Mobster

Mobster: a robust tool for Mobile Element Insertion detection in NGS

Brought to you by: djieth

Downloads: 0 This Week

Last Update: 2016-11-25

Get an email when there's a new version of Mobster

Mobster is used to detect novel (non-reference) Mobile Element Insertion (MEI) events in BAM files and uses both a discordant read pair method and a split-read method.

Project Activity

See All Activity >

License

GNU General Public License version 2.0 (GPLv2)

Follow Mobster

Mobster Web Site

Other Useful Business Software

$300 Free Credits for Your Google Cloud Projects Icon

$300 Free Credits for Your Google Cloud Projects

Start building on Google Cloud with $300 in free credits. No commitment, no credit card required until you're ready to scale.

Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.

Start Free Trial

Rate This Project

Login To Rate This Project

User Reviews

Be the first to post a review of Mobster!

Additional Project Details

Programming Language

Registered

2014-04-13

Report inappropriate content

$300 Free Credits for Your Google Cloud Projects

Start building on Google Cloud with $300 in free credits. No commitment, no credit card required until you're ready to scale.

Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.

Start Free Trial

Recommended Projects

Finite Element Method Magnetics
Finite element analysis of electromagnetic devices
MEISE
Native note editor for the MEI encoding format
inGAP
We developed a novel mining pipeline, inGAP, which is guided by a Bayesian principle to detect single nucleotide polymorphisms, insertion and deletions by comparing high-throughput pyrosequencing reads with a reference genome of related organisms.
EJCCMTools
Generation of EJCCM files from SAM/BAM files
popoolationte
PoPoolation TE is a quick and simple pipeline for the analysis of transposable element insertions in (natural) populations using next generation sequencing. PoPoolation TE calculates TE insertion frequencies for TEs that are present in the reference genome as well as for novel TE insertions. PoPoolation TE requires paired-end reads from a pooled population, a reference sequence and transposable element sequences . Documentation: https://sourceforge.net/p/popoolationte/wiki/Main/