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meaning of "hiseq_info.txt" in Sleuth

Hey all,

In sleuth, what is the meaning of "hiseq_info.txt"???? is it the same as experimental design info.

I am running sleuth as follows;

find the data

> getkdir <- function(id) file.path(base_dir, "results", id, "kallisto")
> base_dir <- system.file("extdata", "", package="sleuthData")
> sample_id <- dir(file.path(base_dir,"results"))
> kal_dirs <- sapply(sample_id, getkdir)
> base_dir <- "~/Desktop/my_lab/Test"

mapping sample

> s2c <- read.table(file.path(base_dir, "meta_data.txt"), header = TRUE, stringsAsFactors=FALSE)


> s2c <- dplyr::select(s2c, sample=run_accession, condition)

what is {sample=run_accession}?? what it means exactly? did I miss a step here? or I need to have sleuth installed to work?

Error: Can't subset columns that don't exist.
x Column `run_accession` doesn't exist.
Run `rlang::last_error()` to see where the error occurred.
> `rlang::last_error()`
Error: object 'rlang::last_error()' not found
> rlang::last_error()
<error/vctrs_error_subscript_oob>
Can't subset columns that don't exist.
x Column `run_accession` doesn't exist.
Backtrace:
  1. dplyr::select(s2c, sample = run_accession, condition)
  2. dplyr:::select.data.frame(s2c, sample = run_accession, condition)
  3. tidyselect::eval_select(expr(c(...)), .data)
  4. tidyselect:::eval_select_impl(...)
 12. tidyselect:::vars_select_eval(...)
 13. tidyselect:::walk_data_tree(expr, data_mask, context_mask)
 14. tidyselect:::eval_c(expr, data_mask, context_mask)
 15. tidyselect:::reduce_sels(node, data_mask, context_mask, init = init)
 16. tidyselect:::walk_data_tree(new, data_mask, context_mask)
 17. tidyselect:::as_indices_sel_impl(...)
 18. tidyselect:::as_indices_impl(x, vars, strict = strict)
 19. tidyselect:::chr_as_locations(x, vars)
 20. vctrs::vec_as_location(x, n = length(vars), names = vars)
 22. vctrs:::stop_subscript_oob(...)
 23. vctrs:::stop_subscript(...)
Run `rlang::last_trace()` to see the full context.
>
rna-seq

Do you try to run your data or the example data?

1 answer

Hey Fatemah, I know you wrote this over a year ago but I am going to leave an answer for others who run into the same problem.

The link to the example data in the sleuth tutorial is broken. If you are using your own data or data downloaded directly from GEO, and you get to this point in the tutorial, this line associates the samples with their treatment conditions.

To run this line of code: "s2c <- dplyr::select(s2c, sample=run_accession, condition)", you don't need to have sleuth loaded yet. Instead, the table you loaded into s2c has to have the columns "run_accession" and "condition" as the "select" command here is grabbing columns with those names.

Alternatively, if your table had column titles like "sample.name" and "experimental.group", then you would change the line of code to s2c <- dplyr::select(s2c, sample=sample.name, experimental.group).

Hope this helps somebody down the road!

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