collapseDuplicates

collapseDuplicates - Remove duplicate DNA sequences and combine annotations

Description¶

collapseDuplicates identifies duplicate DNA sequences, allowing for ambiguous characters, removes the duplicate entries, and combines any associated annotations.

Usage¶

collapseDuplicates(
data,
id = "sequence_id",
seq = "sequence_alignment",
text_fields = NULL,
num_fields = NULL,
seq_fields = NULL,
add_count = FALSE,
fields = NULL,
ignore = c("N", "-", ".", "?"),
sep = ",",
dry = FALSE,
verbose = FALSE
)

Arguments¶

data: data.frame containing Change-O columns. The data.frame must contain, at a minimum, a unique identifier column and a column containing a character vector of DNA sequences.
id: name of the column containing sequence identifiers.
seq: name of the column containing DNA sequences.
text_fields: character vector of textual columns to collapse. The textual annotations of duplicate sequences will be merged into a single string with each unique value alphabetized and delimited by sep.
num_fields: vector of numeric columns to collapse. The numeric annotations of duplicate sequences will be summed.
seq_fields: vector of nucleotide sequence columns to collapse. The sequence with the fewest number of non-informative characters will be retained. Where a non-informative character is one of c("N", "-", ".", "?"). Note, this is distinct from the seq parameter which is used to determine duplicates.
add_count: if TRUE add the column collapse_count that indicates the number of sequences that were collapsed to build each unique entry.
fields: character vector of additional column names used to group sequences prior to identifying duplicates. If specified, sequences will only be collapsed together if they are equivalent in the seq column and also share identical values in every one of the fields columns (see Details). Columns that are not found in data are ignored, with a warning; if none of them are found, all sequences are collapsed together as if fields=NULL.
ignore: vector of characters to ignore when testing for equality.
sep: character to use for delimiting collapsed annotations in the text_fields columns. Defines both the input and output delimiter.
dry: if TRUE perform dry run. Only labels the sequences without collapsing them.
verbose: if TRUE report the number input, discarded and output sequences; if FALSE process sequences silently. When fields is specified, one report is printed for each group of sequences.

Value¶

A modified data data.frame with duplicate sequences removed and annotation fields collapsed if dry=FALSE. If dry=TRUE, sequences will be labeled with the collapse action, but the input will be otherwise unmodified (see Details).

Details¶

collapseDuplicates identifies duplicate sequences in the seq column by testing for character identity, with consideration of IUPAC ambiguous nucleotide codes. A cluster of sequences are considered duplicates if they are all equivalent, and no member of the cluster is equivalent to a sequence in a different cluster.

Textual annotations, specified by text_fields, are collapsed by taking the unique set of values within in each duplicate cluster and delimiting those values by sep. Numeric annotations, specified by num_fields, are collapsed by summing all values in the duplicate cluster. Sequence annotations, specified by seq_fields, are collapsed by retaining the first sequence with the fewest number of N characters.

Columns that are not specified in either text_fields, num_fields, or seq_fields will be retained, but the value will be chosen from a random entry amongst all sequences in a cluster of duplicates.

If fields is specified, sequences are first grouped by the unique combinations of values in the fields columns, and duplicates are then identified separately within each group. As a result, sequences that are otherwise identical, but differ in one or more fields columns (for example, distinct sample_id or c_call isotype assignments), are kept as separate entries rather than being collapsed together. Sequences with an NA value in a fields column are grouped together. When fields is specified, the returned entries are ordered as they appeared in the input, and, if dry=TRUE, the collapse_id values are unique across groups and returned as character values.

An ambiguous sequence is one that can be assigned to two different clusters, wherein the ambiguous sequence is equivalent to two sequences which are themselves non-equivalent. Ambiguous sequences arise due to ambiguous characters at positions that vary across sequences, and are discarded along with their annotations when dry=FALSE. Thus, ambiguous sequences are removed as duplicates of some sequence, but do not create a potential false-positive annotation merger. Ambiguous sequences are not included in the collapse_count annotation that is added when add_count=TRUE.

If dry=TRUE sequences will not be removed from the input. Instead, the following columns will be appended to the input defining the collapse action that would have been performed in the dry=FALSE case.

collapse_id: an identifier for the group of identical sequences. A sequence with collapse_class="ambiguous" belongs to more than one group and receives multiple identifiers delimited by ",".
collapse_class: string defining how the sequence matches to the other in the set. one of "duplicated" (has duplicates), "unique" (no duplicates), "ambiguous_duplicate" (no duplicates after ambiguous sequences are removed), or "ambiguous" (matches multiple non-duplicate sequences).
collapse_pass: TRUE for the sequences that would be retained.
collapse_count: present only when add_count=TRUE. Because no sequences are collapsed during a dry run, this is 1 for every row and does not report sizes of the groups of identical sequences.

Examples¶

# Example data.frame
db <- data.frame(sequence_id=LETTERS[1:4],
sequence_alignment=c("CCCCTGGG", "CCCCTGGN", "NAACTGGN", "NNNCTGNN"),
c_call=c("IGHM", "IGHG", "IGHG", "IGHA"),
sample_id=c("S1", "S1", "S2", "S2"),
duplicate_count=1:4,
stringsAsFactors=FALSE)

# Annotations are not parsed if neither text_fields nor num_fields is specified
# The retained sequence annotations will be random
collapseDuplicates(db, verbose=TRUE)

 FUNCTION> collapseDuplicates
 FIRST_ID> A
    TOTAL> 4
   UNIQUE> 2
COLLAPSED> 1
DISCARDED> 1

  sequence_id sequence_alignment c_call sample_id duplicate_count
1           C           NAACTGGN   IGHG        S2               3
2           A           CCCCTGGG   IGHM        S1               1


# Unique text_fields annotations are combined into a single string with ","
# num_fields annotations are summed
# Ambiguous duplicates are discarded
collapseDuplicates(db, text_fields=c("c_call", "sample_id"), num_fields="duplicate_count", 
verbose=TRUE)

 FUNCTION> collapseDuplicates
 FIRST_ID> A
    TOTAL> 4
   UNIQUE> 2
COLLAPSED> 1
DISCARDED> 1

  sequence_id sequence_alignment    c_call sample_id duplicate_count
1           C           NAACTGGN      IGHG        S2               3
2           A           CCCCTGGG IGHG,IGHM        S1               3


# Use alternate delimiter for collapsing textual annotations
collapseDuplicates(db, text_fields=c("c_call", "sample_id"), num_fields="duplicate_count", 
sep="/", verbose=TRUE)

 FUNCTION> collapseDuplicates
 FIRST_ID> A
    TOTAL> 4
   UNIQUE> 2
COLLAPSED> 1
DISCARDED> 1

  sequence_id sequence_alignment    c_call sample_id duplicate_count
1           C           NAACTGGN      IGHG        S2               3
2           A           CCCCTGGG IGHG/IGHM        S1               3


# Add count of duplicates
collapseDuplicates(db, text_fields=c("c_call", "sample_id"), num_fields="duplicate_count",
add_count=TRUE, verbose=TRUE)

 FUNCTION> collapseDuplicates
 FIRST_ID> A
    TOTAL> 4
   UNIQUE> 2
COLLAPSED> 1
DISCARDED> 1

  sequence_id sequence_alignment    c_call sample_id duplicate_count
1           C           NAACTGGN      IGHG        S2               3
2           A           CCCCTGGG IGHG,IGHM        S1               3
  collapse_count
1              1
2              2


# Use fields to prevent collapsing sequences that differ in sample_id or c_call
collapseDuplicates(db, num_fields="duplicate_count",
fields=c("sample_id", "c_call"), add_count=TRUE, verbose=TRUE)

 FUNCTION> collapseDuplicates
 FIRST_ID> B
    TOTAL> 1
   UNIQUE> 1
COLLAPSED> 0
DISCARDED> 0

 FUNCTION> collapseDuplicates
 FIRST_ID> A
    TOTAL> 1
   UNIQUE> 1
COLLAPSED> 0
DISCARDED> 0

 FUNCTION> collapseDuplicates
 FIRST_ID> D
    TOTAL> 1
   UNIQUE> 1
COLLAPSED> 0
DISCARDED> 0

 FUNCTION> collapseDuplicates
 FIRST_ID> C
    TOTAL> 1
   UNIQUE> 1
COLLAPSED> 0
DISCARDED> 0

  sequence_id sequence_alignment c_call sample_id duplicate_count
1           A           CCCCTGGG   IGHM        S1               1
2           B           CCCCTGGN   IGHG        S1               2
3           C           NAACTGGN   IGHG        S2               3
4           D           NNNCTGNN   IGHA        S2               4
  collapse_count
1              1
2              1
3              1
4              1


# Masking ragged ends may impact duplicate removal
db$sequence_alignment <- maskSeqEnds(db$sequence_alignment)
collapseDuplicates(db, text_fields=c("c_call", "sample_id"), num_fields="duplicate_count", 
add_count=TRUE, verbose=TRUE)

 FUNCTION> collapseDuplicates
 FIRST_ID> A
    TOTAL> 4
   UNIQUE> 1
COLLAPSED> 3
DISCARDED> 0

  sequence_id sequence_alignment         c_call sample_id duplicate_count
1           A           NNNCTGNN IGHA,IGHG,IGHM     S1,S2              10
  collapse_count
1              4