Description Usage Arguments Details Value Author(s) See Also Examples
This function evaluates the number of regions identified for various settings of min_distance and n_min (see DMRforPairs
). It also summarizes the number of probes available inclusion using a specific setting of recode and the number of probes that is covered by the detected regions.
1 | tune_parameters(parameters,classes_gene,classes_island,targetID, chr, position,m.v,beta.v,recode=1,sep=";",gs,do.parallel=0)
|
parameters |
A data frame with two columns: [1] min_distance and [2] min_n. The number of regions / probes will be evaluated for each pair of parameters (per row). |
classes_gene |
Please see |
classes_island |
Please see |
targetID |
Please see |
chr |
Please see |
position |
Please see |
m.v |
Please see |
beta.v |
Please see |
recode |
Please see |
sep |
Please see |
gs |
Please see |
do.parallel |
Tuning of the parameters requires a significant amount of compute time and power. Parallelization if offered to do this more efficiently. 0=no parallelization, -1=use all available cores, n>1 use n cores (default=0) |
This function requires a significant amount of compute time/power. Parallelization is highly recommended. When parallelization is enabled, no progress indicator is displayed by R.
A data frame is returned with the folowing columns
min_distance |
The setting of min_distance. Also see |
min_n |
The setting for min_n. Also see |
n.regions |
The number of regions identified in your data using the before mentioned combination of settings and the setting of recode. |
n.valid.probes |
The number of probes that were assigned to one or more classes in the |
n.probes.included |
The number of probes included in the identified regions. |
Martin Rijlaarsdam
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | data(DMRforPairs_data)
CL.methy=CL.methy[which(CL.methy$position<=1.07E+8 &
CL.methy$position>=1.06E+8),]
#just two relevant values for the parameters
#min_distance (100 & 300) and min_n (4 & 8)
parameters=expand.grid(min_distance = c(200), min_n = c(4,5))
results_parameters= tune_parameters(parameters,
classes_gene=CL.methy$class.gene.related,
classes_island=CL.methy$class.island.related,
targetID=CL.methy$targetID,
chr=CL.methy$chromosome,
position=CL.methy$position,
m.v=CL.methy[,c(7:8)],
beta.v=CL.methy[,c(11:12)],
recode=1,
gs=CL.methy$gene.symbol,
do.parallel=0)
results_parameters
|
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