make_matrices {TTMap} | R Documentation |
control_adjustment
make_matrices
generates the control
and the test matrice in the
right format
make_matrices(mat, col_ctrl, col_test, NAME, CLID, GWEIGHT = rep(1, dim(mat)[1]), EWEIGHT = 0)
mat |
the gene expressions can be matrix, data.frame,
|
col_ctrl |
the columns in the matrix "mat" of the control samples |
col_test |
the columns in the matrix "mat" of the test samples |
NAME |
Name of genes,or annotation, e.g. WNT4 |
CLID |
Identities of genes,e.g. ENSMUSG00000000001 |
GWEIGHT |
the weight for each gene |
EWEIGHT |
the weight for each experiment |
make_matrices
generates the test matrix
and the control matrix in
the format accepted by
control_adjustment
from a matrix object
junk |
A list containing $CTRL and $TEST the matrices
to impute
in |
Rachel Jeitziner
control_adjustment
,
hyperrectangle_deviation_assessment
,
ttmap_sgn_genes
,
"
RangedSummarizedExperiment"
##-- ##-- Aa = 6 B1 = 3 B2 = 3 C0 = 100 D0 = 10000 a0 = 4 b0 = 0.1 a1 = 6 b1 = 0.1 a2 = 2 b2 = 0.5 ALPHA = 1 E = 1 Pw = 1.1 Bw = 0 RA <- matrix(rep(0, Aa * D0), nrow = D0) RB1 <- matrix(rep(0, B1 * D0), nrow = D0) RB2 <- matrix(rep(0, B2 * D0), nrow = D0) RA <- lapply(seq_len(D0 - C0), function(i) rnorm(Aa, mean = a0, sd = sqrt(b0))) RA<-do.call(rbind, RA) RB1<- lapply(seq_len(D0 - C0), function(i) rnorm(B1, mean = a0, sd = sqrt(b0))) RB1 <- do.call(rbind, RB1) RB2 <- lapply(seq_len(D0 - C0), function(i) rnorm(B2, mean = a0, sd = sqrt(b0))) RB2 <- do.call(rbind, RB2) RA_c <- lapply(seq_len(C0), function(i) rnorm(Aa, mean = a0, sd = sqrt(b0))) RA_c <- do.call(rbind, RA_c) RB1_c <- lapply(seq_len(C0), function(i) rnorm(B1, mean = a1, sd = sqrt(b1))) RB1_c <- do.call(rbind, RB1_c) RB2_c <- lapply(seq_len(C0), function(i) rnorm(B2, mean = a2, sd = sqrt(b2))) RB2_c <- do.call(rbind, RB2_c) norm1 <- rbind(RA, RA_c) dis <- cbind(rbind(RB1, RB1_c), rbind(RB2, RB2_c)) colnames(norm1) <- paste("N", seq_len(Aa), sep = "") rownames(norm1) <- c(paste("norm", seq_len(D0 - C0), sep = ""), paste("diff", seq_len(C0), sep = "")) colnames(dis) <- c(paste("B1", seq_len(B1), sep=""), paste("B2", seq_len(B2), sep ="")) rownames(dis)<-c(paste("norm", seq_len(D0 - C0), sep = ""), paste("diff", seq_len(C0), sep = "")) the_experiment <- TTMap::make_matrices(cbind(norm1, dis), col_ctrl = colnames(norm1), col_test = colnames(dis), NAME = rownames(norm1), CLID = rownames(norm1)) ###other example using SummarizedExperiment library(airway) data(airway) airway <- airway[rowSums(assay(airway))>80,] assay(airway) <- log(assay(airway)+1,2) the_experiment <- TTMap::make_matrices(airway, seq_len(4), seq_len(4) + 4, rownames(airway), rownames(airway))