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  • 15:53, 17 April 2024 Brb talk contribs uploaded File:Tiv-demo.png
  • 15:53, 17 April 2024 Brb talk contribs created page File:Tiv-demo.png
  • 20:17, 12 March 2024 Brb talk contribs uploaded File:Filtered R mean.png (Use sample mean instead of variance for each gene as the filter statistic. <syntaxhighlight lang='r'> # Follow the previous code chunks M2 <- rowMeans(exprs(ALL_bcrneg)) theta <- seq(0, .80, .01) R_BH <- filtered_R(alpha=.10, M2, p2, theta, method="BH") which.max(R_BH) # 10% <---- so theta=0.1 is the optimal; only 10% genes are removed # 11 max(R_BH) # [1] 270 plot(theta, R_BH, type="l", xlab=expression(theta), ylab="Rejections", main="BH cutoff = 0.1") abline(v=.1, lty=2) <...)
  • 20:17, 12 March 2024 Brb talk contribs created page File:Filtered R mean.png (Use sample mean instead of variance for each gene as the filter statistic. <syntaxhighlight lang='r'> # Follow the previous code chunks M2 <- rowMeans(exprs(ALL_bcrneg)) theta <- seq(0, .80, .01) R_BH <- filtered_R(alpha=.10, M2, p2, theta, method="BH") which.max(R_BH) # 10% <---- so theta=0.1 is the optimal; only 10% genes are removed # 11 max(R_BH) # [1] 270 plot(theta, R_BH, type="l", xlab=expression(theta), ylab="Rejections", main="BH cutoff = 0.1") abline(v=.1, lty=2) <...)
  • 08:54, 12 March 2024 Brb talk contribs uploaded File:Rainbow v05.png
  • 08:54, 12 March 2024 Brb talk contribs created page File:Rainbow v05.png
  • 08:53, 12 March 2024 Brb talk contribs uploaded File:Rainbow s05.png
  • 08:53, 12 March 2024 Brb talk contribs created page File:Rainbow s05.png
  • 08:52, 12 March 2024 Brb talk contribs uploaded File:Rainbow default.png (<syntaxhighlight lang='r'> library(shiny) # Define the UI ui <- fluidPage( titlePanel("Rainbow Color Palette"), sidebarLayout( sidebarPanel( sliderInput("s_value", "Saturation (s):", min = 0, max = 1, value = 1, step = 0.01), sliderInput("v_value", "Value (v):", min = 0, max = 1, value = 1, step = 0.01) ), mainPanel( plotOutput("rainbow_plot") ) ) ) # Define the server server <- function(input, output) { output$rainbow_plot <- renderPlot({ s <-...)
  • 08:52, 12 March 2024 Brb talk contribs created page File:Rainbow default.png (<syntaxhighlight lang='r'> library(shiny) # Define the UI ui <- fluidPage( titlePanel("Rainbow Color Palette"), sidebarLayout( sidebarPanel( sliderInput("s_value", "Saturation (s):", min = 0, max = 1, value = 1, step = 0.01), sliderInput("v_value", "Value (v):", min = 0, max = 1, value = 1, step = 0.01) ), mainPanel( plotOutput("rainbow_plot") ) ) ) # Define the server server <- function(input, output) { output$rainbow_plot <- renderPlot({ s <-...)
  • 21:41, 11 March 2024 Brb talk contribs uploaded File:Filtered R.png (<syntaxhighlight lang='r'> theta <- seq(0, .80, .01) R_BH <- filtered_R(alpha=.10, S2, p2, theta, method="BH") which.max(R_BH) # 60% <---- so theta=0.6 is the optimal filtering threshold # 61 max(R_BH) # [1] 380 plot(theta, R_BH, type="l", xlab=expression(theta), ylab="Rejections", main="BH cutoff = 0.1") abline(v=.6, lty=2) </syntaxhighlight>)
  • 21:41, 11 March 2024 Brb talk contribs created page File:Filtered R.png (<syntaxhighlight lang='r'> theta <- seq(0, .80, .01) R_BH <- filtered_R(alpha=.10, S2, p2, theta, method="BH") which.max(R_BH) # 60% <---- so theta=0.6 is the optimal filtering threshold # 61 max(R_BH) # [1] 380 plot(theta, R_BH, type="l", xlab=expression(theta), ylab="Rejections", main="BH cutoff = 0.1") abline(v=.6, lty=2) </syntaxhighlight>)
  • 21:35, 11 March 2024 Brb talk contribs uploaded File:Filtered p.png (Note: # x-axis "p cutoff" should be "BH cutoff" or "FDR cutoff". # Each curve represents theta (filtering threshold). For example, theta=.1 means 10% of genes are filtered out before we do multiple testing (or BH adjustment). # It is seen the larger the theta, the more hypotheses are rejected at the same FDR cutoff. For example, #* if theta=0, 251 hypotheses are rejected at FDR=.1 #* if theta=.5, 355 hypotheses are rejected at FDR=.1. <syntaxhighlight lang='r'> BiocManager::install("ALL")...)
  • 21:35, 11 March 2024 Brb talk contribs created page File:Filtered p.png (Note: # x-axis "p cutoff" should be "BH cutoff" or "FDR cutoff". # Each curve represents theta (filtering threshold). For example, theta=.1 means 10% of genes are filtered out before we do multiple testing (or BH adjustment). # It is seen the larger the theta, the more hypotheses are rejected at the same FDR cutoff. For example, #* if theta=0, 251 hypotheses are rejected at FDR=.1 #* if theta=.5, 355 hypotheses are rejected at FDR=.1. <syntaxhighlight lang='r'> BiocManager::install("ALL")...)
  • 16:49, 8 March 2024 Brb talk contribs uploaded File:DataOutliers2.png ({{Pre}} puree <- read.csv("https://gist.githubusercontent.com/arraytools/e851ed88c7456779557fbf3ed67b157a/raw/9971c61fea1db99acbd9de17ea82679ba9811358/dataOutliers2.csv", header=F) plot(puree[,1], puree[, 2], xlab="X", ylab="Y") abline(lm(V2 ~ V1, data = puree)) # robust regression require(MASS) summary(rlm(V2 ~ V1, data = puree)) abline(rr.huber <- rlm(V2 ~ V1, data = puree), col = "blue") # quantile regression library(quantreg) abline(rq(V2 ~ V1, data=puree, tau = 0.5), col = "red") # theil...)
  • 16:49, 8 March 2024 Brb talk contribs created page File:DataOutliers2.png ({{Pre}} puree <- read.csv("https://gist.githubusercontent.com/arraytools/e851ed88c7456779557fbf3ed67b157a/raw/9971c61fea1db99acbd9de17ea82679ba9811358/dataOutliers2.csv", header=F) plot(puree[,1], puree[, 2], xlab="X", ylab="Y") abline(lm(V2 ~ V1, data = puree)) # robust regression require(MASS) summary(rlm(V2 ~ V1, data = puree)) abline(rr.huber <- rlm(V2 ~ V1, data = puree), col = "blue") # quantile regression library(quantreg) abline(rq(V2 ~ V1, data=puree, tau = 0.5), col = "red") # theil...)
  • 15:27, 7 March 2024 Brb talk contribs uploaded File:DataOutliers.png ({{Pre}} puree <- read.csv("https://gist.githubusercontent.com/arraytools/47d3a46ae1f9a9cd47db350ae2bd2338/raw/b5cccc8e566ff3bef81b1b371e8bfa174c98ef38/dataOutliers.csv", header = FALSE) plot(puree[,1], puree[, 2], xlim=c(0,1), ylim=c(0,1), xlab="X", ylab="Y") abline(0,1, lty=2) abline(lm(V2 ~ V1, data = puree)) # robust regression require(MASS) summary(rlm(V2 ~ V1, data = puree)) abline(rr.huber <- rlm(V2 ~ V1, data = puree), col = "blue") # almost overlapped with lm() # quantile regressio...)
  • 15:27, 7 March 2024 Brb talk contribs created page File:DataOutliers.png ({{Pre}} puree <- read.csv("https://gist.githubusercontent.com/arraytools/47d3a46ae1f9a9cd47db350ae2bd2338/raw/b5cccc8e566ff3bef81b1b371e8bfa174c98ef38/dataOutliers.csv", header = FALSE) plot(puree[,1], puree[, 2], xlim=c(0,1), ylim=c(0,1), xlab="X", ylab="Y") abline(0,1, lty=2) abline(lm(V2 ~ V1, data = puree)) # robust regression require(MASS) summary(rlm(V2 ~ V1, data = puree)) abline(rr.huber <- rlm(V2 ~ V1, data = puree), col = "blue") # almost overlapped with lm() # quantile regressio...)
  • 22:41, 10 February 2024 Brb talk contribs uploaded File:R162.png
  • 22:41, 10 February 2024 Brb talk contribs created page File:R162.png
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