Coda specifications

Information


Unique identifier OMICS_15427
Name Coda
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Stability Stable
Requirements
Numpy, Scipy, SciKit-learn, Pandas, h5py, rpy2, Keras
Maintained Yes

Download


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Versioning


No version available

Documentation


Maintainer


  • person_outline Anshul Kundaje

Publication for Coda

Coda citation

library_books

Denoising genome wide histone ChIP seq with convolutional neural networks

2017
Bioinformatics
PMCID: 5870713
PMID: 28881977
DOI: 10.1093/bioinformatics/btx243

[…] mpirical fold enrichment by 10 since only 10% of the actual reads were kept), as if that were the case, the correlation would be unchanged. In contrast, when trained on GM12878 and tested on GM18526, Coda accurately recovered high-quality, uncorrupted signal from the corrupted data (). shows a comparison of Coda’s output versus the corrupted and uncorrupted data at the promoter of the EBF1 gene, […]

Coda institution(s)
Department of Computer Science, Stanford University, Stanford, CA, USA; Department of Genetics, Stanford University, Stanford, CA, USA
Coda funding source(s)
Supported by a Hertz Fellowship, an NDSEG Fellowship and by NIH grants DP2-GM-123485 and 1R01ES025009-01.

Coda review

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avilella

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Desktop
The github repo could do with some examples on how to produce the input files.