control_adjustment {TTMap} | R Documentation |
control_adjustment
function
finds outliers in the control group and
removes them
control_adjustment(normal.pcl, tumor.pcl, normalname, dataname, org.directory = "", A = 1, e = 0, meth = 0, P = 1.1, B = 0)
normal.pcl |
the control matrix with annotation as obtained by $CTRL from
|
tumor.pcl |
the disease/test data matrix with annotation as obtained by $TEST
from |
normalname |
A name for the corrected control files |
dataname |
the name of the project |
org.directory |
where the outputs should be saved |
A |
integer if A=0 then the difference to the median is calculated otherwise the difference to the mean. |
e |
integer giving how far to the median an outlier is at least |
meth |
value or method that defines how to replace outliers, default is set to replace by the median |
P |
if more than P percent of features are outliers the feature is removed, by default all are kept |
B |
Batch vector a vector for normal and test samples with a same number corresponding to a same batch |
control_adjustment
calculates a
corrected control group, discovers
outliers in it.
Several files are created
paste(org.directory,normalname,".normMesh",sep = "") |
The normal matrix with only common features with the test matrix. This file is only created if the two have different rows |
paste(org.directory,dataname,".normMesh",sep = "") |
The test matrix with only common features with the normal matrix. This file is only created if the two have different rows. |
mean_vs_variance.pdf |
A pdf showing a plot of the mean (X axis) against the variances (Y axis) of each feature |
mean_vs_variance_after_correction.pdf |
A pdf showing a plot of the mean (X axis) against the variances (Y axis) of each feature after correction of the control group |
na_numbers_per_row.txt |
number of outliers per row |
na_numbers_per_col.txt |
number of outliers per column |
And values of ttmap_part1_ctrl_adj
e |
Selected criteria for what is an outlier |
tag.pcl |
Annotation of features, ID of features and weight |
Normal.mat |
The control matrix without annotation and only with the common rows with Disease.mat |
Disease.mat |
The test/disease matrix without annotation and only with the common rows with Disease.mat |
flat.Nmat |
A list $mat being the corrected control matrix $m a record of the different numbers of removed genes per sample |
record |
numbers recording the number of columns in Disease.mat and Normal.mat |
B |
The batch vector B introduced in the begining |
U1 |
The different batches in Normal.mat |
U2 |
The different batches in Disease.mat |
Rachel Jeitziner
hyperrectangle_deviation_assessment
,
ttmap
ttmap_sgn_genes
##-- library(airway) data(airway) airway <- airway[rowSums(assay(airway))>80,] assay(airway) <- log(assay(airway)+1,2) ALPHA <- 1 the_experiment <- TTMap::make_matrices(airway, seq_len(4), seq_len(4) + 4, rownames(airway), rownames(airway)) TTMAP_part1prime <-TTMap::control_adjustment( normal.pcl = the_experiment$CTRL, tumor.pcl = the_experiment$TEST, normalname = "The_healthy_controls", dataname = "Effect_of_cancer", org.directory = tempdir(), e = 0, P = 1.1, B = 0);