makeChangeoClone: Generate a ChangeoClone object for lineage construction

Description

makeChangeoClone takes a data.frame with AIRR or Change-O style columns as input and masks gap positions, masks ragged ends, removes duplicates sequences, and merges annotations associated with duplicate sequences. It returns a ChangeoClone object which serves as input for lineage reconstruction.

Usage

makeChangeoClone(
  data,
  id = "sequence_id",
  seq = "sequence_alignment",
  germ = "germline_alignment",
  v_call = "v_call",
  j_call = "j_call",
  junc_len = "junction_length",
  clone = "clone_id",
  mask_char = "N",
  locus = "locus",
  max_mask = 0,
  pad_end = FALSE,
  text_fields = NULL,
  num_fields = NULL,
  seq_fields = NULL,
  add_count = TRUE,
  verbose = FALSE
)

Value

A ChangeoClone object containing the modified clone.

Arguments

data: data.frame containing the AIRR or Change-O data for a clone. See Details for the list of required columns and their default values.
id: name of the column containing sequence identifiers.
seq: name of the column containing observed DNA sequences. All sequences in this column must be multiple aligned.
germ: name of the column containing germline DNA sequences. All entries in this column should be identical for any given clone, and they must be multiple aligned with the data in the seq column.
v_call: name of the column containing V-segment allele assignments. All entries in this column should be identical to the gene level.
j_call: name of the column containing J-segment allele assignments. All entries in this column should be identical to the gene level.
junc_len: name of the column containing the length of the junction as a numeric value. All entries in this column should be identical for any given clone.
clone: name of the column containing the identifier for the clone. All entries in this column should be identical.
mask_char: character to use for masking and padding.
locus: name of the column containing locus specification. Must be present and only contain the value "IGH", representing heavy chains.
max_mask: maximum number of characters to mask at the leading and trailing sequence ends. If NULL then the upper masking bound will be automatically determined from the maximum number of observed leading or trailing Ns amongst all sequences. If set to 0 (default) then masking will not be performed.
pad_end: if TRUE pad the end of each sequence with mask_char to make every sequence the same length.
text_fields: text annotation columns to retain and merge during duplicate removal.
num_fields: numeric annotation columns to retain and sum during duplicate removal.
seq_fields: sequence annotation columns to retain and collapse during duplicate removal. Note, this is distinct from the seq and germ arguments, which contain the primary sequence data for the clone and should not be repeated in this argument.
add_count: if TRUE add an additional annotation column called collapse_count during duplicate removal that indicates the number of sequences that were collapsed.
verbose: passed on to collapseDuplicates. If TRUE, report the numbers of input, discarded and output sequences; otherwise, process sequences silently.

Details

The input data.frame (data) must columns for each of the required column name arguments: id, seq, germ, v_call, j_call, junc_len, and clone. The default values are as follows:

id = "sequence_id": unique sequence identifier.
seq = "sequence_alignment": IMGT-gapped sample sequence.
germ = "germline_alignment": IMGT-gapped germline sequence.
v_call = "v_call": V segment allele call.
j_call = "j_call": J segment allele call.
junc_len = "junction_length": junction sequence length.
clone = "clone_id": clone identifier.

Additional annotation columns specified in the text_fields, num_fields or seq_fields arguments will be retained in the data slot of the return object, but are not required. If the input data.frame data already contains a column named sequence, which is not used as the seq argument, then that column will not be retained.

The default columns are IMGT-gapped sequence columns, but this is not a requirement. However, all sequences (both observed and germline) must be multiple aligned using some scheme for both proper duplicate removal and lineage reconstruction.

The value for the germline sequence, V-segment gene call, J-segment gene call, junction length, and clone identifier are determined from the first entry in the germ, v_call, j_call, junc_len and clone columns, respectively. For any given clone, each value in these columns should be identical.

Examples

Run this code

# Example data
db <- data.frame(sequence_id=LETTERS[1:4],
                 sequence_alignment=c("CCCCTGGG", "CCCCTGGN", "NAACTGGN", "NNNCTGNN"),
                 germline_alignment="CCCCAGGG",
                 v_call="Homsap IGKV1-39*01 F",
                 j_call="Homsap IGKJ5*01 F",
                 junction_length=2,
                 clone_id=1,
                 locus=rep("IGH", length=4),
                 c_call=c("IGHM", "IGHG", "IGHG", "IGHA"),
                 duplicate_count=1:4,
                 stringsAsFactors=FALSE)


 # Without end masking
 makeChangeoClone(db, text_fields="c_call", num_fields="duplicate_count")

 # With end masking
 makeChangeoClone(db, max_mask=3, text_fields="c_call", num_fields="duplicate_count")