normalizeQuantileSpline.numeric {aroma.light} | R Documentation |
Normalizes the empirical distribution of a single sample to a target distribution.
## S3 method for class 'numeric': normalizeQuantileSpline(x, w=NULL, xTarget, sortTarget=TRUE, ..., robust=TRUE)
x |
a numeric vector of length N. |
w |
an optional numeric vector of length N of weights. |
xTarget |
a numeric vector of length N. |
sortTarget |
If TRUE , argument xTarget is sorted. |
... |
Arguments passed to (smooth.spline
or robustSmoothSpline ), e.g. w
for weights. |
robust |
If TRUE , the normalization function is
estimated robustly. |
Returns a numeric
vector
of length N.
Both argument X
and xTarget
may contain non-finite values.
These values do not affect the estimation of the normalization function.
Non-finite values in X
, remain in the output.
Henrik Bengtsson (http://www.braju.com/R/)
[1] H. Bengtsson, R. Irizarry, B. Carvalho, and T. Speed, Estimation and assessment of raw copy numbers at the single locus level, Bioinformatics, 2008.
Internally either robustSmoothSpline
or
smooth.spline
is used.
normalizeQuantileSpline.matrix
().
*normalizeQuantileRank()
.