Skip to content

README.md

Latest commit

 

History

History
74 lines (52 loc) · 3.66 KB

README.md

File metadata and controls

74 lines (52 loc) · 3.66 KB

AlphaGenome Docker Environment

This Docker image provides a minimal Python environment with AlphaGenome and common data science libraries installed. It is designed to replicate a similar environment to Google Colab for offline or local development.

Included Libraries

  • alphagenome
  • matplotlib
  • pandas
  • numpy
  • flask

Requirements

Build the Image

To build the Docker image:

docker build -t alphagenome-web .

This will create an image named alphagenome-web.

Run an Interactive AlphaGenome Web App

To start an interactive Web app inside the container with your API key, you can pass it as an environment variable:

docker run -it --rm -p 8080:8080 \
  -v $(pwd):/alphagenome \
  -e API_KEY=your_real_api_key_here \
  alphagenome-web

Alternatively, create a .env file in this directory with the following content:

API_KEY=your_real_api_key_here

Then run the container using:

docker run -it --rm -p 8080:8080 \
  -v $(pwd):/alphagenome \
  --env-file .env \
  alphagenome-web

Once the application is running, you can open a web interface where you can input a DNA sequence and run the analysis by visiting http://localhost:8080/ in your browser.

Supported analyses types in AlphaGenome

Output Type Description Data / Interpretation
ATAC Identifies regions of open chromatin using Tn5 transposase Open chromatin; regulatory accessibility
CAGE Captures transcription start sites (TSS) via 5' capped RNAs Promoter activity; precise TSS location
DNASE Maps DNase I hypersensitive sites Regulatory elements like enhancers and promoters
RNA_SEQ Measures gene expression via RNA sequencing Transcript abundance; splicing patterns
CHIP_HISTONE ChIP-seq for histone modifications Epigenetic marks (e.g., H3K27ac, H3K4me3) indicating active regions
CHIP_TF ChIP-seq for transcription factors TF binding sites; regulatory network inference
SPLICE_SITES Annotated or predicted splice donor/acceptor sites Exon-intron boundaries; splicing signals
SPLICE_SITE_USAGE Quantitative usage level of splice sites Splicing dynamics; isoform switching
SPLICE_JUNCTIONS Inferred exon junctions from RNA-seq reads Alternative splicing patterns
CONTACT_MAPS Chromatin interaction data (e.g., Hi-C, Micro-C) 3D genome organization; enhancer-promoter loops
PROCAP High-resolution identification of transcription start sites via run-on cap Active transcription initiation; enhancer activity

License

This project is licensed under the MIT License. See the LICENSE file for details.