★ Challenge 1: Python/Biopython¶
This week’s lesson is, in some ways, a one-question “midterm” that covers the skills you’ve learned so far. It’s designed to be more challenging than anything we’ve done so far, so don’t be discouraged if you have to think things over (and fail) before succeeding!
We assume that you’ve already covered (and only covered) all three of our previous sessions. For your reference, they’re linked here: Week 1 Week 2 Week 3. The techniques for solving the problem below are, with 100% certainty, covered in the previous three lessons.
Note: This does not mean that they are explicitly mentioned in one of our previous lessons. Recall that we emphasize finding specific commands, options, and tools on your own. However, we have covered the core concepts before.
The problem below does not specify how you should solve it. Instead, we’ll present you with a task to perform and you’ll need to determine the output.
Additionally, you’ll never need to download any software. Everything you need is on EC2.
In the real world, you’re often on your own when you’re stuck and need help. Reading through Google searches, documentations, tutorials, and manuals is a real life skill.
However, we don’t just want to throw you off the deep end. If you do get stuck on something and you can’t figure it out, you can draft an email and send it to the bootcamp instructors. Provide a specific description of 1) what you’re trying to accomplish 2) what issue you’re running into 3) what you’ve already tried to troubleshoot it. If we find many common issues, we’ll send out an FAQ/hints email on Sunday.
Good luck, have fun!¶
We’ve previously described how and why we sequence DNA. The raw output of these sequencing machines are FASTQ files. Each base that a FASTQ file contains is paired with a quality score that’s encoded in ASCII (proportional to how confident the machine is that the base was identified correctly). We, of course, do not want to have our downstream analyses tainted by low-confidence sequences.
There are various techniques for cleaning up such raw data. Your goal here is to implement one possible method: We will only keep reads if:
1. No base in the read has a quality score (strictly) less than 50 2. The average base quality is (strictly) greater than 68
Our goal is to output a count of the number of reads that we kept.
As an example, imagine our FASTQ file contains only two sequences, each with three characters:
@SAMPLE1 AGG + DEF @SAMPLE2 TGC + BCD
@SAMPLE1 has an average quality score of 69 (from the average ASCII of
DEF), and no character is under 50. We will keep this sequence.
@SAMPLE2 has an average quality score of 67 (from the average ASCII of
BCD), and no character is under 50. We will not keep this sequence.
The output, therefore, would be 1.
Make a copy of your input FASTQ file, available at
~/../smansuri/raw.fastq. Have fun!
Just getting 0 as your count over and over? Click me!
Newline characters have an ASCII value of 10.
Checking Your Solution¶
Your answer should be in the mid-900’s.