Chromatin accessibility plays a key role in epigenetic regulation of gene activation and silencing. Open chromatin regions allow regulatory elements such as transcription factors and polymerases to bind for gene expression while closed chromatin regions prevent the activity of transcriptional machinery. Recently, nucleosome occupancy and methylome sequencing (NOMe-seq) has been developed for simultaneously profiling of chromatin accessibility and DNA methylation on single molecules. However, there is no computational method for analyzing NOMe-seq data.
Results: In this article, we present CAME, a seed-extension based approach that identifies chromatin accessibility from NOMe-seq. The efficiency and effectiveness of CAME were demonstrated through comparisons with other existing techniques on both simulated and real data, and the results show that our method not only can precisely identify chromatin accessibility but also outperforms other methods.

Project Activity

See All Activity >

Categories

Bio-Informatics

License

GNU General Public License version 3.0 (GPLv3)

Follow came

came Web Site

Other Useful Business Software
Gen AI apps are built with MongoDB Atlas Icon
Gen AI apps are built with MongoDB Atlas

Build gen AI apps with an all-in-one modern database: MongoDB Atlas

MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
Start Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of came!

Additional Project Details

Intended Audience

End Users/Desktop

User Interface

Command-line

Programming Language

Java

Related Categories

Java Bio-Informatics Software

Registered

2016-01-11