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https://doi.org/10.1101/433763
> Recent advances in deep learning, particularly unsupervised approaches, have shown promise for furthering our biological knowledge through their application to gen…
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we should look at this...
| MGA repository: a curated data resource for ChIP-seq and other genome annotated data.
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| Dréos R, Ambrosini G, Groux R, Périer RC, Bucher P.
| Nucleic …
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Hi,
I have GWAS summary data and individual level data in the same cohort, also have DNA methylation prediction models. I use GWAS summary data to run Predict.py, get the methylation-level associati…
ymqwa updated
2 years ago
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Hi, Dr. Lee
First off, thank you for developing this incredible toolkit for calculating several measures from which we are able to infer DNA methylation heterogeneity of the sample. Just like the p…
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Hello!
I have used this program to extract the DNA methylation levels from data and have bam outputs. I am trying to analyze where methylation is occurring on the genome, but the annotations of the…
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Hi Alan,
I've returned with another question. I know that you say that Nanodisco requires ONT sequenced WGA DNA for the methylation-free dataset. However, would data generated from the Rapid PCR Ba…
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Update the following URL to point to the GitHub repository of
the package you wish to submit to _Bioconductor_
- Repository: https://github.com/nshen7/vmrseq
Confirm the following by editing ea…
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Hi,
I am trying to compare DNA methylation over set of genomic regions through average profile and heatmap. Is there any control to keep the y-axis same for top annotation in the enrichedheatmap fu…
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a useful feature for the 'select experiments' panel would be to group by category (TF, Histone mark, DNA methylation, ...)
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To compute cell counts based on DNA methylation data, use the 'estimateCellCounts' command in the 'minfi' Bioconductor package:
https://rdrr.io/bioc/minfi/man/estimateCellCounts.html