summit_from_vector | R Documentation |
Determine summit from numeric vector
summit_from_vector(x, spar = 0.5, edge_buffer = 0, return_height = TRUE, ...)
x |
|
spar |
|
edge_buffer |
|
... |
additional arguments are passed to |
This function takes a numeric vector, intended to be data that
represents some signal across a range where that signal is above
noise; it calls smooth.spline()
to generate a smooth curve across
the region, then returns the x position with the max smoothed
spline signal.
The original intent is to take genome sequence coverage across an enriched region (a "peak") and determine the peak summit. It should work well for each row of a coverage matrix, provided the coverage matrix is wide enough that the highest signal is located inside the range analyzed.
The other alternative is to import bigWig coverage data for a set
of regions of interest defined by a GRanges
object.
A useful function is splicejam::getGRcoverageFromBw()
which
can load coverage from one or multiple bigWig files, returning
a GRanges
object with one column per bigWig file loaded.
Then iterate each coverage vector to determine the summit.
integer
vector with two values:
"summit"
with the index position of the highest point
on the smoothed spline curve.
If x
has one uniform numeric value across the entire range,
it returns the midpoint defined by round(length(x)/2)
.
If are two maximum values, the first position is returned.
"summit_height"
numeric
value with the spline height
at the summit position.
Other jam utility functions:
cardinality()
,
color_complement()
,
convert_PD_df_to_SE()
,
convert_imputed_assays_to_na()
,
curate_se_colData()
,
curate_to_df_by_pattern()
,
design2layout()
,
get_numeric_transform()
,
handle_df_args()
,
merge_proteomics_se()
,
nmat_summary()
,
nmatlist_summary()
,
rmd_tab_iterator()
,
rowNormScale()
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