Fig. 2: Comparison of RADICL-seq with similar methods. | Nature Communications

Fig. 2: Comparison of RADICL-seq with similar methods.

From: RADICL-seq identifies general and cell type–specific principles of genome-wide RNA-chromatin interactions

Fig. 2

a Summary of the features that distinguish RADICL-seq from GRID-seq. b Analysis of the read length and mapping outcome. Unique (dark gray) and multi-mapping (blue) reads are reported as percentage of the total number of reads pool. RADICL-seq reads were artificially trimmed down to 20 nt for direct comparison with the GRID-seq dataset. c Assessment of the genomic coverage as a function of the sequencing depth for RADICL-seq (blue) and GRID-seq (yellow). The coverage was calculated for both datasets by sub-sampling with a step of 1,000,000 reads up to the maximum available number of reads. d Distribution of the linear genomic distance between RNA and DNA tags derived from the same read for the GRID-seq (yellow) and RADICL-seq (blue) datasets. Data are presented as mean ± s.d.; statistical significance was calculated with one-sided two-proportions z test; *P ≤ 0.05. e Comparison of Malat1 transcript target DNA loci in mESCs identified by RAP-DNA (yellow), RADICL-seq (grey), and GRID-seq (blue) methods. f Comparison of Rn7sk transcript target DNA loci in mESCs identified by ChIRP-seq (yellow), RADICL-seq (grey), and GRID-seq (blue) methods. All panels were generated using RADICL-seq total dataset. Source data are available in the Source Data File.

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