dStructGuided {dStruct} | R Documentation |
This function takes as input reactivity profiles for a transcript region from samples of two groups. First, it regroups the samples into homogeneous and heteregenous sub-groups, which are used to compute the within-group and between-group nucleotide-wise d scores. If the region meets the quality criteria, the between- and within-group d scores are compared using the Wilcoxon signed-rank test. The resulting p-values quantify the significance of difference in reactivity patterns between the two input groups.
dStructGuided( rdf, reps_A, reps_B, batches = FALSE, within_combs = NULL, between_combs = NULL, check_quality = TRUE, quality = "auto", evidence = 0 )
rdf |
Dataframe of reactivities for each sample. Each column must be labelled as A1, A2, ..., B1, B2, ... |
reps_A |
Number of replicates of group A. |
reps_B |
Number of replicates of group B. |
batches |
Logical suggesting if replicates of group A and B were performed in batches and are labelled accordingly. If TRUE, a heterogeneous/homogeneous subset may not have multiple samples from the same batch. |
within_combs |
Data.frame with each column containing groupings of replicates of groups A or B, which will be used to assess within-group variation. |
between_combs |
Dataframe with each column containing groupings of replicates of groups A and B, which will be used to assess between-group variation. |
check_quality |
Logical, if TRUE, check regions for quality. |
quality |
Worst allowed quality for a region to be tested. |
evidence |
Minimum evidence of increase in variation from within-group comparisons to between-group comparisons for a region to be tested. |
p-value for the tested region (estimated using one-sided Wilcoxon signed rank test) and the median of nucleotide-wise difference of between-group and within-group d-scores.
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 Wan et al., 2014 data data(wan2014) #Run dStruct in the guided mode on first region in wan2014. dStructGuided(wan2014[[1]], reps_A = 2, reps_B = 1)