proximity.RdTakes a set of n "query" elements (GRanges object, e.g. genes) and determines their proximity to m "subject" elements (GRanges object, e.g. regulatory elements) subject to set of rearrangement adjacencies (GRangesList with width 1 range pairs)
proximity(
gg,
query,
subject,
ignore.strand = TRUE,
verbose = F,
mc.cores = 1,
strict.ref = FALSE,
chunksize = NULL,
max.dist = 1e+06
)gGraph of the "alternate genome"
GRanges of "intervals of interest" eg regulatory elements
GRanges of "intervals of interest" eg genes
whether to ignore strand of input GRanges. Default: True
logical flag, verbose output. Default: False
how many cores to use for the path exploration step or if chunksize is provided, across chunks. Default: 1
Boolean, only use actual reference edges in graph. Default: False
chunks to split subject and query into to minimize memory usage, if mc.cores>1 then each chunk will be allotted a core. Default: NULL
maximum genomic distance to store and compute (1MB by default) should the maximum distance at which biological interactions may occur. Default: 1e6
gWalk object each representing a proximity
This analysis makes the (pretty liberal) assumption that all pairs of adjacencies that can be linked on a gGraph path are in cis (i.e. share a chromosome) in the tumor genome.
Each output proximity is a gWalk that connects query-subject on the genome described by gGraph gg. Each gWalk is annotated by the metadata of the corresponding query-subject GRanges pair as well as fields "altdist" and "refdist" specifying the "alternate and "reference" gGraph distance of the query-subject pair. The gWalk metadata field "reldist" specifies the relative distance (i.e. ratio of altdist to refdist) for that walk.
For more details follow the Proximity Analysis in the gGnome Tutorial: