deco: Decomposing Heterogeneous Cohorts using Omic Data Profiling

Question

[Ana]

Hello!

I'm trying to do a supervised analysis from some data and I always get the same error from the decoRDA function:

sub_binary <- decoRDA(
    data = se, classes = classes.DIAGNOSIS, q.val = 0.05,
    iterations = 1000, rm.xy = TRUE, r = NULL, 
    control = "FERTILE", annot = TRUE, bpparam = SnowParam(),
    id.type = "SYMBOL", pack.db = "Homo.sapiens"
)

'temp' folder will be created to store internal loop data.
 08:12:30  All features are placed on X or Y chromosome,
                       filter will not be applied.

 Classes vector defined as input.
            SUPERVISED analysis will be carry out.

 08:12:30 -- Resampling design:
 Binary analysis for 69 samples.
 Control or 0 --> ' FERTILE ' with 59 samples.
 Case or 1    --> ' SIMPLE_INFERTILITY ' with 10 samples.
 Resampling size for both classes: 3 
 adj.p.value threshold: 0.05
 08:12:30 -- Randomly selected 1000 iterations.
 08:14:25 -- Summarizing results...
  |============================================================================================================| 100%
Error in rowSums(UP[, seq_len(n1)]) > 0 && rowSums(UP[, (n1 + 1):(n1 +  : 
  'length = 10294' in coercion to 'logical(1)'

Can any help me?

Thank you!