TS_kernel {ChIPtest} | R Documentation |
Calculate the Test Statistics for kernel-based nonparametric test.
Description
Get the difference between two conditions. Apply Kernel smoothing to fit a smooth curve. Estimate variance for each gene and improve the estimation of variance based on all the genes. Derive test statistics and get the rank list of all the genes.
Usage
TS_kernel(data, band, quantile)
Arguments
data |
difference matrix between two conditions |
band |
bandwidth used in kernel smoothing |
quantile |
threshold used in variance estimation |
Details
Note 1: Need to chose a bandwidth. Do not recommend to use cross validation (not gene-specific bandwidth) but chose a fixed biological meaningful bandwidth. A fixed bandwidth which can capture the signal profile and smooth out noise would be recommend. The bandwidth used in reference is 20/280.
Note 2: quantile value is based on the distribution of variance estimation of each gene. Recommend to use histogram to double check the distribution. Default 0.9 = 90 %
Value
TS |
Kernel based test statistics after WH transformation. Please refer the details in the reference |
TS_sign |
"+" represent for condition B enriched more than condition A; "-" vice versa |
Tmean |
Original test statistics, which is calculated as integral of square of kernel estimator |
References
Qian Wu, Kyoung-Jae Won and Hongzhe Li. (2015) Nonparametric Methods for Identifying Differential Enrichment Regions with ChIP-seq Data. Cancer Informatics
,14 (Suppl 1), 11-22
Examples
data(data1)
data(data4)
Data1=NormTransformation(data1)
Data4=NormTransformation(data4)
data=Data4-Data1
band=54
TS=TS_kernel(data, band, quantile=0.9)