<b>Statistical modeling of immunoprecipitation efficiency of MeRIP-seq data enabled accurate detection and quantification of epitranscriptome</b>

The MeRIP-seq datasets used in the study titled <i>"Statistical modeling of immunoprecipitation efficiency of MeRIP-seq data enables accurate detection and quantification of epitranscriptome"</i> 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 <code>data/u2os-DAA.rds</code>, and the m6A sites Grange object is located in <code>data/m6Asites_81519_singlebase.rds</code>. Note that the U2OS dataset uses the hg19 genome assembly.For the other datasets, the IP and input read counts are stored in <code>data/SRR(2024-11-24)/Input_counts_108740.rds</code> and <code>data/SRR(2024-11-24)/IP_counts_108740.rds</code>, respectively. The corresponding m6A sites Grange object is located in <code>data/SRR(2024-11-24)/m6A_108740.rds</code>. The <code>colData.rds</code> 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 <code>data/results</code>.<br>Cite:Statistical modeling of immunoprecipitation efficiency of MeRIP-seq data enabled accurate detection and quantification of epitranscriptome - ScienceDirect