m6 Aexpress-Reader
m6Aexpress-Reader predicts N6-methyladenosine (m6A)-regulated gene expression by integrating m6A site data and reader binding information within specific biological contexts.
Key Features:
- Integration of m6A sites and reader binding information: Combines m6A site data with reader binding signals to inform expression regulation predictions.
- Utilization of limited MeRIP-seq data: Produces predictions from limited MeRIP-seq datasets profiling transcriptome-wide m6A modifications.
- Weighting by reader binding signal strength: Uses reader binding signal strength as a weighting factor to refine the posterior distribution of estimated regulatory coefficients.
- Identification of reader-specific regulated patterns: Reveals distinct m6A-regulated expression patterns among genes targeted by readers such as YTHDF2 and IGF2BP1/3.
Scientific Applications:
- Cancer research: Characterizes roles and distinct modes of m6A readers like YTHDF2 and IGF2BP1/3 in cancer-associated genes and pathways.
- Gene expression studies: Predicts m6A-regulated genes to analyze gene expression mechanisms in specific cellular or condition-specific environments.
Methodology:
Integrates m6A site data with reader binding information, applies reader binding signal strength as a weighting factor to refine the posterior distribution of estimated regulatory coefficients, and performs prediction using MeRIP-seq datasets.
Topics
Details
- License:
- Not licensed
- Cost:
- Free of charge
- Tool Type:
- library
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- R
- Added:
- 7/6/2022
- Last Updated:
- 11/24/2024
Operations
Data Inputs & Outputs
Binding site prediction
Inputs
Outputs
Publications
Zhang T, Zhang S, Zhang S, Ma Q. mAexpress-Reader: Prediction of m6A regulated expression genes by integrating m6A sites and reader binding information in specific- context. Methods. 2022;203:167-178. doi:10.1016/j.ymeth.2022.03.008. PMID:35314342.
PMID: 35314342
Funding: - China Postdoctoral Science Foundation: 2020M683568
- National Natural Science Foundation of China: 61473232, 61873202, 62173271