Getting started with BAM tools

[qnc]

Hi I have a question do I run BAM tools under unix or from a web browser with the applications on them.

Very confused about how to get started.

I see commands but I don't know where to enter them.

[maubp]

Do you mean BamTools (C++)?

Or BAM tools in the general sense, e.g. samtools, Picard, etc?

Either way, you will need to download and install software locally - typically this means Linux or Unix (e.g. Mac OS X), but things like BAM viewers generally also work on Windows (via Java).

[qnc]

Yes this sound like it..

want to be able to take the BAM files I have on UCSC and Compare them with SNP annotators and find gaps and produce histograms of coverage so I can see areas of weakness for further investigation.

We are starting in Next Gen so there is lots to learn but its exciting so we hope we can get to the line command stage and try things out to get the data we want.

Where do I download the tools from and are there easy non technical instructions around.


Thanks for the help btw.

[maubp]

There are graphical viewers for SAM/BAM files, e.g. IGV and Tablet.

http://www.broadinstitute.org/software/igv/home

http://bioinf.hutton.ac.uk/tablet/

Then there are command line tools for working with SAM/BAM files, e.g. samtools
http://samtools.sourceforge.net

You'd best well advised to scan these forums for tips etc... but also you'll benefit in the long run from general Unix command line skills. If you are at a university, there may be some courses on this (possibly in the Computer Science department).

[qnc]

We got IGV viewer working and we uploaded BAM files to UCSC Genome browser. We also managed to get a SNP track of the Seattle Seq info from the BAM files so that is why we wanted to look at BAMTools to compare what UCSC annotates as a possible change vs Seattle Seq and others.

We also wanted a histogram of coverage and more as we go along.

Its generally learning to manipulate cross reference and put in context our Next Gen data as it comes along.

Here is the UCSC session to give you an idea Purple was the Seattle Seq results and you can zoom into to see a local annotation showed up lost more SNPs and UCSC even more. http://goo.gl/7o4Il