCGTGAGACGTTTTGGTATAGGACTGCTCCAAAAGTCGGCTTCCAAT
## GCTTTGTTTTATCGCACACAGGAGGCTATTGCGGTATAGTCGAAAGAATGCATATGATTTATTTCACCAT
## GGGGCGGTTGCGTACGACAAAGTATTTAGAGGAACAACTTGATGGATGGTCCACGCAAGGGCTCAGTTGA
## TAGCAAATAAATACGATTCCCGGTAATGTTCATAAAATTAACTTCGAAACCAAAAGTTAAGCGTGGCACA
## TAGAGAATGACGAGGGACGTGATAGAGCAGAAAAGTTATCTTGTTGGTGCCACTAAACTAACACAGTAGA
## AGTGGACAACTTGAGAGACTGGGACGCTCAGGGTAGTAAAACGACAGAAAGTCTTTGGGGCATCGTACTC
## GGCTGAAGAGAATGGATGTAGGATCGAAATCAAAGCATTTTTACTAGTATCAGTGAATGTTAAGACAGCT
## AAACAAACGTCTTTGTGTAGAACAGATACACGGGGACAGAAATCAACAGAGCGTAGCGCCAGGTGCAGAT
## TCGGGTGATTAGACCAGGCGCGCATGAGTTGAATAATGTAGTAGTAAACGGAAATAAACAGAGTGGCAAC
## TACGACACTAAAAATGGAATATACAAGAGTAAGGGGAAGTCTGCAATAGTACTGTGCCGAATTTGGAGGG
## ATAAAAAACGACTGGGGAAGTTTCGCTGGAAAAGGTATAGAAGTAACGACAGGGTATAGCTCTAACAAGA
## AGTTCACGATAGAAGGACAGGAATAACAAACTCATATTCAGATAAGTTATCGTGGAGGGGGGTGGGAAGT
## CCTACCTGAGTGAGTGGTAGAGTGTGTCTAGCACCTAGTGAGGAACGTGTATTATGAGTGACAGAACGGG
## GACGCATGGGGTCATACTCAGAACAGTAAAGGTGACTATAATAAACGTCGACTGCTTGGGGAGTTTAGTT
## TAGTCTCGGGATCGTACCCAGGGCTAGGTAGGCACATAAACTCAGGTACGTGTGAGGGCGAGCGATGTGA
## CGATATACTCAATTGCTCTCCCCCGGAGACAGAAAGGGGTAGTATGCGAAAGTTGATCGCTCAGTGTGCG
## CACAACGGCAGTGAGTGATCGAGAGCGGCGATATGAGGCGAGTACTGAGCTAGGAGCTATATGTAGAGCT
## GTATGATGATCGAATTTCGAACAAGATGCGTTTTAGCGAACGTCTCTAATAGGTCACTATTACCACTCTT
## AGACAAAGAGACATAAGCTCAAAAATGAGTGACCGCACTTATGAACCTCTACAGAGTGATAAGTAATATA
## CTCTGAGCTTGTATAGAGATTCGTAATGGGCCTGAGATTTCATAGCTTTAAGGTCAACGAATCGGCTTAT
## CATCAGCGATAACTATGCTGGAATGATCCCTAAAAGTTCTGTCTATTGTAGAATTTACTGTATAGAATCG
## GTAAAGACATTGGTATACATTAATCTATTCGGAGATCGCCTATGCTTTGAATGAAGGACAAAATCATGAA
## TATTTTAAAACTTGATGCGGACTTCTAGCTGGTCGCTGGACACAATGTTTGGGAAAAAAATTAAACGGTA
## CGAACAAAGGCCGTGGACAGGAAAGGTTTTGACTTGGGAATTTAAAGGGGAATGAAAATCGATCATAGTC
## AATCGCCAGAAATTGATATGACATGGCCCACTAGATATGATATAGCAGAAGCAAATCTGCCGGCAGAATC
## ACGGTCCGATACTTTTCAGTTAAGGGTAAGTAACCGTTAATCGCGCTCGAGAACCAAATAACATATCCAA
## GATGCATAAACATAGCTGTTGGATCGATGTAGGATGGACTAAATAACAAAAGAAAAGTTATACGCAAGGA
## TCAAGAATAGATAAAGCTTCTAGCTAATTCACTAGAGATTAGGGGTTTCGAGAGAGTACCGAGATACTGC
## CTAGCACCCTGGTAGTAGGCCTGAAACTGGAGGGGCTTATGCTAGAAATATACGATAAGTAATCTTATCT
## GACTAGATCAAACGACACCTAGGTCTGGTCGGTACAAAAATCAGGCATAGTTAGAGGGAACGAGAGAGTG
## GTGTATGCAACTGACGAAGCAAAGTGATATAAAGCAAAGAAGCCCTTCACAGTGAAAGCCAGGTATGATA
## AAGTAGATATAAGGGAGGAAGAGACTCGAGAGAGACACGATTAGTAAGGAAGATTAAAAAGATAACAATA
## TATGTGACGAGCCTAGGCAAAAGAACTCTAGGCTACATAGTGGAACTCTATCGGACCCATCTGAACTGCG
## CTACCGAACAGATTGGTTAACCGTCATAATTGCCCAATAAGAAATTACTAGTAAAAGCAATACTCCGCTG
## GTTTGAACTTCAATGACGGTGAAAACTAGGAAATACGCCAATAGGGGGGCATATGAAGTCCTGTTCTCTC
## CAAGCTGTCGCGACATACAAAAAGAAGAGGAACTCTAGATGATTCCAAGTATAAAATGAGCACATTACAA
## TGTAACGAGGGTGCGGTGAGGGACATCATTAACTTTTATTATAGGAGAATGTTCCATGGAGTCAGGAGAT
## TAGCATCTTCAAGGGCACGTATCTCCCTTATAATGTGCAGAAAGATAGGCCGTTGCCAGCAAGTAATTAA
## AAAAAGAAGCAGTGTGAAGCAGTCGGACCAGAACTGACTTGGGTAAGGCGAAGCATACTGAAATTAGGTC
## GAGAAAAGTAGAATTGGAAAATAAGCGAGGGCAGATCGCCGAAATACGTAAAACAACAGAAAGAACTATC
## TGACCGTTATCTCTTCGTAGTATGCGTAGATTTAGGTAAATTTAAATGCAATAGGCATGGTATAAAATTG
## GAAAACGAATTCAGCCAACATGGATGAACGCCAAATTACAAGGGATCCTATCACTCTTAAAAATACTGAT
## AGCAAGTGTGGACAACAATAAGAGGATTTCAACATGTGGAGTACCCAGATATCCGATTGTATGGGCGTTG
## CATTGTGGGAGTATTGTCTGCGAAGGGGGTACGAATTACCCCAGGACTATATCGACCAAATGAAAAAAAG
## TACTCACAACCAGATGTAAGCCTACATATATCGAGTACCGATGATAAAGAGTCGTCAATATGATACATCA
## AGAGAAAAGGCGACCTATATGTGTAATAAAAGAAGTAAAGCATCCGTACAGTAGGAAGTTATTTATGAAG
## TAGGTATAGACATGAGTCAAAATAAATGATCAAATGATGAGGGAAACCAAATTAACGACCAGGTATAATA
## AGGAATATGAACGCTGATAGTCAAACCTGAAGGAAATGGAATAAATTACTGGATGAATACCTAGCAAAGC
## AAAATAACTAAAGCCAGAATTTACACATAATCCTACTATAAGGGCGGAAGCTAGGTAGAGCAGTATCTCA
## AAATCAGTTGTAAGATCGATATGGGTCGGAGAGAGCATGATATCAATGCGGCACTGGATCAGATCCACTT
## TGAATGAATTTCGGTGAACTAAAAAAGACGTTAAATCCTCCCGTGAACGAAAAATCGCAGATCCAATTAC
## CCGTATAGTCCTTAGAACAAATACAGCACGAGTTCAACTACTACCTCTGTCCGAGACACCGAGTAAAAGA
## AGTACAAGGATTGGACGATTATAAAGAGAGAATAATGTATGAAGTGAGGACAAGGTGAGTCGCGGGGATT
## GGAAATACACGGTAAAAGTCATGGCCGGCTTGCGCATAGCGGTGGAAAATATATTAATACAGCGAGTGTC
## GCCAAGCGCAGCCCAGTATATAACCAGACGCAGCCAAAACAGAAAGGATCTATTATTTTCCGTGATGGTG
## TAAAAAGGCGTACGACATAAGTTTTAATGCTGATTGTTAAGAATGTCAAATTAGTGCTGTGGCTAGATGC
## GAAGCACTTGAATTAACAGCGTGATTTTGTTACTGACCCTACACAAAATAAAGCGTCATTTGAAGAATGA
## TTACGGTATAGGATGAGTATAACGGTATAGTATTAAGGTCACGGATCGGGAAACTAAACCACCGCACGAG
## AGGCATTACGTAAGGTAACTCGGAGGACAAATCCCTCTTTAATTTTTAGGTTACCAAACAGGTAGTAAAA
## CAAGGGCTGTAAAAAAGGGTCTATCAACAGTCATATTCTAACAATCTCAGCGCTTAGATCCAAAAAATAA
## ATCGAATAACTAAGTTGTAGCTGAGAACAGACGGTAACTTAGGAAGGTCCCTCAGAATCATGTGGGAAAC
## GATTCGAATGTACCNCATATATGGAAAAGAGTCCGTTTCCCCAAGCCACATGGATGGATACAGACAATTC
## AAAATCAACTAGAAAACAATTTTGAAAACAGTGTGTTTATTCATTGAAAGGCAAAAGTAAGTACGTCTAC
## GCCCGAGCAACAAACTTACACGCGTAGAAACTTAAGCAAACCACACCGTCAATACATTCCATAAGAATGA
## TTCAGAGCCGAATAAAACGAGAAGAAACATTATAACAGGTGGAAAGACAAAGGGGGAGGCAACACGTGTA
## ACACGAATGGGCATAGGAATCTCACTTTCTACAGAGAATATATTTACTGGTGGTGGCAAGCCAATCCGCA
## TAAAATTGTTCCTTTCTAACGATGAAAGAAAAGGCAACTATCACAATCTAAATGGATAGATGACCTATCC
## GACAAGTTTAATTAGGGTTAGGTCAGGACCAGTAGAGTGAAATGTGACAGGTCCAACACTGAAACAAGAC
## TAGTATGCGCTGTTTAAATACGCAAAAGTGCAAAAAAAAAACTATTTAATTTGAAACATACGAGGTATGA
## AAAACAGGATAGTGGGATGAATGTTAGCTGAACTGTCCCCTAAGATACGCTAAGCTGCCTCAACTTAATA
## TGGGCAGCATAATTAAGCCTGGGAACGAATAGATCCAGAAGCCATTCCCAACCGGTCACCGTAAGAAACT
## TAACGAGGCAGTCAGTCTCAAATTGCGATTTGAGAAATGTGGAAAACTCGAATATGGAAAATTGGAAACC
## TAAATCAAAGGACTAATATCAATTGGCAAATCCTAACAAAAATTTTAGTTACCGTTTGAACAACTGGGAG
## CGGGCACGCTCAAACCAGGCAGACTTTAAAACCTAAGAGAATCGATGAAGGTTTTAGAAAGTGATCAAGT
## AAATGCCATTTAGCTGACAGACGTTGACGGAATGACGCGCACGTAGATTTAGGACAGTTAAAACATAAGG
## ATGTAGTTTCATCCACGGTATCTAAATCTAGCGAAATAACTTAAGGTGTTTGATAGGAAAAAACACAAGG
## TTGAATTGGAATCTTGAACACATTTATTAGCGTCAAAGAGTAAGGGGAAAGGTACACAACTTCACTAACT
## TGCAATTGAGGAATAAGTAGGTCAAGGGTAGAAATCACGAATGGGCAAGAAGTAGTGGGTCTAAACGGCA
## GTAATTTCTAGAATAGCTTCAGTCCGAGTGTGCTAAAGAAATAAACGCAGAAAGGGTGGCAAGCAAAAGT
## GTTCTTTGATTACGCTTTATGGTAGGGACTACTAAACACAGAAGGGAAATAACAAAACATTCCGTCGGCA
## ATCACAGCCATAAACAAATGGAGTGGATTAGCGAGATATACCTAGAAAAGCAAATGCTAAGGGCCGAGTT
## AGCCGTGCAATCATAACATAAAACCATATCCATCCTAAACAAATGTGACGTATTAAGAGAAGCAAAAAAA
## CTACAAGATACCACAACATATAAATTTAGTAAGCAAGGGAGCCAATTTGGGATAAAAGTAAGACAGGTAA
## GATGTGGTCACAGGGAGTCCCAAAGCACGATATAGGTTATCATCCCCCTTGCAAAGAGGATAGAGAAGCC
## AAACAATAAGCGAATCATGAATTGAAATAAACGACATAGTTAGGAATTAGAAATTATATGGGTAAGATAT
## TGTTACTGAACTGATTTATCTTCTTAATGGGACTCGAGTAGGTCCAAAATGCCTATATGGAGTAGACCAT
## ATGTGGCCAAATAGCATGAGCTAACGAGTCGAGTCGATAAACACACAATGTGATCGTTGTGTCGAACCGA
## GGGGGGTGGCTGATGCCTAAGACAACCCTTATAGACAAGGTTACCCTATCATGAAACAAAGTAGATGGGC
## AGTCAGCCATTAGCAAGGACAAGACAAAAGAACATGGGTCAAATGATTGGGCAAATGAGATCTGTAGGTA
## GGCGGGAAAGGAGCATACTCAATAGAAAGACACAGGATGGATATCTATACAGCACTAACGAAGTGCTTAA
## ATAGCGGGAGTAAGAATCAAAAAGGGGAGCCCGAGATTAGGTTAATATTAGAGTAACAATAATTTTACAC
## GAACTATGTGCATCAGAGTCAAATATTCGGAGTGGGACCTTTGGAATTTTCTTAGTAATAGGGCATAGGA
## AGAGATACGGAAAGGGAAATAGATAGTTAGAGCGGCCAATTTTACAAAACATGTTGGGCCAGGTATCACT
## AAAAGAAGGAAGAAGTCAGGTATGACCTAGCGAAGGAGAGGATAGGCCAACCATTGGTAAATTANGACAA
## CGACAACAGTGGCGACACAAACATGTGGAGCAAGAGCTTTAAAAAAGATATTAAAAGGTATACACTCGCA
## ATGTAGAGACAACGGAAATTTTTGACTGATAATAAGCAAACGTATTAAGGTAGTGAATTGCAACCATTCA
## AGATGAAGGCCTCCGGAAAGTACAATACGATAACATCATTAATGAGTGTGTGCTAGAAGACTAAGAAGCA
## TCAGAGGACCGATACATATTGCAGTAGCAAAAACTGTTCATAAGTTAGTTTATGAGAAGATATTAGTACT
## TATAAATGCGGCAAGTCCTGCGCACATAAGAAAGGAAATGCTGAGACTTCGAAGTTGTATGACATATGTG
## GCAAAACATGTGAGGTGTATCTGCAAAAGATCGCGTCATTAGGCAAGTGACTACATTCTTAGAAAAACAT
## TGAGCTAAGCCGAGTGACGTGCAGATTAGTAACGCGCACTTATACAAAATAATACTGGTGATAGNATGTC
## ACATGAACGATATGGTTTGAAAACATGAGTTTGTGCAACAGGCGCGGTACGTGTTATGCCTCCTTAAAGA
## CGAAGGAGTTGAGCATGGGAAAAGTTAGAGTTCTTGAAGATGCCTTTTTGCCTCAGCTAACCAAATAGAA
## GTGCCTACGATGTTGATCGGCGTCCAAATATCAGCAGTCAGGGCTTAAATCTAAAGACTAAATTAAAGGT
## ATTATAGAGTGAGAGTTCACCCAAACTCAACATGTAGAAGGATATCAGGTTTCATTACCATTACCAAGAG
## ATACGAACTGGAAAGGTACATCGAAGACGGAGGGGGGCGCAGCCGAAGATAACTTTTTTGAGACTCATGC
## ATTATGAATACGCGAGGGCTCGATGGGGCTCGGTGTGCAGGGAGTGTGATGAATAATTTAATTGAAGCAG
## ATGGCCCAACTAACGCATAAGAAAAACAGTCGTGATGACATAGTGTTTTGTGATTGGAATATTACAGACT
## CTCCACTACTAAAAGAGCGAGATGTACAGGTAAAGACATATTAGATAAGAGGTAAATGGCGGCTAATAAA
## GATTTATGCTGCAATGAGGAAAGAGGTGTGTGAGGGTTAGAGAGGAGCCCAGGAGGAAAACGCAAGTATT
## GTAATAGCTATCAAGTCATTAAGCGAATAGATACTAGGACTTGATGTCGAAGTAATCATCGAAGCGAGGG
## CCAAGTGAAGAGTCACTGATTCTATGGAGGATATCCGATAAATGAAAAGTAACTAGTTATGCGCCAAGTG
## GAAAAGACAGGACAACGAGGACGCAGGCAATGCATCGCATGGAGCATGATGAACCCAACATGACAACGGT
## TATTCAGTGTCAAGAGTGAGAATGCATCTATGTACTCGCCAAAGGGGAAGGAGAAATTACTGCGTCACGT
## TCAATAAATTTTTGTAAGTTTGTAAACAAGAAACTGAATGCAAAAGCAAGGATTGTATACGGTCATCGAT
## CTTATAGTGAAATAGCGAAAGATTTTCGAGAAACAATTACACAGCAAAAGCATAGAAGTGGACTTAGTCT
## AAAAGGACATGACAACATCCTAAACGGCATTGCATAACGAGAAAAGGAGTAGACGCCATGCCAGTATTTA
## GTCAGTATATAACGGACACTCACCATTAAACATAATTTAGTACCAAATGTAAAAAGCGCACGCGCGTAGC
## AATTATGGTTTAATAGAAAAAACTGGAGAAACCATACATTATAAATATCAAAGGACGGTGAGAGAAGTAG
## ATCGGGGAGGGAGAATTTATACGAAAGTAGCAAGTAGGTACCAAGCTTCGAAACTCAAATAAAGACAACC
## TTGAGAAGATCGATATGAAAGACAGAGGGGTAACTATAATCTACCCGGGGGATCAAATTCAAATTCACTA
## CGTGTGGAAGAGTCGAAGACCGACAGCGGTGGGACTGCACCAAGTCCCACAAGCTAGGCCAACTACATGT
## AATAGACTCCAGACAAGCAAAAGATCATGATTGCGAAGTAAAGCAGCAATTGTGTGGGTATGAATAAAGG
## GACATGCGTTCCGATGCTACAAGGAATGACATTACAGTACGGCTGCAATAAGAGGTTGGG

Homework assignment

Extend the read class with a method for calculating the "reverse complement" of the sequence
Write a script that calculates the GC content of each read in 1000_reads.fastq and for each read with > 40% GC content prints:
- the read name
- the GC content
- the GC content of the (reverse) complement

Points will be awarded for the following criteria:

creativity: did you try something new?
simplicity: could you accomplish the same thing in less lines of code?
correctness: does it run and produce the expected result?
completeness: does it do everything we want?

Let's work on the homework

The code and python module used to generate these slides can be found at https://github.com/mdshw5/BIOF309.

Start by downloading lecture12.py, which contains the classes and methods detailed in this lecture.

Are you a hacker yet? (check out the image and see if it looks familiar)