Error when running "counts <- getCount(...)" in Chapter 10.1

[yashi99]

Hi, When running counts <- getCount(...), I got the same error "object 'X4' not found "as shown below.Could you please help to solve it? Besides, I find that when running "m2g <- getMotif2Gene(...)" in Chapter 11, it reported error when I just provided the "japser_motif.txt" downloaded from _https://jaspar.genereg.net/download/data/2022/CORE/JASPAR2022_CORE_non-redundant_pfms_meme.txt_ as input. Is is because the correct input motif file is not this file but should be an output file calculated by my own data?

counts <- getCount(sample_list=c("hESC_rep1","hESC_rep2"), 
                   cut_path="./cut_sites/", 
                   peak_path="./peaks",
                   save_file_path="./",
                   peak_suffix = "_peaks_unique.narrowPeak.bed")

Error in `summarize()`:
i In argument: `sum = sum(X4)`.
i In group 1: `.id.x = 1`.
Caused by error:
! object 'X4' not found
Traceback:

1. getCount(sample_list = c("hESC_rep1", "hESC_rep2", "iMeLC_rep1", 
 .     "iMeLC_rep2", "d1hPGCLC_rep1", "d1hPGCLC_rep2", "d2hPGCLC_rep1", 
 .     "d2hPGCLC_rep2", "d4hPGCLC_rep1", "d4hPGCLC_rep2", "d6hPGCLC_rep1", 
 .     "d6hPGCLC_rep2"), cut_path = "./atac4/cut_sites/", peak_path = "./atac4/peaks", 
 .     save_file_path = "./atac4_downstream_results/", peak_suffix = "_peaks_unique.narrowPeak.bed")
2. lapply(sample_list, function(x) {
 .     cut <- valr::read_bed(sprintf("%s/%s_q30_cut_sites.bed", 
 .         cut_path, x))
 .     res <- valr::bed_map(merged_peaks, cut, sum = sum(X4))[4]
 .     return(res)
 . })
3. FUN(X[[i]], ...)
4. valr::bed_map(merged_peaks, cut, sum = sum(X4))
5. summarize(res_int, !!!quos(...))
6. summarise.grouped_df(res_int, !!!quos(...))
7. summarise_cols(.data, dplyr_quosures(...), by, "summarise")
8. withCallingHandlers({
 .     for (i in seq_along(dots)) {
 .         poke_error_context(dots, i, mask = mask)
 .         context_poke("column", old_current_column)
 .         dot <- dots[[i]]
 .         dot <- expand_pick(dot, mask)
 .         quosures <- expand_across(dot)
 .         quosures_results <- map(quosures, summarise_eval_one, 
 .             mask = mask)
 .         for (k in seq_along(quosures)) {
 .             quo <- quosures[[k]]
 .             quo_data <- attr(quo, "dplyr:::data")
 .             quo_result <- quosures_results[[k]]
 .             if (is.null(quo_result)) {
 .                 next
 .             }
 .             types_k <- quo_result$types
 .             chunks_k <- quo_result$chunks
 .             results_k <- quo_result$results
 .             if (!quo_data$is_named && is.data.frame(types_k)) {
 .                 chunks_extracted <- .Call(dplyr_extract_chunks, 
 .                   chunks_k, types_k)
 .                 types_k_names <- names(types_k)
 .                 for (j in seq_along(chunks_extracted)) {
 .                   mask$add_one(name = types_k_names[j], chunks = chunks_extracted[[j]], 
 .                     result = results_k[[j]])
 .                 }
 .                 chunks <- append(chunks, chunks_extracted)
 .                 types <- append(types, as.list(types_k))
 .                 results <- append(results, results_k)
 .                 out_names <- c(out_names, types_k_names)
 .             }
 .             else {
 .                 name <- dplyr_quosure_name(quo_data)
 .                 mask$add_one(name = name, chunks = chunks_k, 
 .                   result = results_k)
 .                 chunks <- append(chunks, list(chunks_k))
 .                 types <- append(types, list(types_k))
 .                 results <- append(results, list(results_k))
 .                 out_names <- c(out_names, name)
 .             }
 .         }
 .     }
 .     sizes <- .Call(dplyr_summarise_recycle_chunks_in_place, chunks, 
 .         results)
 .     for (i in seq_along(chunks)) {
 .         result <- results[[i]] %||% vec_c(!!!chunks[[i]], .ptype = types[[i]])
 .         cols[[out_names[i]]] <- result
 .     }
 . }, error = function(cnd) {
 .     if (inherits(cnd, "dplyr:::summarise_incompatible_size")) {
 .         action <- "recycle"
 .         i <- cnd$dplyr_error_data$index
 .     }
 .     else {
 .         action <- "compute"
 .         i <- i
 .     }
 .     handler <- dplyr_error_handler(dots = dots, mask = mask, 
 .         bullets = summarise_bullets, error_call = error_call, 
 .         action = action)
 .     handler(cnd)
 . }, warning = dplyr_warning_handler(state = warnings_state, mask = mask, 
 .     error_call = error_call))
9. map(quosures, summarise_eval_one, mask = mask)
10. lapply(.x, .f, ...)
11. FUN(X[[i]], ...)
12. mask$eval_all_summarise(quo)
13. eval()
14. .handleSimpleError(function (cnd) 
  . {
  .     if (inherits(cnd, "dplyr:::summarise_incompatible_size")) {
  .         action <- "recycle"
  .         i <- cnd$dplyr_error_data$index
  .     }
  .     else {
  .         action <- "compute"
  .         i <- i
  .     }
  .     handler <- dplyr_error_handler(dots = dots, mask = mask, 
  .         bullets = summarise_bullets, error_call = error_call, 
  .         action = action)
  .     handler(cnd)
  . }, "object 'X4' not found", base::quote(NULL))
15. h(simpleError(msg, call))
16. handler(cnd)
17. abort(message, class = error_class, parent = parent, call = error_call)
18. signal_abort(cnd, .file)

[tzhu-bio]

This is the same as the previous quantification error reported due to the valr version, I've fixed the bug. Please reinstall cisDynet!

There are some differences between this and the motif file needed in snakemake. It is in jaspar format and can be downloaded from here https://jaspar.genereg.net/download/data/2022/CORE/JASPAR2022_CORE_redundant_pfms_jaspar.txt.

[yashi99]

It works! Thank you so much!