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1. BLASTing from a container

-- | TOC | Episode 2 >>

Objectives

This episode will introduce containers for bioinformatics by showcasing a practical real use case.

Do not worry at this stage if the commands you are running are unclear, they will be discussed in detail in Episode 2.

Getting ready

It is assumed that all commands are executed in a Unix-like terminal.

All the materials for this workshop, including tutorials and scripts, are available on GitHub. Run the following command to get them in the current directory:

git clone https://github.com/PawseySC/bio-workshop-18.git

In this first Episode we'll be running a BLAST (Basic Local Alignment Search Tool) example with a container from BioContainers.

To begin, we'll move to the directory:

cd bio-workshop-18/episode1_blast

There is a script, blast-demo.sh, that will run all the commands if you want. Otherwise, you can follow along below.

Setting up the container

To start we'll pull the BLAST container (this will take up to several minutes):

docker pull biocontainers/blast:v2.2.31_cv2

The output will look like:

v2.2.31_cv2: Pulling from biocontainers/blast
22dc81ace0ea: Pull complete 
1a8b3c87dba3: Pull complete 
...
Status: Downloaded newer image for biocontainers/blast:v2.2.31_cv2

That's it! BLAST is ready to run.

A quick check

We can run a simple command to verify the container works:

docker run biocontainers/blast:v2.2.31_cv2 blastp -help

USAGE
  blastp [-h] [-help] [-import_search_strategy filename]
...
 -use_sw_tback
   Compute locally optimal Smith-Waterman alignments?

Running BLAST on a sample dataset

Let's copy some data over to start working with:

cp -p ../data_files/P04156.fasta .
cp -p ../data_files/zebrafish.1.protein.faa.gz .
gunzip zebrafish.1.protein.faa.gz

This is a human prion FASTA sequence along with a reference database we'll blast against. We need to prepare the zebrafish database with makeblastdb. Do not worry about all of the flags we are using, we will explain them in detail in Episode 2:

docker run --rm -v $(pwd):/data/ -w /data biocontainers/blast:v2.2.31_cv2 makeblastdb -in zebrafish.1.protein.faa -dbtype prot

We can now run BLAST and compare our data against the database:

docker run --rm -v $(pwd):/data/ -w /data biocontainers/blast:v2.2.31_cv2 blastp -query P04156.fasta -db zebrafish.1.protein.faa -out results.txt

The final results are stored in results.txt:

less results.txt

This will display:

BLASTP 2.2.31+


Reference: Stephen F. Altschul, Thomas L. Madden, Alejandro A.
Schaffer, Jinghui Zhang, Zheng Zhang, Webb Miller, and David J.
Lipman (1997), "Gapped BLAST and PSI-BLAST: a new generation of
protein database search programs", Nucleic Acids Res. 25:3389-3402.

...
                                                                     Score     E
Sequences producing significant alignments:                          (Bits)  Value

 XP_017207509.1 protein piccolo isoform X2 [Danio rerio]             43.9    2e-04
 XP_017207511.1 mucin-16 isoform X4 [Danio rerio]                    43.9    2e-04
 XP_021323434.1 protein piccolo isoform X5 [Danio rerio]             43.5    3e-04
 XP_017207510.1 protein piccolo isoform X3 [Danio rerio]             43.5    3e-04
 XP_021323433.1 protein piccolo isoform X1 [Danio rerio]             43.5    3e-04
 XP_009291733.1 protein piccolo isoform X1 [Danio rerio]             43.5    3e-04
 NP_001268391.1 chromodomain-helicase-DNA-binding protein 2 [Dan...  35.8    0.072
...

You can press the space bar to go forward with displaying the contents of the file, and then q to exit and return to the shell prompt.

Conclusion

We have installed BLAST and run it on a sample dataset with just three commands, corresponding to:

  1. Pulling (download) the container;
  2. Preparing the database using the container;
  3. Running the alignment query using the container.

-- | TOC | Episode 2 >>