| Type: | Package |
| Title: | Normalize Gene Expression Data using Evaluated Methods |
| Version: | 0.1.1 |
| Author: | Zhenfeng Wu , Shan Gao |
| Maintainer: | Shan Gao <gao_shan@mail.nankai.edu.cn> |
| Description: | It provides a framework and a fast and simple way for researchers to evaluate methods (particularly some data-driven methods or their own methods) and then select a best one for data normalization in the gene expression analysis, based on the consistency of metrics and the consistency of datasets. Zhenfeng Wu, Weixiang Liu, Xiufeng Jin, Deshui Yu, Hua Wang, Gustavo Glusman, Max Robinson, Lin Liu, Jishou Ruan and Shan Gao (2018) <doi:10.1101/251140>. |
| License: | Artistic-2.0 |
| Encoding: | UTF-8 |
| LazyData: | true |
| NeedsCompilation: | no |
| Packaged: | 2024-03-19 12:30:07 UTC; wuzf |
| Depends: | R (≥ 2.10) |
| Repository: | CRAN |
| Date/Publication: | 2024-03-20 04:40:02 UTC |
CV2AUCVC
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
CV2AUCVC(data, cvResolution = 0.005)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, cvResolution = 0.005)
{
cv_cutoff <- NULL
uniform_genes_counts <- NULL
for (i in seq(0, 1, cvResolution)) {
cv_cutoff <- c(cv_cutoff, i)
gene_number <- length(which(data <= i))
uniform_genes_counts <- c(uniform_genes_counts, gene_number)
}
getArea(cv_cutoff, uniform_genes_counts)
}
bkRNA18
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
data("bkRNA18")Format
A data frame with 57955 observations on the following 18 variables.
col36l6_1a numeric vector
col38l6_3a numeric vector
col39l6_5a numeric vector
col40l6_7a numeric vector
col44l6_9a numeric vector
col45l6_11a numeric vector
col47l6_13a numeric vector
col48l6_97a numeric vector
col52l6_17a numeric vector
col36l6_2a numeric vector
col38l6_4a numeric vector
col39l6_6a numeric vector
col40l6_8a numeric vector
col44l6_10a numeric vector
col45l6_12a numeric vector
col47l6_14a numeric vector
col48l6_98a numeric vector
col52l6_18a numeric vector
Examples
data(bkRNA18)
## maybe str(bkRNA18) ; plot(bkRNA18) ...
bkRNA18_factors
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
data("bkRNA18_factors")Format
A data frame with 18 observations on the following 13 variables.
HG7a numeric vector
ERCCa numeric vector
TNa numeric vector
TCa numeric vector
CRa numeric vector
NRa numeric vector
DESeqa numeric vector
UQa numeric vector
TMMa numeric vector
TUa numeric vector
NCSa numeric vector
ESa numeric vector
GAPDHa numeric vector
Examples
data(bkRNA18_factors)
## maybe str(bkRNA18_factors) ; plot(bkRNA18_factors) ...
calcFactorRLE
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
calcFactorRLE(data, p = p)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
p |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, p = p)
{
gm <- exp(rowMeans(.log(data), na.rm = TRUE))
apply(data, 2, function(u) quantile((u/gm)[u != 0], na.rm = TRUE,
p = p))
}
calcFactorUpperquartile
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
calcFactorUpperquartile(data, lib.size, p = p)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
lib.size |
Please refer to the file /inst/doc/readme.pdf. |
p |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, lib.size, p = p)
{
y <- t(t(data)/lib.size)
f <- apply(y, 2, function(x) quantile(x[x != 0], p = p))
}
calcFactorWeighted
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
calcFactorWeighted(obs, ref, libsize.obs, libsize.ref, logratioTrim,
sumTrim, doWeighting, Acutoff)
Arguments
obs |
Please refer to the file /inst/doc/readme.pdf. |
ref |
Please refer to the file /inst/doc/readme.pdf. |
libsize.obs |
Please refer to the file /inst/doc/readme.pdf. |
libsize.ref |
Please refer to the file /inst/doc/readme.pdf. |
logratioTrim |
Please refer to the file /inst/doc/readme.pdf. |
sumTrim |
Please refer to the file /inst/doc/readme.pdf. |
doWeighting |
Please refer to the file /inst/doc/readme.pdf. |
Acutoff |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (obs, ref, libsize.obs = NULL, libsize.ref = NULL, logratioTrim = 0.3,
sumTrim = 0.05, doWeighting = TRUE, Acutoff = -1e+10)
{
if (all(obs == ref))
return(1)
obs <- as.numeric(obs)
ref <- as.numeric(ref)
if (is.null(libsize.obs))
nO <- sum(obs)
else nO <- libsize.obs
if (is.null(libsize.ref))
nR <- sum(ref)
else nR <- libsize.ref
logR <- log2((obs/nO)/(ref/nR))
absE <- (log2(obs/nO) + log2(ref/nR))/2
v <- (nO - obs)/nO/obs + (nR - ref)/nR/ref
fin <- is.finite(logR) & is.finite(absE) & (absE > Acutoff)
logR <- logR[fin]
absE <- absE[fin]
v <- v[fin]
n <- length(logR)
loL <- floor(n * logratioTrim) + 1
hiL <- n + 1 - loL
loS <- floor(n * sumTrim) + 1
hiS <- n + 1 - loS
keep <- (rank(logR) >= loL & rank(logR) <= hiL) & (rank(absE) >=
loS & rank(absE) <= hiS)
if (doWeighting) {
2^(sum(logR[keep]/v[keep], na.rm = TRUE)/sum(1/v[keep],
na.rm = TRUE))
}
else {
2^(mean(logR[keep], na.rm = TRUE))
}
}
change_colours
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
change_colours(p, palette, type)
Arguments
p |
Please refer to the file /inst/doc/readme.pdf. |
palette |
Please refer to the file /inst/doc/readme.pdf. |
type |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (p, palette, type)
{
n <- nlevels(p$data[[deparse(p$mapping$group)]])
tryCatch(as.character(palette), error = function(e) stop("be vector",call. = FALSE))
if (n > length(palette))
stop("Not enough colours in palette.")
if (missing(type))
type <- grep("colour|fill", names(p$layers[[1]]$mapping),
value = TRUE)[1]
pal <- function(n) palette[seq_len(n)]
p + discrete_scale(type, "foo", pal)
}
estimateSizeFactorsForMatrix
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
estimateSizeFactorsForMatrix(data, p = p)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
p |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, p = p)
{
loggeomeans <- rowMeans(.log(data), na.rm = TRUE)
apply(data, 2, function(cnts) exp(quantile(.log(cnts) - loggeomeans,
na.rm = TRUE, p = p)))
}
filteredZero
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
filteredZero(data, nonzeroRatio)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatio |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, nonzeroRatio)
{
nozeroCount <- apply(data, 1, function(x) length(which(x !=
0)))
geneIndex <- which(nozeroCount >= ncol(data) * nonzeroRatio)
return(geneIndex)
}
findGenes
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
findGenes(g, qlower = NULL, qupper = NULL, pre_ratio = NULL)
Arguments
g |
Please refer to the file /inst/doc/readme.pdf. |
qlower |
Please refer to the file /inst/doc/readme.pdf. |
qupper |
Please refer to the file /inst/doc/readme.pdf. |
pre_ratio |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (g, qlower = NULL, qupper = NULL, pre_ratio = NULL)
{
gene_name <- rownames(g)
g <- unlist(g)
seen <- which(g >= qlower & g <= qupper)
counts <- length(seen)
if (counts >= pre_ratio * length(g)) {
gene_name
}
}
gatherCVs
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
gatherCVs(data,nonzeroRatio,HG7,ERCC,TN,TC,CR,NR,
DESeq,UQ,TMM,TU,GAPDH,cvNorm,cvResolution)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatio |
Please refer to the file /inst/doc/readme.pdf. |
HG7 |
Please refer to the file /inst/doc/readme.pdf. |
ERCC |
Please refer to the file /inst/doc/readme.pdf. |
TN |
Please refer to the file /inst/doc/readme.pdf. |
TC |
Please refer to the file /inst/doc/readme.pdf. |
CR |
Please refer to the file /inst/doc/readme.pdf. |
NR |
Please refer to the file /inst/doc/readme.pdf. |
DESeq |
Please refer to the file /inst/doc/readme.pdf. |
UQ |
Please refer to the file /inst/doc/readme.pdf. |
TMM |
Please refer to the file /inst/doc/readme.pdf. |
TU |
Please refer to the file /inst/doc/readme.pdf. |
GAPDH |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, nonzeroRatio = NULL, HG7 = NULL, ERCC = NULL,
TN = NULL, TC = NULL, CR = NULL, NR = NULL, DESeq = NULL,
UQ = NULL, TMM = NULL, TU = NULL, GAPDH = NULL, cvNorm = TRUE,
cvResolution = 0.005)
{
if (is.null(nonzeroRatio)) {
stop("Please provide nonzeroRatio!")
}
methodsList <- list(HG7 = HG7, ERCC = ERCC, TN = TN, TC = TC,
CR = CR, NR = NR, DESeq = DESeq, UQ = UQ, TMM = TMM,
TU = TU, GAPDH = GAPDH)
specifiedMethods <- methodsList[!unlist(lapply(methodsList,
is.null))]
numMethod <- length(specifiedMethods)
method_range_tmp <- seq(1, numMethod, 1)
cv_range_tmp <- seq(0, 1, cvResolution)
method_range_times <- length(cv_range_tmp)
cv_range_times <- length(method_range_tmp)
method_range <- rep(method_range_tmp, each = round(method_range_times))
cv_range <- rep(cv_range_tmp, times = round(cv_range_times))
nozeroIndex <- filteredZero(data, nonzeroRatio = nonzeroRatio)
for (j in method_range_tmp) {
norm.matrix <- getNormMatrix(data, specifiedMethods[[j]])
dataUse2CV <- norm.matrix[nozeroIndex, ]
cv.result <- getCV(dataUse2CV, cvNorm = cvNorm)
assign(paste(names(specifiedMethods)[j], ".cv", sep = ""),
cv.result)
}
cv_uniform <- NULL
cv_uniform_all <- mapply(function(i, j) {
cv.result <- paste(names(specifiedMethods)[j], ".cv",
sep = "")
gene_number <- length(which(get(cv.result) <= i))
cv_uniform_row <- c(i, gene_number, names(specifiedMethods)[j])
rbind(cv_uniform, cv_uniform_row)
}, cv_range, method_range)
cv_uniform_all <- t(cv_uniform_all)
colnames(cv_uniform_all) <- c("Cutoff", "Counts", "Methods")
return(cv_uniform_all)
}
gatherCVs4Matrices
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
gatherCVs4Matrices(..., raw_matrix, nonzeroRatio , cvNorm , cvResolution = 0.005)
Arguments
... |
Please refer to the file /inst/doc/readme.pdf. |
raw_matrix |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatio |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (..., raw_matrix, nonzeroRatio = NULL, cvNorm = TRUE,
cvResolution = 0.005)
{
if (is.null(nonzeroRatio)) {
stop("Please provide nonzeroRatio!")
}
matrices <- list(...)
matrices_name <- names(matrices)
numMethod <- length(matrices)
method_range_tmp <- seq(1, numMethod, 1)
cv_range_tmp <- seq(0, 1, cvResolution)
method_range_times <- length(cv_range_tmp)
cv_range_times <- length(method_range_tmp)
method_range <- rep(method_range_tmp, each = round(method_range_times))
cv_range <- rep(cv_range_tmp, times = round(cv_range_times))
nozeroIndex <- filteredZero(raw_matrix, nonzeroRatio = nonzeroRatio)
for (j in method_range_tmp) {
dataUse2CV <- matrices[[j]][nozeroIndex, ]
cv.result <- getCV(dataUse2CV, cvNorm = cvNorm)
assign(paste(matrices_name[j], ".cv", sep = ""), cv.result)
}
cv_uniform <- NULL
cv_uniform_all <- mapply(function(i, j) {
cv.result <- paste(matrices_name[j], ".cv", sep = "")
gene_number <- length(which(get(cv.result) <= i))
cv_uniform_row <- c(i, gene_number, matrices_name[j])
rbind(cv_uniform, cv_uniform_row)
}, cv_range, method_range)
cv_uniform_all <- t(cv_uniform_all)
colnames(cv_uniform_all) <- c("Cutoff", "Counts", "Methods")
return(cv_uniform_all)
}
gatherCors
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
gatherCors(data, cor_method = c("spearman", "pearson", "kendall"),
HG7 = NULL, ERCC = NULL, TN = NULL, TC = NULL, CR = NULL, NR = NULL,
DESeq = NULL, UQ = NULL, TMM = NULL, TU = NULL, GAPDH = NULL,
pre_ratio = 0.5, lower_trim = 0.05, upper_trim = 0.65, rounds = 1e+06)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
cor_method |
Please refer to the file /inst/doc/readme.pdf. |
HG7 |
Please refer to the file /inst/doc/readme.pdf. |
ERCC |
Please refer to the file /inst/doc/readme.pdf. |
TN |
Please refer to the file /inst/doc/readme.pdf. |
TC |
Please refer to the file /inst/doc/readme.pdf. |
CR |
Please refer to the file /inst/doc/readme.pdf. |
NR |
Please refer to the file /inst/doc/readme.pdf. |
DESeq |
Please refer to the file /inst/doc/readme.pdf. |
UQ |
Please refer to the file /inst/doc/readme.pdf. |
TMM |
Please refer to the file /inst/doc/readme.pdf. |
TU |
Please refer to the file /inst/doc/readme.pdf. |
GAPDH |
Please refer to the file /inst/doc/readme.pdf. |
pre_ratio |
Please refer to the file /inst/doc/readme.pdf. |
lower_trim |
Please refer to the file /inst/doc/readme.pdf. |
upper_trim |
Please refer to the file /inst/doc/readme.pdf. |
rounds |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, cor_method = c("spearman", "pearson", "kendall"),
HG7 = NULL, ERCC = NULL, TN = NULL, TC = NULL, CR = NULL,
NR = NULL, DESeq = NULL, UQ = NULL, TMM = NULL, TU = NULL,
GAPDH = NULL, pre_ratio = 0.5, lower_trim = 0.05, upper_trim = 0.65,
rounds = 1e+06)
{
methodsList <- list(HG7 = HG7, ERCC = ERCC, TN = TN, TC = TC,
CR = CR, NR = NR, DESeq = DESeq, UQ = UQ, TMM = TMM,
TU = TU, GAPDH = GAPDH)
specifiedMethods <- methodsList[!unlist(lapply(methodsList,
is.null))]
numMethod <- length(specifiedMethods)
method_range <- seq(1, numMethod, 1)
ubq_genes <- identifyUbq(data, pre_ratio = pre_ratio, lower_trim = lower_trim,
upper_trim = upper_trim, min_ubq = 100)
cor_value_method <- NULL
for (j in method_range) {
norm.matrix <- getNormMatrix(data, specifiedMethods[[j]])
dataUse2Cor <- norm.matrix[ubq_genes, ]
cor.result <- getCor(dataUse2Cor, method = cor_method,
rounds = rounds)
cor_vm <- cbind(cor.result, rep(names(specifiedMethods)[j],
times = round(rounds)))
cor_value_method <- rbind(cor_value_method, cor_vm)
}
colnames(cor_value_method) <- c("Value", "Methods")
return(cor_value_method)
}
gatherCors4Matrices
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
gatherCors4Matrices(..., raw_matrix, cor_method = c("spearman", "pearson", "kendall"),
pre_ratio = 0.5, lower_trim = 0.05, upper_trim = 0.65, rounds = 1e+06)
Arguments
... |
Please refer to the file /inst/doc/readme.pdf. |
raw_matrix |
Please refer to the file /inst/doc/readme.pdf. |
cor_method |
Please refer to the file /inst/doc/readme.pdf. |
pre_ratio |
Please refer to the file /inst/doc/readme.pdf. |
lower_trim |
Please refer to the file /inst/doc/readme.pdf. |
upper_trim |
Please refer to the file /inst/doc/readme.pdf. |
rounds |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (..., raw_matrix, cor_method = c("spearman", "pearson",
"kendall"), pre_ratio = 0.5, lower_trim = 0.05, upper_trim = 0.65,
rounds = 1e+06)
{
matrices <- list(...)
numMethod <- length(matrices)
method_range <- seq(1, numMethod, 1)
ubq_genes <- identifyUbq(raw_matrix, pre_ratio = pre_ratio,
lower_trim = lower_trim, upper_trim = upper_trim, min_ubq = 100)
cor_value_method <- NULL
for (j in method_range) {
dataUse2Cor <- matrices[[j]][ubq_genes, ]
cor.result <- getCor(dataUse2Cor, method = cor_method,
rounds = rounds)
cor_vm <- cbind(cor.result, rep(names(matrices)[j], times = round(rounds)))
cor_value_method <- rbind(cor_value_method, cor_vm)
}
colnames(cor_value_method) <- c("Value", "Methods")
return(cor_value_method)
}
gatherFactors
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
gatherFactors(data,
methods = c("HG7", "ERCC", "TN", "TC", "CR", "NR", "DESeq", "UQ", "TMM", "TU"),
HG7.size = NULL, ERCC.size = NULL, TN.size = NULL, TC.size = NULL,
CR.size = NULL, NR.size = NULL, pre_ratio = 0.5,
lower_trim = 0.05, upper_trim = 0.65, min_ubq = 100)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
methods |
Please refer to the file /inst/doc/readme.pdf. |
HG7.size |
Please refer to the file /inst/doc/readme.pdf. |
ERCC.size |
Please refer to the file /inst/doc/readme.pdf. |
TN.size |
Please refer to the file /inst/doc/readme.pdf. |
TC.size |
Please refer to the file /inst/doc/readme.pdf. |
CR.size |
Please refer to the file /inst/doc/readme.pdf. |
NR.size |
Please refer to the file /inst/doc/readme.pdf. |
pre_ratio |
Please refer to the file /inst/doc/readme.pdf. |
lower_trim |
Please refer to the file /inst/doc/readme.pdf. |
upper_trim |
Please refer to the file /inst/doc/readme.pdf. |
min_ubq |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, methods = c("HG7", "ERCC", "TN", "TC", "CR",
"NR", "DESeq", "UQ", "TMM", "TU"), HG7.size = NULL, ERCC.size = NULL,
TN.size = NULL, TC.size = NULL, CR.size = NULL, NR.size = NULL,
pre_ratio = 0.5, lower_trim = 0.05, upper_trim = 0.65, min_ubq = 100)
{
method1 <- as.list(methods)
numMethod <- length(method1)
method_range <- seq(1, numMethod, 1)
for (i in method_range) {
if (method1[[i]] == "HG7" || method1[[i]] == "ERCC" ||
method1[[i]] == "TN" || method1[[i]] == "TC" || method1[[i]] ==
"CR" || method1[[i]] == "NR") {
size.name <- paste(method1[[i]], ".size", sep = "")
out.name1 <- paste(method1[[i]], ".factors", sep = "")
if (is.null(size.name)) {
stop("Please provide", size.name, "!")
}
else {
assign(out.name1, getFactors(data, method = "sizefactor",
lib.size = get(size.name)))
}
}
if (method1[[i]] == "DESeq" || method1[[i]] == "RLE" ||
method1[[i]] == "UQ" || method1[[i]] == "TMM") {
out.name2 <- paste(method1[[i]], ".factors", sep = "")
assign(out.name2, getFactors(data, method = method1[[i]]))
}
if (method1[[i]] == "TU") {
TU.factors <- getFactors(data, method = "TU", pre_ratio = pre_ratio,
lower_trim = lower_trim, upper_trim = upper_trim,
min_ubq = min_ubq)
}
}
factors.list <- NULL
for (m in methods) {
m.factors <- paste(m, ".factors", sep = "")
factors.list <- c(factors.list, m.factors)
}
factors.result <- NULL
for (i in method_range) {
factors.result <- cbind(factors.result, get(factors.list[i]))
}
colnames(factors.result) <- methods
return(factors.result)
}
getAUCVC
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
getAUCVC(data, nonzeroRatio = NULL, cvNorm = TRUE, cvResolution = 0.005)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatio |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, nonzeroRatio = NULL, cvNorm = TRUE, cvResolution = 0.005)
{
nozeroIndex <- filteredZero(data, nonzeroRatio = nonzeroRatio)
dataUse2CV <- data[nozeroIndex, ]
cv.result <- getCV(dataUse2CV, cvNorm = cvNorm)
CV2AUCVC(cv.result, cvResolution = cvResolution)
}
getAUCVCs
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
getAUCVCs(..., nonzeroRatio = NULL, cvNorm = TRUE, cvResolution = 0.005)
Arguments
... |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatio |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (..., nonzeroRatio = NULL, cvNorm = TRUE, cvResolution = 0.005)
{
matrices <- list(...)
numMethod <- length(matrices)
method_range <- seq(1, numMethod, 1)
result <- NULL
for (i in method_range) {
AUCVC.result <- getAUCVC(matrices[[i]], nonzeroRatio = nonzeroRatio,
cvNorm = cvNorm, cvResolution = cvResolution)
result <- c(result, AUCVC.result)
names(result)[i] <- names(matrices)[i]
}
sorted_AUCVCs <- sort(result, decreasing = TRUE)
return(sorted_AUCVCs)
}
getArea
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
getArea(x, y)
Arguments
x |
Please refer to the file /inst/doc/readme.pdf. |
y |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (x, y)
{
x <- x/max(x)
y <- y/max(y)
if (!(is.numeric(x) || is.complex(x)) || !(is.numeric(y) ||
is.complex(y))) {
stop("Arguments 'x' and 'y' must be real or complex vectors.")
}
if (length(x) != length(y)) {
stop("The length of two input vectors should be equal!")
}
m <- length(x)
n <- 2 * m
xp <- c(x, x[m:1])
yp <- c(numeric(m), y[m:1])
p1 <- sum(xp[1:(n - 1)] * yp[2:n]) + xp[n] * yp[1]
p2 <- sum(xp[2:n] * yp[1:(n - 1)]) + xp[1] * yp[n]
return(0.5 * (p1 - p2))
}
getCV
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
getCV(data, cvNorm = TRUE)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, cvNorm = TRUE)
{
if (!is.matrix(data))
data <- as.matrix(data)
if (cvNorm) {
rawCV <- apply(data, 1, function(x) {
sd(log2(x[x != 0]))/mean(log2(x[x != 0]))
})
(rawCV - min(rawCV))/(max(rawCV) - min(rawCV))
}
else {
apply(data, 1, function(x) {
sd(x)/mean(x)
})
}
}
getCor
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
getCor(data, method = c("spearman", "pearson", "kendall"), rounds = 1e+06)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
method |
Please refer to the file /inst/doc/readme.pdf. |
rounds |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, method = c("spearman", "pearson", "kendall"),
rounds = 1e+06)
{
sp_result <- NULL
method <- match.arg(method)
for (i in 1:rounds) {
rg1 <- sample(1:nrow(data), size = 1)
rg2 <- sample(1:nrow(data), size = 1)
while (rg1 == rg2) {
rg2 <- sample(1:nrow(data), size = 1)
}
gene1 <- unlist(data[rg1, ])
gene2 <- unlist(data[rg2, ])
sp_value <- cor(gene1, gene2, method = method)
sp_result <- c(sp_result, sp_value)
}
return(sp_result)
}
getCorMedians
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
getCorMedians(data)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data)
{
if (!is.data.frame(data))
data <- data.frame(data)
if (is.factor(data$Value))
data$Value <- as.numeric(as.character(data$Value))
sorted_result <- sort(tapply(data$Value, data$Methods, median),
decreasing = FALSE)
return(sorted_result)
}
getFactors
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
getFactors(data, method = c("sizefactor", "DESeq", "RLE", "UQ", "TMM", "TU"),
lib.size = NULL, pre_ratio = 0.5, lower_trim = 0.05, upper_trim = 0.65, min_ubq = 100)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
method |
Please refer to the file /inst/doc/readme.pdf. |
lib.size |
Please refer to the file /inst/doc/readme.pdf. |
pre_ratio |
Please refer to the file /inst/doc/readme.pdf. |
lower_trim |
Please refer to the file /inst/doc/readme.pdf. |
upper_trim |
Please refer to the file /inst/doc/readme.pdf. |
min_ubq |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, method = c("sizefactor", "DESeq", "RLE", "UQ",
"TMM", "TU"), lib.size = NULL, pre_ratio = 0.5, lower_trim = 0.05,
upper_trim = 0.65, min_ubq = 100)
{
if (!is.matrix(data))
data <- as.matrix(data)
if (any(is.na(data)))
stop("NA counts not permitted")
if (is.null(lib.size))
libsize <- colSums(data)
else libsize <- lib.size
if (any(is.na(libsize)))
stop("NA libsizes not permitted")
method <- match.arg(method)
i <- apply(data <= 0, 1, all)
if (any(i))
data <- data[!i, , drop = FALSE]
f <- switch(method, sizefactor = 1e+06/libsize, DESeq = 1/estimateSizeFactorsForMatrix(data,
p = 0.5), RLE = calcFactorRLE(data, p = 0.5)/libsize,
UQ = calcFactorUpperquartile(data, lib.size = libsize,
p = 0.75), TMM = {
fq <- calcFactorUpperquartile(data = data, lib.size = libsize,
p = 0.75)
refColumn <- which.min(abs(fq - mean(fq)))
if (length(refColumn) == 0 | refColumn < 1 | refColumn >
ncol(data)) refColumn <- 1
f <- rep(NA, ncol(data))
for (i in 1:ncol(data)) {
f[i] <- calcFactorWeighted(obs = data[, i], ref = data[,
refColumn], libsize.obs = libsize[i], libsize.ref = libsize[refColumn],
logratioTrim = 0.3, sumTrim = 0.05, doWeighting = TRUE,
Acutoff = -1e+10)
}
f
}, TU = {
if (!is.data.frame(data)) data <- data.frame(data)
ubq_genes <- identifyUbq(data, lower_trim = lower_trim,
upper_trim = upper_trim, pre_ratio = pre_ratio,
min_ubq = min_ubq)
ubq_sums <- colSums(data[ubq_genes, ])
mean(ubq_sums)/ubq_sums
}, )
if (method == "RLE" || method == "UQ" || method == "TMM") {
f <- 1e+06/libsize/f
}
norm.factors <- f/exp(mean(base::log(f)))
round(norm.factors, digits = 5)
}
getNormMatrix
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
getNormMatrix(data, norm.factors)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
norm.factors |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, norm.factors)
{
data * matrix(rep(norm.factors, dim(data)[1]), nrow = dim(data)[1],
ncol = length(norm.factors), byrow = T)
}
gridAUCVC
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
gridAUCVC(data, dataType = c("bk", "sc"), HG7 = NULL, ERCC = NULL, TN = NULL,
TC = NULL, CR = NULL, NR = NULL, DESeq = NULL, UQ = NULL, TMM = NULL, TU = 0,
GAPDH = NULL, nonzeroRatios = c(0.7, 0.8, 0.9, 1), cvNorm = TRUE, cvResolution = 0.005)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
dataType |
Please refer to the file /inst/doc/readme.pdf. |
HG7 |
Please refer to the file /inst/doc/readme.pdf. |
ERCC |
Please refer to the file /inst/doc/readme.pdf. |
TN |
Please refer to the file /inst/doc/readme.pdf. |
TC |
Please refer to the file /inst/doc/readme.pdf. |
CR |
Please refer to the file /inst/doc/readme.pdf. |
NR |
Please refer to the file /inst/doc/readme.pdf. |
DESeq |
Please refer to the file /inst/doc/readme.pdf. |
UQ |
Please refer to the file /inst/doc/readme.pdf. |
TMM |
Please refer to the file /inst/doc/readme.pdf. |
TU |
Please refer to the file /inst/doc/readme.pdf. |
GAPDH |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatios |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, dataType = c("bk", "sc"), HG7 = NULL, ERCC = NULL,
TN = NULL, TC = NULL, CR = NULL, NR = NULL, DESeq = NULL,
UQ = NULL, TMM = NULL, TU = 0, GAPDH = NULL, nonzeroRatios = c(0.7,
0.8, 0.9, 1), cvNorm = TRUE, cvResolution = 0.005)
{
grid_result <- NULL
if (length(TU) == 1 && TU == 1) {
colnames_paraMatrix <- c("nonzeroRatio", "pre_ratio",
"lower_trim", "upper_trim")
write.table(t(as.matrix(colnames_paraMatrix)), file = "bestPara.txt",
sep = "\t", row.names = FALSE, col.names = FALSE)
}
for (i in nonzeroRatios) {
if (dataType == "sc") {
if ((ncol(data) * i) <= 100) {
cat("nonzeroRatio:", i, " is too small!\n")
stop("We suggest that the minimal counts of
nonzero samples should be greater than 100!")
}
}
result <- nonzeroRatio2AUCVC(data = data, dataType = dataType,
HG7 = HG7, ERCC = ERCC, TN = TN, TC = TC, CR = CR,
NR = NR, DESeq = DESeq, UQ = UQ, TMM = TMM, TU = TU,
GAPDH = GAPDH, nonzeroRatio = i, cvNorm = cvNorm,
cvResolution = cvResolution)
nonzeroM <- matrix(i, 1, 1, TRUE)
colnames(nonzeroM) <- "NonzeroRatio"
grid_record <- cbind(nonzeroM, result)
grid_result <- rbind(grid_result, grid_record)
}
return(grid_result)
}
gridAUCVC4Matrices
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
gridAUCVC4Matrices(..., nonzeroRatios = NULL, cvNorm = TRUE, cvResolution = 0.005)
Arguments
... |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatios |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (..., nonzeroRatios = NULL, cvNorm = TRUE, cvResolution = 0.005)
{
if (is.null(nonzeroRatios)) {
stop("Please provide nonzeroRatios!")
}
matrices <- list(...)
numMethod <- length(matrices)
grid_result <- NULL
for (i in nonzeroRatios) {
result.sorted <- getAUCVCs(..., nonzeroRatio = i, cvNorm = cvNorm,
cvResolution = cvResolution)
grid_record <- c(i, result.sorted)
names(grid_record)[1] <- "NonzeroRatio"
grid_result <- c(grid_result, names(grid_record), grid_record)
}
grid_result2 <- matrix(grid_result, ncol = numMethod + 1,
byrow = TRUE)
return(grid_result2)
}
identifyUbq
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
identifyUbq(data, pre_ratio = 0.5, lower_trim = 0.05, upper_trim = 0.65, min_ubq = 100)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
pre_ratio |
Please refer to the file /inst/doc/readme.pdf. |
lower_trim |
Please refer to the file /inst/doc/readme.pdf. |
upper_trim |
Please refer to the file /inst/doc/readme.pdf. |
min_ubq |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, pre_ratio = 0.5, lower_trim = 0.05, upper_trim = 0.65,
min_ubq = 100)
{
qlower <- apply(data, 2, function(x) quantile(x[x != 0],
p = lower_trim))
qupper <- apply(data, 2, function(x) quantile(x[x != 0],
p = upper_trim))
ubq_genes <- NULL
for (i in 1:nrow(data)) {
genes_finded <- findGenes(data[i, ], qlower = qlower,
qupper = qupper, pre_ratio = pre_ratio)
ubq_genes <- c(ubq_genes, genes_finded)
}
if (length(ubq_genes) < min_ubq) {
cat("Parameters range", lower_trim, "-", upper_trim,
"...identified too few ubiquitous genes (", length(ubq_genes),
"), trying range 5-95 instead", "\n")
ubq_genes <- identifyUbqRepeat(data, pre_ratioC = pre_ratio,
lower_trimC = 0.05, upper_trimC = 0.95)
}
return(ubq_genes)
}
identifyUbqRepeat
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
identifyUbqRepeat(data, pre_ratioC = NULL, lower_trimC = NULL, upper_trimC = NULL)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
pre_ratioC |
Please refer to the file /inst/doc/readme.pdf. |
lower_trimC |
Please refer to the file /inst/doc/readme.pdf. |
upper_trimC |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, pre_ratioC = NULL, lower_trimC = NULL, upper_trimC = NULL)
{
qlower <- apply(data, 2, function(x) quantile(x[x != 0],
p = lower_trimC))
qupper <- apply(data, 2, function(x) quantile(x[x != 0],
p = upper_trimC))
ubq_genes <- NULL
for (i in 1:nrow(data)) {
genes_finded <- findGenes(data[i, ], qlower = qlower,
qupper = qupper, pre_ratio = pre_ratioC)
ubq_genes <- c(ubq_genes, genes_finded)
}
return(ubq_genes)
}
nonzeroRatio2AUCVC
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
nonzeroRatio2AUCVC(data, dataType = c("bk", "sc"),
HG7 = NULL, ERCC = NULL, TN = NULL, TC = NULL, CR = NULL, NR = NULL, DESeq = NULL,
UQ = NULL, TMM = NULL, TU = 0, GAPDH = NULL, nonzeroRatio = NULL, cvNorm = TRUE,
cvResolution = 0.005)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
dataType |
Please refer to the file /inst/doc/readme.pdf. |
HG7 |
Please refer to the file /inst/doc/readme.pdf. |
ERCC |
Please refer to the file /inst/doc/readme.pdf. |
TN |
Please refer to the file /inst/doc/readme.pdf. |
TC |
Please refer to the file /inst/doc/readme.pdf. |
CR |
Please refer to the file /inst/doc/readme.pdf. |
NR |
Please refer to the file /inst/doc/readme.pdf. |
DESeq |
Please refer to the file /inst/doc/readme.pdf. |
UQ |
Please refer to the file /inst/doc/readme.pdf. |
TMM |
Please refer to the file /inst/doc/readme.pdf. |
TU |
Please refer to the file /inst/doc/readme.pdf. |
GAPDH |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatio |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, dataType = c("bk", "sc"), HG7 = NULL, ERCC = NULL,
TN = NULL, TC = NULL, CR = NULL, NR = NULL, DESeq = NULL,
UQ = NULL, TMM = NULL, TU = 0, GAPDH = NULL, nonzeroRatio = NULL,
cvNorm = TRUE, cvResolution = 0.005)
{
nozeroIndex <- filteredZero(data, nonzeroRatio = nonzeroRatio)
methodsList <- list(HG7 = HG7, ERCC = ERCC, TN = TN, TC = TC,
CR = CR, NR = NR, DESeq = DESeq, UQ = UQ, TMM = TMM,
TU = TU, GAPDH = GAPDH)
specifiedMethods <- methodsList[!unlist(lapply(methodsList,
is.null))]
if (length(TU) == 1 && TU == 0) {
specifiedMethods$TU <- NULL
}
if (length(TU) == 1 && TU == 1) {
if (dataType == "bk") {
optimalPara <- optTU(data, nonzeroRatio = nonzeroRatio,
pre_ratio_range = c(1, 1), prResolution = 0.1,
lower_range = c(0.05, 0.4), upper_range = c(0.6,
0.95), qResolution = 0.05, min_ubq = 1000,
cvNorm = cvNorm, cvResolution = cvResolution)
}
else {
optimalPara <- optTU(data, nonzeroRatio = nonzeroRatio,
pre_ratio_range = c(0.2, 0.6), prResolution = 0.1,
lower_range = c(0.05, 0.4), upper_range = c(0.6,
0.95), qResolution = 0.05, min_ubq = 100, cvNorm = cvNorm,
cvResolution = cvResolution)
}
optimalPara <- as.matrix(optimalPara)
lower_trim <- optimalPara["lower", 1]
upper_trim <- optimalPara["upper", 1]
pre_ratio <- optimalPara["ratio", 1]
para <- c(nonzeroRatio, pre_ratio, lower_trim, upper_trim)
names(para)[1] <- "nonzeroRatio"
paraMatrix <- t(as.matrix(para))
write.table(paraMatrix, file = "bestPara.txt", sep = "\t",
row.names = FALSE, col.names = FALSE, append = TRUE)
TU.factors <- getFactors(data, method = "TU", lower_trim = lower_trim,
upper_trim = upper_trim, pre_ratio = pre_ratio, min_ubq = 100)
norm.matrix <- getNormMatrix(data, TU.factors)
dataUse2CV <- norm.matrix[nozeroIndex, ]
cv.result <- getCV(dataUse2CV, cvNorm = cvNorm)
TU.AUCVC <- CV2AUCVC(cv.result, cvResolution = cvResolution)
specifiedMethods$TU <- NULL
}
numMethod <- length(specifiedMethods)
if (numMethod >= 1) {
method_range <- seq(1, numMethod, 1)
for (i in method_range) {
norm.matrix <- getNormMatrix(data, specifiedMethods[[i]])
dataUse2CV <- norm.matrix[nozeroIndex, ]
cv.result <- getCV(dataUse2CV, cvNorm = cvNorm)
assign(names(specifiedMethods)[i], CV2AUCVC(cv.result,
cvResolution = cvResolution))
}
AUCVC.result <- NULL
for (i in method_range) {
AUCVC.result <- cbind(AUCVC.result, get(names(specifiedMethods)[i]))
}
colnames(AUCVC.result) <- names(specifiedMethods)
if (length(TU) == 1 && TU == 1) {
AUCVC.result <- cbind(AUCVC.result, TU.AUCVC)
colnames(AUCVC.result) <- c(names(specifiedMethods),
"TU")
}
}
if (numMethod == 0 && TU == 0)
stop("Please specify at least one method!")
if (numMethod == 0 && TU == 1) {
AUCVC.result <- as.matrix(TU.AUCVC)
colnames(AUCVC.result) <- "TU"
}
return(AUCVC.result)
}
optTU
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
optTU(data, nonzeroRatio = NULL, pre_ratio_range = c(0.2, 0.6), prResolution = 0.1,
lower_range = c(0.05, 0.4), upper_range = c(0.6, 0.95),
qResolution = 0.05, min_ubq = 100, cvNorm = TRUE, cvResolution = 0.005)
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
nonzeroRatio |
Please refer to the file /inst/doc/readme.pdf. |
pre_ratio_range |
Please refer to the file /inst/doc/readme.pdf. |
prResolution |
Please refer to the file /inst/doc/readme.pdf. |
lower_range |
Please refer to the file /inst/doc/readme.pdf. |
upper_range |
Please refer to the file /inst/doc/readme.pdf. |
qResolution |
Please refer to the file /inst/doc/readme.pdf. |
min_ubq |
Please refer to the file /inst/doc/readme.pdf. |
cvNorm |
Please refer to the file /inst/doc/readme.pdf. |
cvResolution |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, nonzeroRatio = NULL, pre_ratio_range = c(0.2,
0.6), prResolution = 0.1, lower_range = c(0.05, 0.4), upper_range = c(0.6,
0.95), qResolution = 0.05, min_ubq = 100, cvNorm = TRUE,
cvResolution = 0.005)
{
if (is.null(nonzeroRatio)) {
stop("Please provide nonzeroRatios!")
}
pre_ratio_times <- (pre_ratio_range[2] - pre_ratio_range[1] +
prResolution) * 10
lower_times <- (upper_range[2] - upper_range[1] + qResolution)/qResolution
lower_range_tmp <- rep(seq(lower_range[1], lower_range[2],
qResolution), each = round(lower_times))
lower_range2 <- rep(lower_range_tmp, times = round(pre_ratio_times))
upper_times <- (lower_range[2] - lower_range[1] + qResolution)/qResolution
upper_range_tmp <- rep(seq(upper_range[1], upper_range[2],
qResolution), times = round(upper_times))
upper_range2 <- rep(upper_range_tmp, times = round(pre_ratio_times))
lower_upper_tmp_len <- length(lower_range_tmp)
pre_ratio_range2 <- rep(seq(pre_ratio_range[1], pre_ratio_range[2],
0.1), each = round(lower_upper_tmp_len))
nozeroIndex <- filteredZero(data, nonzeroRatio = nonzeroRatio)
all_aucvc <- mapply(function(lower_trim, upper_trim, pre_ratio) {
factors.TU <- getFactors(data, method = "TU", lower_trim = lower_trim,
upper_trim = upper_trim, pre_ratio = pre_ratio, min_ubq = min_ubq)
norm.TU <- getNormMatrix(data, factors.TU)
dataUse2CV <- norm.TU[nozeroIndex, ]
cv.TU <- getCV(dataUse2CV, cvNorm = cvNorm)
TU.AUCVC <- CV2AUCVC(cv.TU, cvResolution = cvResolution)
return(c(TU.AUCVC = TU.AUCVC, lower = lower_trim, upper = upper_trim,
ratio = pre_ratio))
}, lower_range2, upper_range2, pre_ratio_range2)
all_aucvc2 <- t(all_aucvc)
max_index <- which(max(all_aucvc2[, "TU.AUCVC"]) == all_aucvc2[,
"TU.AUCVC"])
return(all_aucvc2[max_index, ])
}
plotCVs
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
plotCVs(data, methods = c("None", "HG7", "ERCC", "TN", "TC", "CR", "NR",
"DESeq", "UQ", "TMM", "TU"), legend.position = c(0.85, 0.48))
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
methods |
Please refer to the file /inst/doc/readme.pdf. |
legend.position |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, methods = c("None", "HG7", "ERCC", "TN", "TC",
"CR", "NR", "DESeq", "UQ", "TMM", "TU"), legend.position = c(0.85,
0.48))
{
if (!is.data.frame(data))
data <- data.frame(data)
if (is.factor(data$Cutoff))
data$Cutoff <- as.numeric(as.character(data$Cutoff))
if (is.factor(data$Counts))
data$Counts <- as.numeric(as.character(data$Counts))
data$Methods <- factor(data$Methods, levels = methods, labels = methods)
change_colours(ggplot(data = data, aes(x = Cutoff, y = Counts)) +
geom_line(aes(group = Methods, color = Methods), size = 3) +
xlab("Normalized CV cutoff") + ylab("Number of uniform genes") +
theme_bw() + theme(panel.grid.minor = element_blank(),
axis.title.x = element_text(size = 48), axis.title.y = element_text(size = 48),
axis.text.x = element_text(size = 38), axis.text.y = element_text(size = 38),
legend.text = element_text(size = 39), legend.title = element_text(size = 43),
legend.position = legend.position, legend.background = element_blank(),
legend.key = element_blank(), legend.key.height = unit(1.8,
"cm"), plot.margin = unit(c(0.5, 0.5, 0.5, 0.5),
"cm")) + scale_x_continuous(breaks = seq(0, 1, 0.2)) +
scale_y_continuous() + guides(color = guide_legend(title = NULL)),
c("olivedrab", "blue", "red", "violet", "orange", "yellow",
"magenta", "peru", "black", "maroon", "lightblue",
"darkslateblue", "seashell4", "tan2", "darkgreen",
"springgreen"))
}
plotCors
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
plotCors(data, methods = c("None", "HG7", "ERCC", "TN", "TC", "CR", "NR", "DESeq",
"UQ", "TMM", "TU"), legend.position = c(0.15, 0.56))
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
methods |
Please refer to the file /inst/doc/readme.pdf. |
legend.position |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, methods = c("None", "HG7", "ERCC", "TN", "TC",
"CR", "NR", "DESeq", "UQ", "TMM", "TU"), legend.position = c(0.15,
0.56))
{
if (!is.data.frame(data))
data <- data.frame(data)
if (is.factor(data$Value))
data$Value <- as.numeric(as.character(data$Value))
data$Methods <- factor(data$Methods, levels = methods, labels = methods)
change_colours(ggplot(data = data, aes(x = Value, y = ..count../sum(..count..))) +
geom_freqpoly(aes(group = Methods, color = Methods),
size = 3, bins = 50) + xlab("Spearman correlation") +
ylab("Fraction of gene pairs") + theme_bw() + theme(panel.grid.minor = element_blank(),
axis.title.x = element_text(size = 48), axis.title.y = element_text(size = 48),
axis.text.x = element_text(size = 38), axis.text.y = element_text(size = 38),
legend.text = element_text(size = 39), legend.title = element_text(size = 43),
legend.position = legend.position, legend.background = element_blank(),
legend.key = element_blank(), legend.key.height = unit(1.8,
"cm"), plot.margin = unit(c(0.5, 1, 0.5, 0.5), "cm")) +
scale_x_continuous(expand = c(0.01, 0.01), breaks = round(seq(-1,
1, 0.25), 2)) + scale_y_continuous(expand = c(0.01,
0)) + guides(color = guide_legend(title = NULL)), c("olivedrab",
"blue", "red", "violet", "orange", "yellow", "magenta",
"peru", "black", "maroon", "lightblue", "darkslateblue",
"seashell4", "tan2", "darkgreen", "springgreen"))
}
plotHC
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
plotHC(data, method = c("spearman", "pearson", "kendall"), mar = c(9, 1, 0, 20))
Arguments
data |
Please refer to the file /inst/doc/readme.pdf. |
method |
Please refer to the file /inst/doc/readme.pdf. |
mar |
Please refer to the file /inst/doc/readme.pdf. |
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (data, method = c("spearman", "pearson", "kendall"),
mar = c(9, 1, 0, 20))
{
if (!is.data.frame(data))
data <- data.frame(data)
method <- match.arg(method)
hc <- hclust(as.dist(1 - cor(data, method = method)))
dend <- as.dendrogram(hc)
dend <- dend %>% set("labels_cex", 6.5) %>% set("branches_lwd",
6.5)
par(mar = mar, mgp = c(10, 5, 0), cex.axis = 6)
plot(dend, horiz = TRUE)
axis(side = 1, lwd = 8)
}
scRNA663
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
data("scRNA663")Format
A data frame with 57955 observations on the following 663 variables.
col36l_1a numeric vector
col36l_2a numeric vector
col36l_3a numeric vector
col36l_4a numeric vector
col36l_5a numeric vector
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col38l_1a numeric vector
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col39l3_64a numeric vector
col39l3_65a numeric vector
col39l3_66a numeric vector
col39l3_67a numeric vector
col39l3_68a numeric vector
col39l3_69a numeric vector
col39l3_70a numeric vector
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col39l3_72a numeric vector
col39l3_73a numeric vector
col39l3_74a numeric vector
col39l3_75a numeric vector
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col39l3_85a numeric vector
col40l_1a numeric vector
col40l_2a numeric vector
col40l_3a numeric vector
col40l_4a numeric vector
col40l_5a numeric vector
col40l_6a numeric vector
col40l_7a numeric vector
col40l_8a numeric vector
col40l_9a numeric vector
col40l_10a numeric vector
col40l_11a numeric vector
col40l_12a numeric vector
col40l_13a numeric vector
col40l_14a numeric vector
col40l_15a numeric vector
col40l_16a numeric vector
col40l_17a numeric vector
col40l_18a numeric vector
col40l_19a numeric vector
col40l_20a numeric vector
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col40l_42a numeric vector
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col44l1_1a numeric vector
col44l1_2a numeric vector
col44l1_3a numeric vector
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col44l1_14a numeric vector
col44l1_15a numeric vector
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col44l1_17a numeric vector
col44l1_18a numeric vector
col44l1_19a numeric vector
col44l1_20a numeric vector
col44l1_24a numeric vector
col44l1_28a numeric vector
col44l1_29a numeric vector
col44l1_30a numeric vector
col44l1_32a numeric vector
col44l1_33a numeric vector
col44l1_36a numeric vector
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col44l1_40a numeric vector
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col44l1_47a numeric vector
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col44l1_58a numeric vector
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col44l1_66a numeric vector
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col44l1_69a numeric vector
col44l1_70a numeric vector
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col44l1_91a numeric vector
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col44l1_94a numeric vector
col44l2_1a numeric vector
col44l2_2a numeric vector
col44l2_3a numeric vector
col44l2_4a numeric vector
col44l2_5a numeric vector
col44l2_6a numeric vector
col44l2_9a numeric vector
col44l2_10a numeric vector
col44l2_12a numeric vector
col44l2_14a numeric vector
col44l2_17a numeric vector
col44l2_18a numeric vector
col44l2_19a numeric vector
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col44l2_26a numeric vector
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col44l2_31a numeric vector
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col44l2_38a numeric vector
col44l2_40a numeric vector
col44l7_67a numeric vector
col44l7_68a numeric vector
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col44l7_70a numeric vector
col44l7_71a numeric vector
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col44l7_94a numeric vector
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col44l8_17a numeric vector
col44l8_19a numeric vector
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col44l8_28a numeric vector
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col45l2_81a numeric vector
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col48l6_14a numeric vector
col48l6_16a numeric vector
col48l6_17a numeric vector
col48l6_18a numeric vector
col48l6_19a numeric vector
col48l6_20a numeric vector
col48l6_21a numeric vector
col48l6_22a numeric vector
col48l6_24a numeric vector
col48l6_26a numeric vector
col48l6_27a numeric vector
col48l6_28a numeric vector
col48l6_30a numeric vector
col48l6_31a numeric vector
col48l6_34a numeric vector
col48l6_35a numeric vector
col48l6_36a numeric vector
col48l6_39a numeric vector
col48l6_40a numeric vector
col48l6_42a numeric vector
col48l6_43a numeric vector
col48l6_44a numeric vector
col48l6_46a numeric vector
col48l6_47a numeric vector
col48l6_48a numeric vector
col48l6_50a numeric vector
col48l6_51a numeric vector
col48l6_52a numeric vector
col48l6_53a numeric vector
col48l6_54a numeric vector
col48l6_55a numeric vector
col48l6_56a numeric vector
col48l6_58a numeric vector
col48l6_60a numeric vector
col48l6_61a numeric vector
col48l6_62a numeric vector
col48l6_63a numeric vector
col48l6_64a numeric vector
col48l6_65a numeric vector
col48l6_66a numeric vector
col48l6_67a numeric vector
col48l6_68a numeric vector
col48l6_69a numeric vector
col48l6_70a numeric vector
col48l6_71a numeric vector
col48l6_72a numeric vector
col48l6_73a numeric vector
col48l6_74a numeric vector
col48l6_75a numeric vector
col48l6_76a numeric vector
col48l6_77a numeric vector
col48l6_78a numeric vector
col48l6_79a numeric vector
col48l6_80a numeric vector
col48l6_81a numeric vector
col48l6_82a numeric vector
col48l6_85a numeric vector
col48l6_86a numeric vector
col48l6_88a numeric vector
col48l6_90a numeric vector
col48l6_92a numeric vector
col48l6_93a numeric vector
col48l6_94a numeric vector
col48l6_95a numeric vector
col48l6_96a numeric vector
col48l7_1a numeric vector
col48l7_2a numeric vector
col48l7_3a numeric vector
col48l7_4a numeric vector
col48l7_5a numeric vector
col48l7_7a numeric vector
col48l7_9a numeric vector
col48l7_11a numeric vector
col48l7_12a numeric vector
col48l7_13a numeric vector
col48l7_15a numeric vector
col48l7_16a numeric vector
col48l7_18a numeric vector
col48l7_20a numeric vector
col48l7_21a numeric vector
Examples
data(scRNA663)
## maybe str(scRNA663) ; plot(scRNA663) ...
scRNA663_factors
Description
Please refer to the file /inst/doc/readme.pdf.
Usage
data("scRNA663_factors")Format
A data frame with 663 observations on the following 12 variables.
HG7a numeric vector
ERCCa numeric vector
TNa numeric vector
TCa numeric vector
CRa numeric vector
NRa numeric vector
DESeqa numeric vector
UQa numeric vector
TMMa numeric vector
TUa numeric vector
NCSa numeric vector
ESa numeric vector
Examples
data(scRNA663_factors)
## maybe str(scRNA663_factors) ; plot(scRNA663_factors) ...