R/vtrack.R
gvtrack.array.slice.RdDefines how a single value within an interval is achieved for a virtual track based on 'Array' track.
gvtrack.array.slice(vtrack = NULL, slice = NULL, func = "avg", params = NULL)virtual track name
a vector of column names or column indices or 'NULL'
see below
None.
A track (regular or virtual) used in a track expression is expected to return one value for each track interval. 'Array' tracks store multiple values per interval (one for each 'column') and hence if used in a track expression one must define the way of how a single value should be deduced from several ones.
By default if an 'Array' track is used in a track expressions, its interval value would be the average of all column values that are not NaN. 'gvtrack.array.slice' allows to select specific columns and to specify the function applied to their values.
'slice' parameter allows to choose the columns. Columns can be indicated by their names or their indices. If 'slice' is 'NULL' the non-NaN values of all track columns are used.
'func' parameter determines the function applied to the columns' values. Use the following table for a reference of all valid functions and parameters combinations:
func = "avg", params = NULL
Average of columns' values.
func = "max", params = NULL
Maximum of columns' values.
func = "min", params = NULL
Minimum of columns' values.
func = "stdev", params = NULL
Unbiased standard deviation of
columns' values.
func = "sum", params = NULL
Sum of columns' values.
func = "quantile", params = [Percentile in the range of [0, 1]]
Quantile of columns' values.
# \dontshow{
options(gmax.processes = 2)
# }
gdb.init_examples()
gvtrack.create("vtrack1", "array_track")
gvtrack.array.slice("vtrack1", c("col2", "col4"), "max")
gextract("vtrack1", gintervals(1, 0, 1000))
#> chrom start end vtrack1 intervalID
#> 1 chr1 0 50 4 1
#> 2 chr1 100 150 102 1
#> 3 chr1 250 300 NaN 1