PrEMeR-CG – Probabilistic Extension of Methylated Reads at CpG resolution

PrEMeR-CG

:: DESCRIPTION

PrEMeR-CG is a computational approach that harnesses the implicit information associated with library fragment profiles to infer nucleotide-resolution methylation values in addition to read counts data.

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CpG binning quantifies the methylation for each CpG in the genome using aligned reads and a fragment profile.

::DEVELOPER

Ralf Bundschuh’s Statistical Physics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Python

:: DOWNLOAD

 PrEMeR-CG

:: MORE INFORMATION

Citation

PrEMeR-CG: Inferring Nucleotide Level DNA Methylation Values from MethylCap-Seq Data.
Frankhouser DE, Murphy M, Blachly JS, Park J, Zoller MW, Ganbat JO, Curfman J, Byrd JC, Lin S, Marcucci G, Yan P, Bundschuh R.
Bioinformatics. 2014 Aug 31. pii: btu583.

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