plotDStructurome {dStruct} | R Documentation |
Given the table of results from dStruct or dStructGuided and the corresponding lists with reactivity scores for all transcripts, this function saves a PDF file with detailed visualizations of reactivities for all differential regions.
plotDStructurome( rl, diff_regions, outfile, fdr = 0.05, ylim = c(-0.05, 3), del_d_cutoff = 0.01 )
rl |
List of dataframes of reactivities for each sample. |
diff_regions |
Output from dStruct or dStructGuided containing coordinates of regions with significance of differentially reactivity. |
outfile |
The name for pdf file which will be saved. |
fdr |
FDR threshold for plotted regions. |
ylim |
Y-axis limits for plots. |
del_d_cutoff |
Minimum effect size for plotted regions specified in terms of median difference of the between-group and within-group d-scores. |
Saves a PDF for all differentially reactive regions. Returns NULL.
Krishna Choudhary
Choudhary, K., Lai, Y. H., Tran, E. J., & Aviran, S. (2019). dStruct: identifying differentially reactive regions from RNA structurome profiling data. Genome biology, 20(1), 1-26.
#Load data from Lai et al., 2019 data(lai2019) #Run dStruct in de novo discovery mode for all the transcripts in this data in one step. res <- dStructome(lai2019, 3, 2, batches= TRUE, min_length = 21, between_combs = data.frame(c("A3", "B1", "B2")), within_combs = data.frame(c("A1", "A2", "A3")), ind_regions = TRUE, processes = 1) #Plot the significant results and save to a PDF file. plotDStructurome(rl = lai2019, diff_regions = res, outfile = "significantly_differential_regions", fdr = 0.05, ylim = c(-0.05, 3))