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

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