igblastr 1.0.23

Rename the following functions:
  compute_imgt_intdata -> compute_V_gene_delineations
  read_V_ndm_data -> read_ndm_data
  write_V_ndm_data -> write_ndm_data
  check_V_ndm_data -> validate_ndm_rows

Author: hpages

DESCRIPTION

@@ -17,7 +17,7 @@ Description: The igblastr package provides functions to conveniently install
 biocViews: Immunology, Immunogenetics, ImmunoOncology, CellBiology
 URL: https://bioconductor.org/packages/igblastr
 BugReports: https://github.com/HyrienLab/igblastr/issues
-Version: 1.0.22
+Version: 1.0.23
 License: Artistic-2.0
 Encoding: UTF-8
 Authors@R: c(
@@ -48,8 +48,8 @@ Collate:
 	file-utils.R
 	loci-utils.R
 	db-utils.R
-	intdata-IO-utils.R
-	compute_imgt_intdata.R
+	ndm_data-IO.R
+	compute_V_gene_delineations.R
 	clean_allele_set.R
 	compute_auxdata.R
 	LATIN_NAMES.R

NAMESPACE

@@ -81,12 +81,14 @@ export(
     ## allele2gene.R:
     allele2gene,
 
-    ## intdata-IO-utils.R:
-    check_V_ndm_data,
-    read_V_ndm_data,
-    write_V_ndm_data,
-
-    ## compute_imgt_intdata.R:
+    ## ndm_data-IO.R:
+    validate_ndm_rows,
+    read_ndm_data,
+    write_ndm_data,
+    same_ndm_data,
+
+    ## compute_V_gene_delineations.R:
+    compute_V_gene_delineations,
     compute_imgt_intdata,
 
     ## compute_auxata.R:
@@ -153,7 +155,6 @@ export(
 
     ## download_OGRDB_germline_json.R:
     download_OGRDB_germline_json,
-    same_intdata,
     makeogrannote,
 
     ## install_OGRDB_germline_db.R:

R/clean_allele_set.R

@@ -90,7 +90,7 @@ checkarg_with.intdata <- function(with.intdata, gapped)
 ### Returns a DNAStringSet object that:
 ### - is parallel to input DNAStringSet object 'dna';
 ### - carries the names and metadata columns of input object 'dna';
-### - also carries the annotations obtained with compute_imgt_intdata()
+### - also carries the annotations obtained with compute_V_gene_delineations()
 ###   in additional metadata columns.
 .annotate_V_alleles <- function(dna)
 {
@@ -102,7 +102,7 @@ checkarg_with.intdata <- function(with.intdata, gapped)
     .check_locus(locus, "the \"locus\" metadata column on 'dna'")
 
     ## Annotate the V alleles based on their gaps.
-    intdata <- compute_imgt_intdata(dna)
+    intdata <- compute_V_gene_delineations(dna)
     stopifnot(identical(names(dna), intdata[ , "allele_name"]))
 
     ## Add "chain_type" column.
@@ -119,7 +119,7 @@ checkarg_with.intdata <- function(with.intdata, gapped)
     stopifnot(is(dna, "DNAStringSet"))
     ## We only care about the annotations found in the Metadata Columns
     ## Of Interest listed in 'MCOI' when comparing the V allele annotations.
-    MCOI <- setdiff(names(IGBLAST_INTDATA_COL2CLASS), "chain_type")
+    MCOI <- setdiff(names(NDM_COL2CLASS), "chain_type")
     ok <- .repeated_vector_elts_have_identical_metadata(dna, MCOI=MCOI)
     if (!ok) {
         msg <- c("V alleles with identical ungapped sequences and names ",
@@ -285,8 +285,8 @@ checkarg_with.intdata <- function(with.intdata, gapped)
 ### Returns a DNAStringSet object that contains the ungapped allele sequences
 ### and carries the metadata columns of input object 'dna', if any.
 ### Furthermore, if 'with.intdata' is TRUE, the returned object will also
-### carry the annotations obtained with compute_imgt_intdata() in additional
-### metadata columns.
+### carry the annotations obtained with compute_V_gene_delineations() in
+### additional metadata columns.
 ### Note that "repeated" alleles (i.e. alleles with identical **ungapped**
 ### DNA sequences **and** names) are dropped.
 ### If, after dropping the "repeated" alleles, the names of the remaining

R/compute_imgt_intdata.R R/compute_V_gene_delineations.RR/compute_imgt_intdata.R renamed to R/compute_V_gene_delineations.R

@@ -68,7 +68,7 @@ clean_imgt_fasta_header_lines  <- function(headers, what="some allele names")
 
 
 ### - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-### compute_imgt_intdata()
+### compute_V_gene_delineations()
 ###
 
 ### The IMGT unique numbering provides a standardized delimitation of
@@ -192,10 +192,10 @@ clean_imgt_fasta_header_lines  <- function(headers, what="some allele names")
 
 ### 'gapped_V_alleles' can be a named DNAStringSet or BStringSet object,
 ### or the path to a FASTA file. Note that **all** the sequences
-### in 'gapped_V_alleles' are expected to have gaps (compute_imgt_intdata()
-### will issue a warning if that's not the case).
+### in 'gapped_V_alleles' are expected to have gaps (the function will
+### issue a warning if that's not the case).
 ### Returns a data.frame with 1 row per sequence in 'gapped_V_alleles'.
-compute_imgt_intdata <- function(gapped_V_alleles, as.IRangesList=FALSE)
+compute_V_gene_delineations <- function(gapped_V_alleles, as.IRangesList=FALSE)
 {
     if (!isTRUEorFALSE(as.IRangesList))
         stop(wmsg("'as.IRangesList' must be TRUE or FALSE"))
@@ -224,8 +224,14 @@ compute_imgt_intdata <- function(gapped_V_alleles, as.IRangesList=FALSE)
 
     names(gapped_V_alleles) <- clean_imgt_fasta_header_lines(allele_names, what)
 
+    ## How many nucleotides sequences are missing on their 3' end
+    ## in order to have a complete FWR3.
+    fwrcdr_max_nucs <- .IMGT_FWRCDR_MAX_LENGTHS * 3L
+    fwr3_trimmed <- sum(fwrcdr_max_nucs) - width(gapped_V_alleles)
+    fwr3_trimmed[fwr3_trimmed < 0L] <- 0L
+
     ## IMGT FWR/CDR fixed intervals in nucleotide space.
-    imgt_bins <- PartitioningByWidth(.IMGT_FWRCDR_MAX_LENGTHS * 3L)
+    imgt_bins <- PartitioningByWidth(fwrcdr_max_nucs)
     midx <- vmatchPattern(GAP_LETTER, gapped_V_alleles)
 
     ## Note that lengths() should propagate the names by default but it
@@ -247,7 +253,8 @@ compute_imgt_intdata <- function(gapped_V_alleles, as.IRangesList=FALSE)
     all_gaps_contained <-
         vapply(all_real_lens, attr, logical(1), "all_gaps_contained")
     coding_frame_start <- 2L - (starting_gap + 2L) %% 3L
-    mcols(IRL) <- DataFrame(coding_frame_start=coding_frame_start,
+    mcols(IRL) <- DataFrame(fwr3_trimmed=fwr3_trimmed,
+                            coding_frame_start=coding_frame_start,
                             starting_gap=starting_gap,
                             all_gaps_in_frame=all_gaps_in_frame,
                             all_gaps_contained=all_gaps_contained)
@@ -256,3 +263,9 @@ compute_imgt_intdata <- function(gapped_V_alleles, as.IRangesList=FALSE)
     .IRL_to_data_frame(IRL)
 }
 
+compute_imgt_intdata <- function(...)
+{
+    .Deprecated("compute_V_gene_delineations")
+    compute_V_gene_delineations(...)
+}
+

R/create_region_db.R

@@ -149,11 +149,11 @@
     internal_data_path <- file.path(destdir, "internal_data")
     stopifnot(!dir.exists(internal_data_path))
 
-    V_ndm_data <- as.data.frame(dna_mcols[ , names(IGBLAST_INTDATA_COL2CLASS)])
-    check_V_ndm_data_col2class(V_ndm_data)
+    ndm_data <- as.data.frame(dna_mcols[ , names(NDM_COL2CLASS)])
+    check_ndm_data_col2class(ndm_data)
     dir.create(internal_data_path)
     destfile <- file.path(internal_data_path, "V.ndm.imgt")
-    write_V_ndm_data(V_ndm_data, destfile)
+    write_ndm_data(ndm_data, destfile)
 }
 
 

R/download_OGRDB_germline_json.R

@@ -156,33 +156,13 @@ makeogrannote <- function(ogrdb_json_file)
                      "in JSON file: ", ogrdb_json_file))
         data <- character(0)
     }
-    col2class <- head(IGBLAST_INTDATA_COL2CLASS, n=-1L)
+    col2class <- head(NDM_COL2CLASS, n=-1L)
     m <- matrix(data, ncol=length(col2class), byrow=TRUE)
     df <- matrix2df(m, col2class)
     cbind(df, coding_frame_start=integer(nrow(df)))
 }
 
 
-### - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-### same_intdata()
-###
-
-### Returns TRUE if the 2 data.frames contain the same intdata (possibly
-### with their rows in different order).
-same_intdata <- function(intdata1, intdata2)
-{
-    if (!identical(dim(intdata1), dim(intdata2)))
-        return(FALSE)
-    allele_names1 <- intdata1[ , "allele_name"]
-    allele_names2 <- intdata2[ , "allele_name"]
-    if (!setequal(allele_names1, allele_names2))
-        return(FALSE)
-    m <- match(allele_names1, allele_names2)
-    intdata2 <- S4Vectors:::extract_data_frame_rows(intdata2, m)
-    identical(intdata1, intdata2)
-}
-
-
 ### - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 ### validate_OGRDB_intdata()
 ###
@@ -207,10 +187,10 @@ same_intdata <- function(intdata1, intdata2)
     }
     stopifnot(length(V_fasta_file) == 1L)
 
-    intdata <- compute_imgt_intdata(V_fasta_file)
+    intdata <- compute_V_gene_delineations(V_fasta_file)
     locus <- extract_loci_from_OGRDB_set_names(organism, names(germline_set))
     intdata$chain_type <- paste0("V", substr(locus, 3L, 3L))
-    intdata[ , names(IGBLAST_INTDATA_COL2CLASS)]
+    intdata[ , names(NDM_COL2CLASS)]
 }
 
 ### Returns the intdata in a data.frame.
@@ -258,6 +238,6 @@ validate_OGRDB_intdata <- function(organism, germline_set, source_set=FALSE,
                                       recache=recache, ...)
 
     ## Compare.
-    same_intdata(intdata1, intdata2)
+    same_ndm_data(intdata1, intdata2)
 }
 

R/intdata-IO-utils.R

@@ -71,7 +71,7 @@ load_intdata <- function(organism, for.aa=FALSE,
     intdata_path <- get_intdata_path(organism, for.aa=for.aa,
                                      domain_system=domain_system,
                                      which=which)
-    read_V_ndm_data(intdata_path)
+    read_ndm_data(intdata_path)
 }