Chris Miller chrisamiller

Introduction

In this exercise, you will analyze RNA-seq data from a p53 activation experiment. Cells were either mock-treated (control) or exposed to ionizing radiation (IR), which activates the p53 tumor suppressor pathway. There are 4 biological replicates per condition (8 samples total).

Data was obtained from https://github.com/pacthoen/BMW2_RNA_clust_vis. To get a copy, drop into a terminal, and download the following files:

wget https://raw.githubusercontent.com/pacthoen/BMW2_RNA_clust_vis/refs/heads/main/data/p53_mock_1.csv
wget https://raw.githubusercontent.com/pacthoen/BMW2_RNA_clust_vis/refs/heads/main/data/p53_mock_2.csv
wget https://raw.githubusercontent.com/pacthoen/BMW2_RNA_clust_vis/refs/heads/main/data/p53_mock_3.csv

Working with FASTQs on the command line

We're going to work with data from a human cell line posted here: https://storage.googleapis.com/bfx_workshop_tmp/Exome_Tumor.tar

Make a directory called "week03", and download the tarball to your computer using the command line (wget or curl).
Use tar -xvf to extract the directory from the tar file, then cd into the directory and look around with ls. We're not going to use all of this data in this week's homework. Let's focus on the contents of Exome_Tumor.tar. Untar it, then unzip the fastq files.
Look at the first three records (not first three lines!) of each fastq file. Take a close look at the read names and how they match up across files.

Using Docker

On your laptop:

docker pull ubuntu

What is that doing? It's going to https://hub.docker.com/_/ubuntu and pulling down the image with the "latest" tag

docker run ubuntu

Germline Variant Calling and filtering

Module objectives

Perform single-sample germline variant calling with GATK HaplotypeCaller and the GATK GVCF workflow on exome data
Perform joint genotype calling on exome data, including additional exomes from 1000 Genomes Project
Manipulate and Filter VCFs to remove artifacts and identify variants of interest

In this module we will use the GATK HaplotypeCaller to call germline variants from "normal" bams. For a more in-depth look, see this excellent GATK tutorial, provided by the Broad Institute.

Long Read Alignment

Let's start by looking at some outputs of long read sequencing from the Oxford Nanopore (ONT) platform. These are sequences from the K562 cell line, prepared with the ONT cDNA sequencing kit (poly-A selected). Off the machines, the data will consist of a FAST5 or POD5 file, which are a compressed representation of the raw signal. These are subsequently run through a basecalling algorithm (such as Dorado) to generate FASTQ files.

The choice of basecalling algorithm and parameters goes pretty deep, so we'll assume that reasonable choices have been made. For simplicity, we've also subset the data to include just small portions of the genome, including a few genes of interest.

Go ahead and pull down this fastq file:

wget https://storage.googleapis.com/bfx_workshop_tmp/k562_ont_raw.fastq.gz

Somatic Variant calling

Gather your inputs.

Start by gathering some data. Navigate to a somatic folder and pull down a set of input data from (human build38) from this location:

wget https://storage.googleapis.com/bfx_workshop_tmp/inputs.tar.gz

There are three inputs you need to run a workflow:

A .cwl file that contains the steps to be run
A .yaml file that gives the inputs to that CWL
A config file that tells cromwell about it's environment, how to submit jobs to the cluster, and where to stick the results

Let's start with #3 - the config file. I've made this easy for you. Create a directory where you want to run things, then inside of it, run the following command:

/storage1/fs1/timley/Active/aml_ppg/src/utilities/create_cromwell_config -o cromwell.config -l logs -d output -q timley -G compute-timley```

New employee setup

Tasks

Join the mgibio Slack. Ask any user to invite you using your wustl address, or email c.a.miller@wustl.edu. Excellent place to post questions about anything and get answers. Useful channels include #bfx-workshop, #analysis-workflows, #cancergenomics, and #docker
Get compute1 access set up. This requires a ticket to the RIS Servicedesk requesting to be added to the appropriate compute and storage groups
VPN access Connect to msvpn.wusm.wustl.edu through Cisco AnyConnect. Use WUSTL key log in and submit request at https://it.wustl.edu/items/connect/
Set up compute1 config files (Need a link for this - env variables, etc)
Sign up for the bfx_workshop get on the [email list](https://outlook.office365.com/owa/bioinformatics@gowustl.onmicrosoft.com/groupsubscription.ashx?action=join&source=MSExchange/LokiServer&guid=

RNAseq team (Sid)

Add RNAseq sanity/QC checks https://github.com/genome/analysis-workflows/issues/904
Add input type fastqs to RNA seq https://github.com/genome/analysis-workflows/issues/932

	## New employee setup
	### Tasks

	- Join the mgibio Slack. Ask any user to invite you using your wustl address, or email [c.a.miller@wustl.edu](mailto:c.a.miller@wustl.edu). Excellent place to post questions about anything and get answers. Useful channels include #bfx-workshop, #analysis-workflows, #cancergenomics, and #docker
	- Get compute1 access set up. This requires a ticket to the [RIS Servicedesk](https://jira.ris.wustl.edu/servicedesk/customer/portal/1) requesting to be added to the appropriate compute and storage groups
	- VPN access Connect to msvpn.wusm.wustl.edu through Cisco AnyConnect. Use WUSTL key log in and submit request at [https://it.wustl.edu/items/connect/](https://it.wustl.edu/items/connect/)
	- Set up compute1 config files (_Need a link for this - env variables, etc_)
	- Sign up for the bfx_workshop get on the [email list](https://outlook.office365.com/owa/bioinformatics@gowustl.onmicrosoft.com/groupsubscription.ashx?action=join&source=MSExchange/LokiServer&guid=