Merge pull request #289 from kymeratx/master

Only pass data.table objects to data.table::melt and data.table::recast

Author: Yenaled

R/bootstrap.R

@@ -418,10 +418,9 @@ process_bootstrap <- function(i, samp_name, kal_path,
       rm(bs_tpm)
       # Make long tidy table; this step is much faster
       # using data.table melt rather than tidyr gather
-      tidy_tpm <- data.table::melt(bs_tpm_df, id.vars = "bootstrap_num",
+      tidy_tpm <- data.table::melt(as.data.table(bs_tpm_df), id.vars = "bootstrap_num",
                                    variable.name = "target_id",
                                    value.name = "tpm")
-      tidy_tpm <- data.table::as.data.table(tidy_tpm)
       rm(bs_tpm_df)
       tidy_tpm$target_id <- as.character(tidy_tpm$target_id)
       tidy_tpm <- merge(tidy_tpm, mappings, by = "target_id",
@@ -458,7 +457,7 @@ process_bootstrap <- function(i, samp_name, kal_path,
     rm(bs_mat)
     # data.table melt function is much faster than tidyr's gather function
     # output is a long table with each bootstrap's value for each target_id
-    tidy_bs <- data.table::melt(bs_df, id.vars = "bootstrap_num",
+    tidy_bs <- data.table::melt(data.table::as.data.table(bs_df), id.vars = "bootstrap_num",
                                 variable.name = "target_id",
                                 value.name = "est_counts")
     rm(bs_df)
@@ -485,8 +484,9 @@ process_bootstrap <- function(i, samp_name, kal_path,
                                           mappings)
     # this step undoes the tidying to get back a matrix format
     # target_ids here are now the aggregation column ids
-    bs_mat <- data.table::dcast(scaled_bs, sample ~ target_id,
+    bs_mat <- data.table::dcast(data.table::as.data.table(scaled_bs), sample ~ target_id,
                                 value.var = "scaled_reads_per_base")
+    bs_mat <- as.data.frame(bs_mat)
     # this now has the same format as the transcript matrix
     # but it uses gene ids
     bs_mat <- as.matrix(bs_mat[, -1])