misha (version 5.3.1)

gintervals.neighbors.upstream: Directional neighbor finding functions

Description

These functions find neighbors using query strand directionality, where upstream/downstream directionality is determined by the strand of the query intervals rather than the target intervals. This is particularly useful for TSS analysis where you want distances relative to gene direction.

Usage

gintervals.neighbors.upstream(
  query_intervals,
  target_intervals,
  maxneighbors = 1,
  maxdist = 1e+09,
  ...
)
gintervals.neighbors.downstream(
  query_intervals,
  target_intervals,
  maxneighbors = 1,
  maxdist = 1e+09,
  ...
)
gintervals.neighbors.directional(
  query_intervals,
  target_intervals,
  maxneighbors_upstream = 1,
  maxneighbors_downstream = 1,
  maxdist = 1e+09,
  ...
)

Value

gintervals.neighbors.upstream

data frame of upstream neighbors

gintervals.neighbors.downstream

data frame of downstream neighbors

gintervals.neighbors.directional

list with 'upstream' and 'downstream' components

Arguments

query_intervals

intervals with strand information (query intervals)

target_intervals

intervals to search for neighbors

maxneighbors

maximum number of neighbors per query interval (default: 1)

maxdist

maximum distance to search (default: 1e+09)

...

additional arguments passed to gintervals.neighbors

maxneighbors_upstream

maximum upstream neighbors per query interval (default: 1)

maxneighbors_downstream

maximum downstream neighbors per query interval (default: 1)

Details

**Distance interpretation:**

• **Positive strand queries:** upstream distances < 0, downstream distances > 0

• **Negative strand queries:** upstream distances > 0, downstream distances < 0

If no strand column is present, all intervals are treated as positive strand.

See Also

gintervals.neighbors

Examples

# \dontshow{
options(gmax.processes = 2)
# }

gdb.init_examples()

# Create TSS intervals with strand information
tss <- data.frame(
    chrom = c("chr1", "chr1", "chr1"),
    start = c(1000, 2000, 3000),
    end = c(1001, 2001, 3001),
    strand = c(1, -1, 1), # +, -, +
    gene = c("GeneA", "GeneB", "GeneC")
)

# Create regulatory features
features <- data.frame(
    chrom = "chr1",
    start = c(500, 800, 1200, 1800, 2200, 2800, 3200),
    end = c(600, 900, 1300, 1900, 2300, 2900, 3300),
    feature_id = paste0("F", 1:7)
)

# Find upstream neighbors (promoter analysis)
upstream <- gintervals.neighbors.upstream(tss, features,
    maxneighbors = 2, maxdist = 1000
)
print(upstream)

# Find downstream neighbors (gene body analysis)
downstream <- gintervals.neighbors.downstream(tss, features,
    maxneighbors = 2, maxdist = 5000
)
print(downstream)

# Find both directions in one call
both <- gintervals.neighbors.directional(tss, features,
    maxneighbors_upstream = 1,
    maxneighbors_downstream = 1,
    maxdist = 1000
)
print(both$upstream)
print(both$downstream)