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Objectives

In this lab, you will explore a popular fast mapper called BWA. Simulated RNA-seq data will be provided to you; the data contains 75 bp paired-end reads that have been generated in silico to replicate real gene count data from Drosophila. The data simulates two biological groups with three biological replicates per group (6 samples total).  The objectives of this lab is mainly to:

  • Learn how BWA works and how to use it.

Introduction

BWA (the Burrows-Wheeler Aligner) is a fast short read aligner. It is an unspliced mapper. As the name suggests, it uses the burrows-wheeler transform to perform alignment in a time and memory efficient manner.

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Six raw data files have been provided for all our further RNA-seq analysis:

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  • c1_r1, c1_r2, c1_r3 from the first biological condition

  • c2_r1, c2_r2, and c2_r3 from the second biological condition

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Get set up for the exercises
Code Block
cds
cd my_rnaseq_course
cd day_2/bwa_exercise

Lets look at the data files and reference files

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Get set up for the exercises
Code Block
ls ../data
ls ../reference
 
#transcriptome
head ../reference/transcripts.fasta 
#see how many transcripts there are in the file
grep -c '^>' ../reference/transcripts.fasta
 
#genome
head ../reference/genome.fa
#see how many sequences there are in the file
grep -c '^>' ../reference/genome.fa
   
 
#annotation
head ../reference/genes.formatted.gtf
#see how many entries there are in this file
wc -l ../reference/genes.formatted.gtf

Run BWA

Load the module:

Code Block
module load biocontainers
module load bwa

#to get the full pathcommand for running bwa from the container
type bwa

You can see the different commands available under the bwa package from the command line help:

Code Block
singularity exec ${BIOCONTAINER_DIR}/biocontainers/bwa/bwa-0.7.17--pl5.22.0_2.simg bwa 
#this may need to run in an idev session since biocontainer modules cannot be run on the login nodes.

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Code Block
singularity exec ${BIOCONTAINER_DIR}/biocontainers/bwa/bwa-0.7.17--pl5.22.0_2.simg bwa index -a bwtsw ../reference/transcripts.fasta

Part 2. Align the samples to reference using bwa mem

 Running alignment using the newest and greatest, BWA MEM to the transcriptome. Alignment is just one single step with bwa mem.

Warning

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Submit to the TACC queue or run in idev session

Create a commands file and use launcher_creator.py followed by sbatch.

Make sure each command is one line in your commands file.

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Put this in your commands file
Code Block
nano commands.mem
 
#Enter these lines into the file
singularity exec ${BIOCONTAINER_DIR}/biocontainers/bwa/bwa-0.7.17--pl5.22.0_2.simg bwa mem -o C1_R1.mem.sam ../reference/transcripts.fasta ../data/GSM794483_C1_R1_1.fq ../data/GSM794483_C1_R1_2.fq 
singularity exec ${BIOCONTAINER_DIR}/biocontainers/bwa/bwa-0.7.17--pl5.22.0_2.simg bwa mem -o C1_R2.mem.sam ../reference/transcripts.fasta ../data/GSM794484_C1_R2_1.fq ../data/GSM794484_C1_R2_2.fq 
singularity exec ${BIOCONTAINER_DIR}/biocontainers/bwa/bwa-0.7.17--pl5.22.0_2.simg bwa mem -o C1_R3.mem.sam ../reference/transcripts.fasta ../data/GSM794485_C1_R3_1.fq ../data/GSM794485_C1_R3_2.fq 
singularity exec ${BIOCONTAINER_DIR}/biocontainers/bwa/bwa-0.7.17--pl5.22.0_2.simg bwa mem -o C2_R1.mem.sam ../reference/transcripts.fasta ../data/GSM794486_C2_R1_1.fq ../data/GSM794486_C2_R1_2.fq 
singularity exec ${BIOCONTAINER_DIR}/biocontainers/bwa/bwa-0.7.17--pl5.22.0_2.simg bwa mem -o C2_R2.mem.sam ../reference/transcripts.fasta ../data/GSM794487_C2_R2_1.fq ../data/GSM794487_C2_R2_2.fq  
singularity exec ${BIOCONTAINER_DIR}/biocontainers/bwa/bwa-0.7.17--pl5.22.0_2.simg bwa mem -o C2_R3.mem.sam ../reference/transcripts.fasta ../data/GSM794488_C2_R3_1.fq ../data/GSM794488_C2_R3_2.fq 

#ctrl+X to exit nano
#Y, followed by enter to save file
Expand
titleUse this Launcher_creator command

launcher_creator.py -n mem -t 04:00:00 -j commands.mem -q normal -a OTH21164 -m "module unload xalt;module load biocontainers;module load bwa" -l bwa_mem_launcher.slurm

Expand
titleUse sbatch to submit your job to the queue

sbatch --reservation=

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rna-seq-class-0610 bwa_mem_launcher.slurm

#or if reservation is giving us issues

sbatch bwa_mem_launcher.slurm

Since this will take a while to run, you can look at already generated results at: bwa_mem_results_transcriptome

Alternatively, we can also use bwa to map to the genome (reference/genome.fa).

Now that we are done mapping, lets look at how to assess mapping results.