diff --git a/NAMESPACE b/NAMESPACE index 019a2b6dc243ec9d3cc37239995809e78b7ccc2c..84885ea83fb43dbf2c4cc3bdfedecba8dd7d1341 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -45,7 +45,9 @@ export(translate_and_count_stops) export(variant_classifier) export(veganify_asvcounts) export(veganify_generic_wide_tbl) +import(Biostrings) import(DECIPHER) +import(DNAStringSetList) import(dplyr) import(forcats) import(ggplot2) diff --git a/R/variant_classifier.R b/R/variant_classifier.R index dda813384ec0a75c67953c0619b5517dbbc35ea4..4eafec83c86c31f0a6a3bda8a6b7bb1df55ddcbe 100644 --- a/R/variant_classifier.R +++ b/R/variant_classifier.R @@ -8,6 +8,7 @@ #' #' @return A modified master table with variant classifications #' @import dplyr purrr stringr tibble tidyr +#' @import Biostrings DNAStringSetList #' @export variant_classifier <- function( @@ -26,8 +27,8 @@ variant_classifier <- function( # Create a table for clustered sequences and filter out clusters with only one sequence clustab_tbl <- cluster_tbl_named(clustered_sequences) %>% - left_join(tibble(seqnames = unlist(map(clustered_seqs, names)), - seqs = as.character(unlist(clustered_sequences))), + left_join(tibble(seqnames = unlist(map(clustered_sequences, names)), + seqs = as.character(Biostrings:: unlist(clustered_sequences))), by = 'seqnames') %>% dplyr::filter(clus_size > 1)