epiclass

Optimizing and predicting performance of DNA methylation biomarkers using sequence methylation density information.

https://github.com/bmill3r/epiclass

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
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.zenodo.json file
✓
DOI references
Found 2 DOI reference(s) in README
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Academic publication links
✓
Committers with academic emails
2 of 3 committers (66.7%) from academic institutions
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (5.5%) to scientific vocabulary

Last synced: 11 months ago · JSON representation

Repository

Optimizing and predicting performance of DNA methylation biomarkers using sequence methylation density information.

Basic Info

Host: GitHub
Owner: bmill3r
Language: Jupyter Notebook
Default Branch: master
Homepage:
Size: 51.2 MB

Statistics

Stars: 2
Watchers: 2
Forks: 2
Open Issues: 2
Releases: 0

Created almost 7 years ago · Last pushed over 3 years ago

Metadata Files

Readme

README.md

EpiClass

Quick Installation:

note: built with python==3.7 recommend installing in conda environment first.

conda create -n name python==3.7 pip

pip install EpiClass

readthedocs.com documentation:

https://epiclass.readthedocs.io/en/latest/index.html

check out the preprint for more information:

https://doi.org/10.1101/579839

For a deeper look into the code and generating the figures in the manuscript, check out the vignette on GitHub:

https://github.com/bmill3r/EpiClass/blob/master/manuscript_figures/vignette/README_Vignette.ipynb

Owner

Login: bmill3r
Kind: user
Location: Baltimore, MD
Company: Johns Hopkins Univeristy

Website: https://bmill3r.github.io/
Repositories: 24
Profile: https://github.com/bmill3r

Computational Biologist with experience in Spatial Transcriptomics and Cancer Epigenetics. Wet lab/molecular -> computational 🧬🧫🔬💻

GitHub Events

Total

Last Year

Committers

Last synced: almost 3 years ago

All Time

Total Commits: 54
Total Committers: 3
Avg Commits per committer: 18.0
Development Distribution Score (DDS): 0.259

Past Year

Commits: 1
Committers: 1
Avg Commits per committer: 1.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
bmill3r	b**r@g**m	40
Alexander Goncearenco	g**e@n**v	8
Miller	m**2@h**v	6

Committer Domains (Top 20 + Academic)

hg-01842668-lm2.nih.gov: 1 nih.gov: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time

Total issues: 2
Total pull requests: 3
Average time to close issues: 3 months
Average time to close pull requests: about 1 hour
Total issue authors: 1
Total pull request authors: 1
Average comments per issue: 0.0
Average comments per pull request: 0.0
Merged pull requests: 2
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

neksa (2)

Pull Request Authors

neksa (3)

Top Labels

Issue Labels

enhancement (1)

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- pypi 6 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 5
Total maintainers: 1

pypi.org: epiclass

Optimizing and predicting performance of DNA methylation biomarkers using sequence methylation density information.

Homepage: https://github.com/bmill3r/EpiClass
Documentation: https://epiclass.readthedocs.io/
License: Public Domain
Latest release: 2.2.5
published over 6 years ago

Versions: 5
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 6 Last month

Rankings

Dependent packages count: 10.0%

Forks count: 19.1%

Dependent repos count: 21.7%

Average: 22.6%

Stargazers count: 27.8%

Downloads: 34.1%

Maintainers (1)

bmill3r

Last synced: 11 months ago