| Title: | Genome-Wide RNA Degradation Analysis Using BRIC-Seq Data |
|---|---|
| Description: | BRIC-seq is a genome-wide approach for determining RNA stability in mammalian cells. This package provides a series of functions for performing quality check of your BRIC-seq data, calculation of RNA half-life for each transcript and comparison of RNA half-lives between two conditions. |
| Authors: | Naoto Imamachi [aut, cre] |
| Maintainer: | Naoto Imamachi <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.0 |
| Built: | 2024-11-18 06:41:14 UTC |
| Source: | https://github.com/imamachi-n/bridger2 |
BridgeRCore is a basic function for calculating RNA half-life
BRIC-seq data and a wrapper of the other individual bridger2 functions.
BridgeRCore(inputFile, inforColumn = 4, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), RPKMcutoff = 0.1, cutoffBelow = 0.1, YMin = -2, YMax = 2, downsamplingFig = 0.2, makeFig = FALSE, cutoffQuantile = 0.975, inforHKGenesRow = "symbol", HKGenes = c("GAPDH", "PGK1", "PPIA", "ENO1", "ATP5B", "ALDOA"), CutoffTimePointNumber = 4, R2_criteria = 0.9, TimePointRemoval1 = c(1, 2), TimePointRemoval2 = c(8, 12), ThresholdHalfLife1 = 3, ThresholdHalfLife2 = 12, save = TRUE, outputPrefix = "BridgeR", normalization = "default", method = "default")BridgeRCore(inputFile, inforColumn = 4, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), RPKMcutoff = 0.1, cutoffBelow = 0.1, YMin = -2, YMax = 2, downsamplingFig = 0.2, makeFig = FALSE, cutoffQuantile = 0.975, inforHKGenesRow = "symbol", HKGenes = c("GAPDH", "PGK1", "PPIA", "ENO1", "ATP5B", "ALDOA"), CutoffTimePointNumber = 4, R2_criteria = 0.9, TimePointRemoval1 = c(1, 2), TimePointRemoval2 = c(8, 12), ThresholdHalfLife1 = 3, ThresholdHalfLife2 = 12, save = TRUE, outputPrefix = "BridgeR", normalization = "default", method = "default")
inputFile |
The vector of tab-delimited matrix file. |
inforColumn |
The number of information columns. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
RPKMcutoff |
Cutoff value of RPKM at 0hr. |
cutoffBelow |
Cutoff value of RPKM at all time points. |
YMin |
Y-axis min. |
YMax |
Y-axis max. |
downsamplingFig |
the factor for downsampling. |
makeFig |
Whether to save the figure of normalization factor. |
cutoffQuantile |
cutoff value of quantile.#' @param save Whether to save the output matrix file. |
inforHKGenesRow |
The column number of house-keeping gene information. |
HKGenes |
The vector of house-keeping genes. |
CutoffTimePointNumber |
The number of minimum time points for calc. |
R2_criteria |
The cutoff of R2 for R2 selection. |
TimePointRemoval1 |
The candicate_1 of time point removal. |
TimePointRemoval2 |
The candicate_2 of time point removal. |
ThresholdHalfLife1 |
The cutoff of TimePointRemoval1. |
ThresholdHalfLife2 |
The cutoff of TimePointRemoval2. |
save |
Whether to save the output matrix file. |
outputPrefix |
The prefix for the name of the output. |
normalization |
select "default" (percentile method) or "house_keeping_genes" |
method |
select "default" (R2 selection/1st-order) or "3models". |
data.table object including RNA half-life, R2 and the selected fitting model.
halflife_table <- BridgeRCore(RNA_halflife_comparison[1:30,], save = FALSE) halflife_table <- BridgeRCore(RNA_halflife_comparison_HK[177:206], save = FALSE, normalization = "house_keeping_genes", method = "3models")halflife_table <- BridgeRCore(RNA_halflife_comparison[1:30,], save = FALSE) halflife_table <- BridgeRCore(RNA_halflife_comparison_HK[177:206], save = FALSE, normalization = "house_keeping_genes", method = "3models")
BridgeRDatasetChecker returns several BRIC-seq dataset information.
This function is used for checking your BRIC-seq dataset quality.
BridgeRDatasetChecker(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, percentile = c(0.99, 0.95, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.05), save = T, outputPrefix = "BridgeR_2_raw")BridgeRDatasetChecker(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, percentile = c(0.99, 0.95, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.05), save = T, outputPrefix = "BridgeR_2_raw")
inputFile |
Input matrix object. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
inforColumn |
The number of information columns. |
percentile |
Percentile numbers. |
save |
Whether to save the output fig file. |
outputPrefix |
The prefix for the name of the output. |
list object about ggplot2 fig data.
library(data.table) normalized_table <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) fig_list_norm <- BridgeRDatasetChecker(inputFile = normalized_table, save = FALSE)library(data.table) normalized_table <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) fig_list_norm <- BridgeRDatasetChecker(inputFile = normalized_table, save = FALSE)
BridgeRDataSetFromMatrix calculates the relative RPKM values compared with 0hr,
importing data.table format.
BridgeRDataSetFromMatrix(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), cutoff = 0.1, cutoffBelow = 0.1, inforColumn = 4, save = T, outputPrefix = "BridgeR_1")BridgeRDataSetFromMatrix(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), cutoff = 0.1, cutoffBelow = 0.1, inforColumn = 4, save = T, outputPrefix = "BridgeR_1")
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
cutoff |
Cutoff value of RPKM at 0hr. |
cutoffBelow |
Cutoff value of RPKM at all time points. |
inforColumn |
The number of information columns. |
save |
Whether to save the output matrix file. |
outputPrefix |
The prefix for the name of the output. |
data.table object about relative RPKM values.
library(data.table) rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(41, 5, 5), CTRL_1_1h = c(48, 7, 6), CTRL_1_2h = c(56, 10, 6), CTRL_1_4h = c(87, 12, 10), CTRL_1_8h = c(124, 20, 11), CTRL_1_12h = c(185, 22, 15), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(21, 10, 3), KD_1_1h = c(33, 11, 3), KD_1_2h = c(42, 15, 4), KD_1_4h = c(60, 20, 5), KD_1_8h = c(65, 37, 6), KD_1_12h = c(70, 42, 6)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) test_table <- BridgeRDataSetFromMatrix(inputFile = rpkm_matrix, group = group, hour = hour, cutoff = 0.1, inforColumn = 4, save = FALSE)library(data.table) rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(41, 5, 5), CTRL_1_1h = c(48, 7, 6), CTRL_1_2h = c(56, 10, 6), CTRL_1_4h = c(87, 12, 10), CTRL_1_8h = c(124, 20, 11), CTRL_1_12h = c(185, 22, 15), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(21, 10, 3), KD_1_1h = c(33, 11, 3), KD_1_2h = c(42, 15, 4), KD_1_4h = c(60, 20, 5), KD_1_8h = c(65, 37, 6), KD_1_12h = c(70, 42, 6)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) test_table <- BridgeRDataSetFromMatrix(inputFile = rpkm_matrix, group = group, hour = hour, cutoff = 0.1, inforColumn = 4, save = FALSE)
BridgeRDataSetFromRaw calculates the relative RPKM values
compared with 0hr, importing tab-delimited txt file.
BridgeRDataSetFromRaw(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), cutoff = 0.1, cutoffBelow = 0.1, inforColumn = 4, save = T, outputPrefix = "BridgeR_1")BridgeRDataSetFromRaw(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), cutoff = 0.1, cutoffBelow = 0.1, inforColumn = 4, save = T, outputPrefix = "BridgeR_1")
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
cutoff |
Cutoff value of RPKM at 0hr. |
cutoffBelow |
Cutoff value of RPKM at all time points. |
inforColumn |
The number of information columns. |
save |
Whether to save the output matrix file. |
outputPrefix |
The prefix for the name of the output. |
data.table object about relative RPKM values.
BridgeReport returns a shinyapp object to draw RNA decay curve.
You can easily check RNA half-life and RNA decay fitting curve on
your web browser.
BridgeReport(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), comparisonFile = c("Control", "Knockdown"), searchRowName = "symbol", inforColumn = 4, color = c("black", "red"), TimePointRemoval1 = c(1, 2), TimePointRemoval2 = c(8, 12))BridgeReport(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), comparisonFile = c("Control", "Knockdown"), searchRowName = "symbol", inforColumn = 4, color = c("black", "red"), TimePointRemoval1 = c(1, 2), TimePointRemoval2 = c(8, 12))
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
comparisonFile |
The vector of group names. |
searchRowName |
Row name for searching. |
inforColumn |
The number of information columns. |
color |
color of line graph for two decay curve. |
TimePointRemoval1 |
The candicate_1 of time point removal. |
TimePointRemoval2 |
The candicate_2 of time point removal. |
shiny.appobj object for searching and showing RNA decay curve for each gene.
library(data.table) normalized_rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalcR2Select(normalized_rpkm_matrix, group = group, hour = hour, save = FALSE) pvalue_table <- BridgeRPvalueEvaluation(halflife_table, save = FALSE) shiny_test <- BridgeReport(pvalue_table)library(data.table) normalized_rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalcR2Select(normalized_rpkm_matrix, group = group, hour = hour, save = FALSE) pvalue_table <- BridgeRPvalueEvaluation(halflife_table, save = FALSE) shiny_test <- BridgeReport(pvalue_table)
BridgeRGrubbsTest calculates the p-value for each gene
using grubbs test. The estimation is based on the standard deviation of
RNA half-lives in control conditions.
BridgeRGrubbsTest(controlFile, compFile, hour = c(0, 1, 2, 4, 8, 12), controlGroup = c("CTRL_PUM1", "CTRL_PUM2", "CTRL_DKD"), inforColumn = 4, compIndex = 2, save = T, outputPrefix = "BridgeR_8")BridgeRGrubbsTest(controlFile, compFile, hour = c(0, 1, 2, 4, 8, 12), controlGroup = c("CTRL_PUM1", "CTRL_PUM2", "CTRL_DKD"), inforColumn = 4, compIndex = 2, save = T, outputPrefix = "BridgeR_8")
controlFile |
The dataframe of halflife table. |
compFile |
The dataframe of RPKM table. |
hour |
The vector of time course about BRIC-seq experiment. |
controlGroup |
The vector of group names. |
inforColumn |
The number of information columns. |
compIndex |
The number of information columns. |
save |
Whether to save the output matrix file. |
outputPrefix |
The prefix for the name of the output. |
data.table object about Grabbs test result.
group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) half_sd_table <- CalcHalflifeDeviation(halflife_table, RNA_halflife_grubbs_test, group = c("CTRL_1", "CTRL_2", "CTRL_3"), save = FALSE) grubbs_table <- BridgeRGrubbsTest(half_sd_table, halflife_table, compIndex = 4, controlGroup = c("CTRL_1", "CTRL_2", "CTRL_3"), save = FALSE)group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) half_sd_table <- CalcHalflifeDeviation(halflife_table, RNA_halflife_grubbs_test, group = c("CTRL_1", "CTRL_2", "CTRL_3"), save = FALSE) grubbs_table <- BridgeRGrubbsTest(half_sd_table, halflife_table, compIndex = 4, controlGroup = c("CTRL_1", "CTRL_2", "CTRL_3"), save = FALSE)
BridgeRHalfLifeCalc3models calculates RNA half-life for each gene
using 3 models methods (older version).
BridgeRHalfLifeCalc3models(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, CutoffTimePointNumber = 4, save = T, outputPrefix = "BridgeR_5")BridgeRHalfLifeCalc3models(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, CutoffTimePointNumber = 4, save = T, outputPrefix = "BridgeR_5")
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
inforColumn |
The number of information columns. |
CutoffTimePointNumber |
The number of minimum time points for calc. |
save |
Whether to save the output matrix file. |
outputPrefix |
The prefix for the name of the output. |
data.table object about RNA half-life, R2 and fitting model.
library(data.table) normalized_rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalc3models(normalized_rpkm_matrix, group = group, hour = hour, save = FALSE)library(data.table) normalized_rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalc3models(normalized_rpkm_matrix, group = group, hour = hour, save = FALSE)
BridgeRHalfLifeCalcR2Select calculates RNA half-life for each gene
using R2 selection method (default version).
BridgeRHalfLifeCalcR2Select(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, CutoffTimePointNumber = 4, R2_criteria = 0.9, TimePointRemoval1 = c(1, 2), TimePointRemoval2 = c(8, 12), ThresholdHalfLife1 = 3, ThresholdHalfLife2 = 12, save = T, outputPrefix = "BridgeR_5")BridgeRHalfLifeCalcR2Select(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, CutoffTimePointNumber = 4, R2_criteria = 0.9, TimePointRemoval1 = c(1, 2), TimePointRemoval2 = c(8, 12), ThresholdHalfLife1 = 3, ThresholdHalfLife2 = 12, save = T, outputPrefix = "BridgeR_5")
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
inforColumn |
The number of information columns. |
CutoffTimePointNumber |
The number of minimum time points for calc. |
R2_criteria |
The cutoff of R2 for R2 selection. |
TimePointRemoval1 |
The candicate_1 of time point removal. |
TimePointRemoval2 |
The candicate_2 of time point removal. |
ThresholdHalfLife1 |
The cutoff of TimePointRemoval1. |
ThresholdHalfLife2 |
The cutoff of TimePointRemoval2. |
save |
Whether to save the output matrix file. |
outputPrefix |
The prefix for the name of the output. |
data.table object about RNA half-life, R2 and fitting model.
library(data.table) normalized_rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalcR2Select(normalized_rpkm_matrix, group = group, hour = hour, save = FALSE)library(data.table) normalized_rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalcR2Select(normalized_rpkm_matrix, group = group, hour = hour, save = FALSE)
BridgeRNormalization calculates the normalized RPKM values.
BridgeRNormalization(inputFile, normFactorFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, save = T, outputPrefix = "BridgeR_4")BridgeRNormalization(inputFile, normFactorFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, save = T, outputPrefix = "BridgeR_4")
inputFile |
The vector of tab-delimited matrix file. |
normFactorFile |
The vector of tab-delimited normalization factor file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
inforColumn |
The number of information columns. |
save |
Whether to save the output matrix file. |
outputPrefix |
The prefix for the name of the output. |
data.table object about normalized RPKM values.
library(data.table) rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(41, 5, 5), CTRL_1_1h = c(48, 7, 6), CTRL_1_2h = c(56, 10, 6), CTRL_1_4h = c(87, 12, 10), CTRL_1_8h = c(124, 20, 11), CTRL_1_12h = c(185, 22, 15), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(21, 10, 3), KD_1_1h = c(33, 11, 3), KD_1_2h = c(42, 15, 4), KD_1_4h = c(60, 20, 5), KD_1_8h = c(65, 37, 6), KD_1_12h = c(70, 42, 6)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) rpkm_list <- BridgeRDataSetFromMatrix(inputFile = rpkm_matrix, group = group, hour = hour, cutoff = 0.1, inforColumn = 4, save = FALSE) raw_table <- rpkm_list[[1]] test_table <- rpkm_list[[2]] factor_table <- BridgeRNormalizationFactors(test_table, save = FALSE) normalized_table <- BridgeRNormalization(test_table, factor_table, save = FALSE)library(data.table) rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(41, 5, 5), CTRL_1_1h = c(48, 7, 6), CTRL_1_2h = c(56, 10, 6), CTRL_1_4h = c(87, 12, 10), CTRL_1_8h = c(124, 20, 11), CTRL_1_12h = c(185, 22, 15), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(21, 10, 3), KD_1_1h = c(33, 11, 3), KD_1_2h = c(42, 15, 4), KD_1_4h = c(60, 20, 5), KD_1_8h = c(65, 37, 6), KD_1_12h = c(70, 42, 6)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) rpkm_list <- BridgeRDataSetFromMatrix(inputFile = rpkm_matrix, group = group, hour = hour, cutoff = 0.1, inforColumn = 4, save = FALSE) raw_table <- rpkm_list[[1]] test_table <- rpkm_list[[2]] factor_table <- BridgeRNormalizationFactors(test_table, save = FALSE) normalized_table <- BridgeRNormalization(test_table, factor_table, save = FALSE)
BridgeRNormalizationFactors calculates the normalization factors
for BRIC-seq datasets.
BridgeRNormalizationFactors(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, save = T, YMin = -2, YMax = 2, downsamplingFig = 0.2, makeFig = FALSE, cutoffQuantile = 0.975, figOutputPrefix = "BridgeR_3_fig", factorOutputPrefix = "BridgeR_3")BridgeRNormalizationFactors(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, save = T, YMin = -2, YMax = 2, downsamplingFig = 0.2, makeFig = FALSE, cutoffQuantile = 0.975, figOutputPrefix = "BridgeR_3_fig", factorOutputPrefix = "BridgeR_3")
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
inforColumn |
The number of information columns. |
save |
Whether to save the output matrix file. |
YMin |
Y-axis min. |
YMax |
Y-axis max. |
downsamplingFig |
the factor for downsampling. |
makeFig |
Whether to save the figure of normalization factor. |
cutoffQuantile |
cutoff value of quantile. |
figOutputPrefix |
The prefix for the name of figure output. |
factorOutputPrefix |
The prefix for the name of factor output. |
data.table object about normalization factors calculated by quantile method.
library(data.table) rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(41, 5, 5), CTRL_1_1h = c(48, 7, 6), CTRL_1_2h = c(56, 10, 6), CTRL_1_4h = c(87, 12, 10), CTRL_1_8h = c(124, 20, 11), CTRL_1_12h = c(185, 22, 15), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(21, 10, 3), KD_1_1h = c(33, 11, 3), KD_1_2h = c(42, 15, 4), KD_1_4h = c(60, 20, 5), KD_1_8h = c(65, 37, 6), KD_1_12h = c(70, 42, 6)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) rpkm_list <- BridgeRDataSetFromMatrix(inputFile = rpkm_matrix, group = group, hour = hour, cutoff = 0.1, inforColumn = 4, save = FALSE) raw_table <- rpkm_list[[1]] test_table <- rpkm_list[[2]] factor_table <- BridgeRNormalizationFactors(test_table, save = FALSE)library(data.table) rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(41, 5, 5), CTRL_1_1h = c(48, 7, 6), CTRL_1_2h = c(56, 10, 6), CTRL_1_4h = c(87, 12, 10), CTRL_1_8h = c(124, 20, 11), CTRL_1_12h = c(185, 22, 15), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(21, 10, 3), KD_1_1h = c(33, 11, 3), KD_1_2h = c(42, 15, 4), KD_1_4h = c(60, 20, 5), KD_1_8h = c(65, 37, 6), KD_1_12h = c(70, 42, 6)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) rpkm_list <- BridgeRDataSetFromMatrix(inputFile = rpkm_matrix, group = group, hour = hour, cutoff = 0.1, inforColumn = 4, save = FALSE) raw_table <- rpkm_list[[1]] test_table <- rpkm_list[[2]] factor_table <- BridgeRNormalizationFactors(test_table, save = FALSE)
BridgeRNormalizationFactorsHK calculates the normalization factors
from house-keeping genes.
BridgeRNormalizationFactorsHK(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, inforHKGenesRow = "symbol", HKGenes = c("GAPDH", "PGK1", "PPIA", "ENO1", "ATP5B", "ALDOA"), save = T, factorOutputPrefix = "BridgeR_3")BridgeRNormalizationFactorsHK(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, inforHKGenesRow = "symbol", HKGenes = c("GAPDH", "PGK1", "PPIA", "ENO1", "ATP5B", "ALDOA"), save = T, factorOutputPrefix = "BridgeR_3")
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
inforColumn |
The number of information columns. |
inforHKGenesRow |
The column number of house-keeping gene information. |
HKGenes |
The vector of house-keeping genes. |
save |
Whether to save the output matrix file. |
factorOutputPrefix |
The prefix for the name of factor output. |
data.table object about normalization factor calculated by house-keeping genes.
library(data.table) rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(41, 5, 5), CTRL_1_1h = c(48, 7, 6), CTRL_1_2h = c(56, 10, 6), CTRL_1_4h = c(87, 12, 10), CTRL_1_8h = c(124, 20, 11), CTRL_1_12h = c(185, 22, 15), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(21, 10, 3), KD_1_1h = c(33, 11, 3), KD_1_2h = c(42, 15, 4), KD_1_4h = c(60, 20, 5), KD_1_8h = c(65, 37, 6), KD_1_12h = c(70, 42, 6)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) rpkm_list <- BridgeRDataSetFromMatrix(inputFile = rpkm_matrix, group = group, hour = hour, cutoff = 0.1, inforColumn = 4, save = FALSE) raw_table <- rpkm_list[[1]] test_table <- rpkm_list[[2]] factor_table <- BridgeRNormalizationFactorsHK(test_table, save = FALSE)library(data.table) rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(41, 5, 5), CTRL_1_1h = c(48, 7, 6), CTRL_1_2h = c(56, 10, 6), CTRL_1_4h = c(87, 12, 10), CTRL_1_8h = c(124, 20, 11), CTRL_1_12h = c(185, 22, 15), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(21, 10, 3), KD_1_1h = c(33, 11, 3), KD_1_2h = c(42, 15, 4), KD_1_4h = c(60, 20, 5), KD_1_8h = c(65, 37, 6), KD_1_12h = c(70, 42, 6)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) rpkm_list <- BridgeRDataSetFromMatrix(inputFile = rpkm_matrix, group = group, hour = hour, cutoff = 0.1, inforColumn = 4, save = FALSE) raw_table <- rpkm_list[[1]] test_table <- rpkm_list[[2]] factor_table <- BridgeRNormalizationFactorsHK(test_table, save = FALSE)
BridgeRPvalueEvaluation calculates the fold-change of RNA half-life
and p-value between two conditions.
BridgeRPvalueEvaluation(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), comparisonFile = c("Control", "Knockdown"), inforColumn = 4, CutoffTimePointNumber = 4, calibration = FALSE, save = TRUE, outputPrefix = "BridgeR_6")BridgeRPvalueEvaluation(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), comparisonFile = c("Control", "Knockdown"), inforColumn = 4, CutoffTimePointNumber = 4, calibration = FALSE, save = TRUE, outputPrefix = "BridgeR_6")
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
comparisonFile |
The vector of group names. |
inforColumn |
The number of information columns. |
CutoffTimePointNumber |
The number of minimum time points for calc. |
calibration |
Calibration of RNA half-life. |
save |
Whether to save the output matrix file. |
outputPrefix |
The prefix for the name of the output. |
data.table object about Fold-change of RNA half-lives, p-value.
library(data.table) normalized_rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalcR2Select(normalized_rpkm_matrix, group = group, hour = hour, save = FALSE) pvalue_table <- BridgeRPvalueEvaluation(halflife_table, group = group, hour = hour, save = FALSE)library(data.table) normalized_rpkm_matrix <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalcR2Select(normalized_rpkm_matrix, group = group, hour = hour, save = FALSE) pvalue_table <- BridgeRPvalueEvaluation(halflife_table, group = group, hour = hour, save = FALSE)
BridgeRResultChecker returns several BRIC-seq result information.
This function is used for checking the distribution of genome-wide RNA half-lives.
BridgeRResultChecker(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, save = T, outputPrefix = "BridgeR_9")BridgeRResultChecker(inputFile, group = c("Control", "Knockdown"), hour = c(0, 1, 2, 4, 8, 12), inforColumn = 4, save = T, outputPrefix = "BridgeR_9")
inputFile |
The vector of tab-delimited matrix file. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
inforColumn |
The number of information columns. |
save |
Whether to save the output fig file. |
outputPrefix |
The prefix for the name of the output. |
list object about ggplot2 fig data.
library(data.table) normalized_table <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalcR2Select(normalized_table, group = group, hour = hour, save = FALSE) pvalue_table <- BridgeRPvalueEvaluation(halflife_table, group = group, hour = hour, save = FALSE) result_fig <- BridgeRResultChecker(pvalue_table, save = FALSE)library(data.table) normalized_table <- data.table(gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), CTRL_1_0h = c(1.00, 1.00, 1.00), CTRL_1_1h = c(1.00, 0.86, 0.96), CTRL_1_2h = c(1.00, 0.96, 0.88), CTRL_1_4h = c(1.00, 0.74, 0.85), CTRL_1_8h = c(1.00, 0.86, 0.68), CTRL_1_12h = c(1.01, 0.65, 0.60), gr_id = c(8, 9, 14), symbol = c("AAAS", "AACS", "AADAT"), accession_id = c("NM_015665", "NM_023928", "NM_182662"), locus = c("chr12", "chr12", "chr4"), KD_1_0h = c(1.00, 1.00, 1.00), KD_1_1h = c(1.01, 0.73, 0.71), KD_1_2h = c(1.01, 0.77, 0.69), KD_1_4h = c(1.01, 0.72, 0.67), KD_1_8h = c(1.01, 0.64, 0.38), KD_1_12h = c(1.00, 0.89, 0.63)) group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) halflife_table <- BridgeRHalfLifeCalcR2Select(normalized_table, group = group, hour = hour, save = FALSE) pvalue_table <- BridgeRPvalueEvaluation(halflife_table, group = group, hour = hour, save = FALSE) result_fig <- BridgeRResultChecker(pvalue_table, save = FALSE)
BridgeRHalfLifeCalcR2Select calculates RPKM SD and RNA half-life SD
for each gene.
CalcHalflifeDeviation(inputFile, rawFile, group = c("CTRL_PUM1", "CTRL_PUM2", "CTRL_DKD"), hour = c(0, 1, 2, 4, 8, 12), save = T, figSave = F, inforColumn = 4, outputPrefix = "BridgeR_7")CalcHalflifeDeviation(inputFile, rawFile, group = c("CTRL_PUM1", "CTRL_PUM2", "CTRL_DKD"), hour = c(0, 1, 2, 4, 8, 12), save = T, figSave = F, inforColumn = 4, outputPrefix = "BridgeR_7")
inputFile |
The dataframe of halflife table. |
rawFile |
The dataframe of RPKM table. |
group |
The vector of group names. |
hour |
The vector of time course about BRIC-seq experiment. |
save |
Whether to save the output matrix file. |
figSave |
Whether to save the output fig file. |
inforColumn |
The number of information columns. |
outputPrefix |
The prefix for the name of the output. |
data.table object about RNA half-life SD.
group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) half_sd_table <- CalcHalflifeDeviation(halflife_table, RNA_halflife_grubbs_test, group = c("CTRL_1", "CTRL_2", "CTRL_3"), save = FALSE)group <- c("Control", "Knockdown") hour <- c(0, 1, 2, 4, 8, 12) half_sd_table <- CalcHalflifeDeviation(halflife_table, RNA_halflife_grubbs_test, group = c("CTRL_1", "CTRL_2", "CTRL_3"), save = FALSE)
A dataset containing the RPKM for each time point, information column, RNA half-life, R2 and fitting model about 200 genes. The variables are as follows:
halflife_tablehalflife_table
A data frame with 200 rows and 52 variables:
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in control condition
RPKM value at 1h in control condition
RPKM value at 2h in control condition
RPKM value at 4h in control condition
RPKM value at 8h in control condition
RPKM value at 12h in control condition
RNA decay fitting model
R2 for fitting curve
RNA half-life
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in control condition
RPKM value at 1h in control condition
RPKM value at 2h in control condition
RPKM value at 4h in control condition
RPKM value at 8h in control condition
RPKM value at 12h in control condition
RNA decay fitting model
R2 for fitting curve
RNA half-life
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in control condition
RPKM value at 1h in control condition
RPKM value at 2h in control condition
RPKM value at 4h in control condition
RPKM value at 8h in control condition
RPKM value at 12h in control condition
RNA decay fitting model
R2 for fitting curve
RNA half-life
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in knockdown condition
RPKM value at 1h in knockdown condition
RPKM value at 2h in knockdown condition
RPKM value at 4h in knockdown condition
RPKM value at 8h in knockdown condition
RPKM value at 12h in knockdown condition
RNA decay fitting model
R2 for fitting curve
RNA half-life
A dataset containing the RPKM for each time point and information column about 200 genes. The variables are as follows:
RNA_halflife_comparisonRNA_halflife_comparison
A data frame with 200 rows and 20 variables:
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in control condition
RPKM value at 1h in control condition
RPKM value at 2h in control condition
RPKM value at 4h in control condition
RPKM value at 8h in control condition
RPKM value at 12h in control condition
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in knockdown condition
RPKM value at 1h in knockdown condition
RPKM value at 2h in knockdown condition
RPKM value at 4h in knockdown condition
RPKM value at 8h in knockdown condition
RPKM value at 12h in knockdown condition
A dataset containing the RPKM for each time point and information column about 200 genes + house-keeping genes. The variables are as follows:
RNA_halflife_comparison_HKRNA_halflife_comparison_HK
A data frame with 200 rows and 20 variables:
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in control condition
RPKM value at 1h in control condition
RPKM value at 2h in control condition
RPKM value at 4h in control condition
RPKM value at 8h in control condition
RPKM value at 12h in control condition
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in knockdown condition
RPKM value at 1h in knockdown condition
RPKM value at 2h in knockdown condition
RPKM value at 4h in knockdown condition
RPKM value at 8h in knockdown condition
RPKM value at 12h in knockdown condition
A dataset containing the RPKM for each time point and information column about 200 genes. The variables are as follows:
RNA_halflife_grubbs_testRNA_halflife_grubbs_test
A data frame with 200 rows and 40 variables:
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in control condition
RPKM value at 1h in control condition
RPKM value at 2h in control condition
RPKM value at 4h in control condition
RPKM value at 8h in control condition
RPKM value at 12h in control condition
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in control condition
RPKM value at 1h in control condition
RPKM value at 2h in control condition
RPKM value at 4h in control condition
RPKM value at 8h in control condition
RPKM value at 12h in control condition
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in control condition
RPKM value at 1h in control condition
RPKM value at 2h in control condition
RPKM value at 4h in control condition
RPKM value at 8h in control condition
RPKM value at 12h in control condition
Group id
Gene symbol
Gene accession id (RefSeq)
Genome locus
RPKM value at 0h in knockdown condition
RPKM value at 1h in knockdown condition
RPKM value at 2h in knockdown condition
RPKM value at 4h in knockdown condition
RPKM value at 8h in knockdown condition
RPKM value at 12h in knockdown condition