Corresponding lecture
Lecture 2 - Ultra-fast read mapping with Kallisto
If you’re new to R
Please take time to work through this Learn R! module on basic R
Description
In our lecture, we covered the basics for running Kallisto with a single sample. However, you will rarely, if ever, be dealing with a single sample. In this lab, we’ll work through how to automate alignments and other command-line work using shell scripts and ‘for loops’. To keep the lab moving along, we’ll work with very small fastq files (see below)
Files you’ll need for this lab
subsampled fastq files - This is the course dataset, but each file has been subsampled to retrieve only 10,000 reads per sample.
shell script – To carry out read mapping and QC analysis for multiple samples.
Follow along
Bash basics - this is the code I’ll be running and discussing in lab today. You can copy/paste lines from this page to follow along.
On your own
If you’re taking the course in-person at Penn but were unable to attend today’s lab, you can still get credit for attendance by completing the lab and turning in your work to the TAs via Discord. By the start of lab next week, please turn in your code for a conditional for-loop that selectively maps only the subsetted fastq files even when they are in the same directory as the full fastq files from the course dataset. Don’t hesitate to attend the TA help session if you need assistance.