Statistical modeling of immunoprecipitation efficiency of MeRIP-seq data enabled accurate detection and quantification of epitranscriptome

The MeRIP-seq datasets used in the study titled "Statistical modeling of immunoprecipitation efficiency of MeRIP-seq data enables accurate detection and quantification of epitranscriptome" are obtained from GSE122744, GSE48037, and GSE106124.The first two datasets come from heart and liver tissues (GEO accession: GSE122744). The third dataset contains m6A profiling of U2OS cells treated with deazaadenosine (DAA) (GEO accession: GSE48037). The fourth dataset is from HEL cells (GEO accession: GSE106124).The read counts for U2OS are stored in data/u2os-DAA.rds, and the m6A sites Grange object is located in data/m6Asites_81519_singlebase.rds. Note that the U2OS dataset uses the hg19 genome assembly.For the other datasets, the IP and input read counts are stored in data/SRR(2024-11-24)/Input_counts_108740.rds and data/SRR(2024-11-24)/IP_counts_108740.rds, respectively. The corresponding m6A sites Grange object is located in data/SRR(2024-11-24)/m6A_108740.rds. The colData.rds file contains metadata indicating which columns correspond to specific studies, tissues, or cell lines.The code file contains all the code used in the study, and the results are stored in data/results.Cite:Statistical modeling of immunoprecipitation efficiency of MeRIP-seq data enabled accurate detection and quantification of epitranscriptome - ScienceDirect