I have three different groups of gene sets (Control, Treat1 , Treat 2), and for TFBS prediction of each group, I have tried to run FIMO(= Find Individual Motif Occurrences ) for each group from MEME suit. For individual transcription factors, HOCOMOCO data was used with their official TF name.

With result of FIMO, I have acquired multiple grange objects. As there are 763 TF from HOCOMOCO, I will have around 3763 each promotor seq.

So my question will be,

1. Would be ideal to merge all the dataset from each group ?
2. If yes, how should I merge this multiple grange object?
3. For interpretation of fimo result, would it be wise to compare motif occurence?
4. Is there any better way to compare TFBS prediction from different groups of gene set, only with their name. (not with chip data)

• targeted sequences are was upstream 5k downstream 3k from TSS

Example of code for fimo :

  dummyseq <- getSeq(BSgenome.Hsapiens.UCSC.hg38, found_PR)
  writeXStringSet(dummyseq, file="DummySeq.fasta")

  foo_dummy<- MotifDb::MotifDb %>%  # Query the database for the HOCOMOCO motif using it's gene name
  MotifDb::query(HOCOMOCO$`Transcription factor`[1]) %>%  # Convert from motifdb format to universalmotif format
  universalmotif::convert_motifs() %>%  
 .[[1]]         # The result is a list, to simplify the object, return it as a single universalmotif

  Foo_dummy_Fimo_result_CT <- runFimo(DummySeq.fasta, foo_dummy)

  class(Foo_dummy_Fimo_result_CT) # grange 

  length(Foo_dummy_Fimo_result_CT) # 1428