Working with BAM files

[deKoch13]

Hi everybody!

This is my first thread in this forum.
Recently, I started an internship in a bioinformatics research group. Unfortunately, I have only little experience regarding programming, bioinformatic data handling, ...
I have basic programming skills in Bash, Python and R, but that's it.

My task is to inspect three BAM files (> 1 Mio reads). The three BAM files were generated using different methods. I want to find out which BAM files contain the same reads, which reads are only in BAM file 1, which reads are missing in BAM file 3 and so on.

Can you give me some advice how to deal with this task? Do you have experiences in BAM file handling?

Many greetings!

[deKoch13]

more details

Maybe I should add some information:
We took one sample and generated the BAM files using three different pipelines.
At the moment, we are only interested in the read names (first column of the BAM files) and want to find out which reads are present in all BAM files, which are present in file 1, file 2, file 3...

[GenoMax]

You could simply get the names (field 1 as you already note, sort | uniq them in bash) and do a "comm" comparison of the three results. If your aim is just to find which reads are present in all three files.

[deKoch13]

progress

Thank you for the answer!

I already extracted the read names from all files separately using:

> samtools sort -n bam_filename | samtools view | awk -F "\t" '{print $1}' > output_filename

Now, my supervisor supposed to use python to do the rest of the task...
Or can you recommend another possibility?

Greetings

[deKoch13]

I looked the "comm" command up. Sounds promising, but I am not sure if this works for such big data files with > 1 Million reads. Do you have an idea for a smart python-based solution?

Nevertheless, I will try it also using comm.

Greetings

[GenoMax]

If this is an assignment then use what you have to but comm should work (as long as you have enough RAM available). Since you are working with only read names (if you are not then you should).