establish_overlap2d: Establish m:n mapping between interactions from replicate 1...

In idr2d: Irreproducible Discovery Rate for Genomic Interactions Data

Description

This method returns all overlapping interactions between two replicates. For each pair of overlapping interactions, the ambiguity resolution value (ARV) is calculated, which helps to reduce the m:n mapping to a 1:1 mapping. The semantics of the ARV depend on the specified ambiguity_resolution_method, but in general interaction pairs with lower ARVs have priority over interaction pairs with higher ARVs when the bijective mapping is established.

Usage

establish_overlap2d(
  rep1_df,
  rep2_df,
  ambiguity_resolution_method = c("overlap", "midpoint", "value"),
  max_gap = -1L
)

Arguments

rep1_df	data frame of observations (i.e., genomic interactions) of replicate 1, with at least the following columns (position of columns matter, column names are irrelevant): column 1: chr_a character; genomic location of anchor A - chromosome (e.g., "chr3") column 2: start_a integer; genomic location of anchor A - start coordinate column 3: end_a integer; genomic location of anchor A - end coordinate column 4: chr_b character; genomic location of anchor B - chromosome (e.g., "chr3") column 5: start_b integer; genomic location of anchor B - start coordinate column 6: end_b integer; genomic location of anchor B - end coordinate column 7: value numeric; p-value, FDR, or heuristic used to rank the interactions
rep2_df	data frame of observations (i.e., genomic interactions) of replicate 2, with the following columns (position of columns matter, column names are irrelevant): column 1: chr_a character; genomic location of anchor A - chromosome (e.g., "chr3") column 2: start_a integer; genomic location of anchor A - start coordinate column 3: end_a integer; genomic location of anchor A - end coordinate column 4: chr_b character; genomic location of anchor B - chromosome (e.g., "chr3") column 5: start_b integer; genomic location of anchor B - start coordinate column 6: end_b integer; genomic location of anchor B - end coordinate column 7: value numeric; p-value, FDR, or heuristic used to rank the interactions
ambiguity_resolution_method	defines how ambiguous assignments (when one interaction in replicate 1 overlaps with multiple interactions in replicate 2 or vice versa) are resolved. Available methods: "value" interactions are prioritized by ascending or descending value column (see sorting_direction), e.g., if two interactions in replicate 1 overlap with one interaction in replicate 2, the interaction from replicate 1 is chosen which has a lower (if sorting_direction is "ascending") or higher (if "descending") value "overlap" the interaction pair is chosen which has the highest relative overlap, i.e., overlap in nucleotides of replicate 1 interaction anchor A and replicate 2 interaction anchor A, plus replicate 1 interaction anchor B and replicate 2 interaction anchor B, normalized by their lengths "midpoint" the interaction pair is chosen which has the smallest distance between their anchor midpoints, i.e., distance from midpoint of replicate 1 interaction anchor A to midpoint of replicate 2 interaction anchor A, plus distance from midpoint of replicate 1 interaction anchor B to midpoint of replicate 2 interaction anchor B
max_gap	integer; maximum gap in nucleotides allowed between two anchors for them to be considered as overlapping (defaults to -1, i.e., overlapping anchors)

Value

data frame with the following columns:

column 1:	rep1_idx	index of interaction in replicate 1 (i.e., row index in rep1_df)
column 2:	rep2_idx	index of interaction in replicate 2 (i.e., row index in rep2_df)
column 3:	arv	ambiguity resolution value used turn m:n mapping into 1:1 mapping. Interaction pairs with lower arv are prioritized.

Examples

rep1_df <- idr2d:::chiapet$rep1_df
rep1_df$fdr <- preprocess(rep1_df$fdr, "log_additive_inverse")

rep2_df <- idr2d:::chiapet$rep2_df
rep2_df$fdr <- preprocess(rep2_df$fdr, "log_additive_inverse")

# shuffle to break preexisting order
rep1_df <- rep1_df[sample.int(nrow(rep1_df)), ]
rep2_df <- rep2_df[sample.int(nrow(rep2_df)), ]

# sort by value column
rep1_df <- dplyr::arrange(rep1_df, rep1_df$fdr)
rep2_df <- dplyr::arrange(rep2_df, rep2_df$fdr)

pairs_df <- establish_overlap2d(rep1_df, rep2_df)

idr2d documentation built on Nov. 8, 2020, 6:16 p.m.