m6a_nmf_reduced: Non-negative matrix factorization on m6a predictions from 3...

In dieterich-lab/JACUSA2helper: Post-processing for JACUSA2 output

Non-negative matrix factorization on m6a predictions from 3 miCLIP experiments

Description

Non-negative matrix factorization on m6a predictions from 3 miCLIP experiments

Usage

data(m6a_nmf_results)

Format

a list with results from NMF

Details

description of list items:

• "estim_r"Factorizations for 'x'

• "nmf_matrix"Factorization of 'x' with 'r' that maximizes 'estim_r$measures$silhouette.consensus' and 'estim_r$measures$cophenetic'

• "chosen_rank"Optimal rank

• "chosen_pattern"The pattern that has the highest score

• "reduced_coef"Reduced coefficient matrix.

References

Koh CWQ, Goh YT, Goh WSS. Atlas of quantitative single-base-resolution n6-methyl-adenine methylomes. Nat Commun. 2019; 10:5636. https://doi.org/10.1038/s41467-019-13561-z.

Boulias K, Toczydłowska-Socha D, Hawley BR, Liberman N, Takashima K, Zaccara S, Guez T, Vasseur J-J, Debart F, Aravind L, Jaffrey SR, Greer EL. Identification of the m, javax.xml.bind.jaxbelement@3155288a, am methyltransferase pcif1 reveals the location and functions of m, javax.xml.bind.jaxbelement@72f29a24, am in the transcriptome. Mol Cell. 2019; 75:631–6438. https://doi.org/10.1016/j.molcel.2019.06.006.

Körtel N, Rücklé C, Zhou Y, Busch A, Hoch-Kraft P, Sutandy FXR, Haase J, Pradhan M, Musheev M, Ostareck D, Ostareck-Lederer A, Dieterich C, Hüttelmaier S, Niehrs C, Rausch O, Dominissini D, König J, Zarnack K. Deep and accurate detection of m6a RNA modifications using miclip2 and m6aboost machine learning. Nucleic Acids Res. 2021; 49:92. https://doi.org/10.1093/nar/gkab485.

See Also

JACUSA2helper::m6a_miclip.

Predictions are based on data from:

• Boulias et al. 2019,

• Koh et al. 2019, and

• Koertel et al. 2021.

dieterich-lab/JACUSA2helper documentation built on March 1, 2023, 12:09 a.m.