# Homework Project 1 - 10 kilobase alignment
## CS/BIOINFO M122/M222
### Due: Monday, May 4th, 2021, 5:00 pm
This short programming assignment is designed to help you get an understanding for the basics
of sequence alignment. You can use any language for this project, but Python is strongly
recommended, and you will receive starter code in Python. You will submit your response to
https://cm122.herokuapp.com/upload as a `.zip` file.
### Overview
In the first two programming assignments for this class, you will solve the computational
problem of re-sequencing, which is the process of inferring a donor genome based on reads
and a reference.
You are given a reference genome in FASTA format, and paired-end reads.
The first line of each file indicates which project the data relates to. In the reference file, the
genome is written in order, 80 bases (A's, C's, G's, and T's) per line.
The paired end reads are generated from the unknown donor sequence, and 10 percent of the
reads are generated randomly to mimic contamination with another genetic source. There is
also a 1% sequencing error rate that is independent of location in the read.These reads are
formatted as two 50 bp-long ends, which are separated by a 90-110 bp-long separator.
Your task is to map the reads to the reference genome and then determine where the reads
indicate there is a difference (a variant). The different kinds of variants that may be found in the
donor genome are explained at https://cm122.herokuapp.com/variant_doc
### Starter Code
Starter code for all the class projects is available at
https://github.com/rosie068/CM122_starter_code . It is strongly recommended that you use git
for these programming assignments, and to set up your own account on github.com. The
tutorials at http://try.github.io/ might come in handy. If you are completely unfamiliar with git and
github, you can obtain a copy of the code by running
```
git clone https://github.com/rosie068/CM122_starter_code.git
```
This will create a folder named CM122_starter_code in your current directory.
## Tutorial
The starter code provided handles reading the reads and reference genome into Python lists, as
well as converting a list of SNPs into the proper output format. You will be responsible for
aligning the reads to the reference, and calling SNPs.
You should download the practice from
https://studentdownloads.s3-us-west-1.amazonaws.com/practice_W_1.zip and "for-credit" data
from https://studentdownloads.s3-us-west-1.amazonaws.com/hw1_W_2.zip . DO NOT
DOWNLOAD FROM THE LINKS ON HEROKU. If you want to follow the tutorial below,
download and extract these files into the HP1 folder. Via command line that would look like this:
```
cd CM122_starter_code
cd HP1
wget http://studentdownloads.s3-us-west-1.amazonaws.com/practice_W_1.zip
wget http://studentdownloads.s3-us-west-1.amazonaws.com/hw1_W_2.zip
unzip practice_W_1.zip
unzip hw1_W_2.zip
```
Obviously, you can just also open the browser and download and unzip the files using your file
manager.
We are providing you with the skeleton for one script:
1. `basic_aligner.py` takes in a reference genome, a set of reads, an output file and an output
header and outputs the SNPs called based on its produced alignment
Running the above script with the `-h` option should be self explanatory, but here is an example
of running them to create a file that can be submitted on the website for the practice data.
```
python basic_aligner.py -g ref_practice_W_1_chr_1.txt -r reads_practice_W_1_chr_1.txt -o
test_output.txt -t practice_W_1_chr_1
```
This will generate the file test_output.txt.zip that you can submit on the website. It also
generates a .txt file that you can look at. **Note that the -t parameter HAS to be
practice_W_1_chr_1 when submitting the practice data and hw1_W_2_chr_1 when submitting
the real assignment. This will let the online submission system know on which leaderboard to
place you.**
Read the content of HP1, and see if you can understand what it is doing. You can submit your
results as many times as you want to achieve a passing score.
### I/O Details
https://cm122.herokuapp.com/ans_file_doc should handle most of your questions on reading
and writing output.
### Questions to consider
The genome from which the reads are generated has not only SNPs, but insertions, deletions,
and repeated sequences that are not present in the reference. In addition, there is a 1%
sequencing error rate independent of location in the read.
What will these non-SNP mutations look like when you try to align them to the genome? Try
writing it out on a piece of paper.
More generally, what is the "signature" of a SNP mismatch in the consensus sequence? What
is the "signature" of an insertion or deletion?
### Grading
Remember to submit your solutions to https://cm122.herokuapp.com/upload as a `.zip` file. You
can submit as many times as you want without penalty.
You will be graded on your performance on the test set, which can be found at
https://studentdownloads.s3-us-west-1.amazonaws.com/hw1_W_2.zip and under week 4 on
CCLE. Again, DO NOT DOWNLOAD FROM THE LINK ON HEROKU. You can also submit
your solutions for the practice data to https://cm122.herokuapp.com/upload to see how your
solution is performing.
Undergrads will get full credit with a score of 45 on SNPs, and no credit for a score of 25 or
below. Grad students will get full credit with a score of 60 on SNPs, and no credit for a score of
40 or below.
























































































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