From 1fd3b2bad43776b8b58543f296c31c17a2435df0 Mon Sep 17 00:00:00 2001 From: hannesbecher Date: Sun, 21 Nov 2021 23:55:51 +0000 Subject: [PATCH 1/5] seg allo --- .gitignore | 7 + Tetmer/DESCRIPTION | 2 +- Tetmer/R/formulae.R | 27 ++++ Tetmer/R/tetmer.R | 305 ++++++++++++++++++++++++++++++++++---------- 4 files changed, 276 insertions(+), 65 deletions(-) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..2a008c6 --- /dev/null +++ b/.gitignore @@ -0,0 +1,7 @@ +.Rproj.user +.Rhistory +.RData +.Ruserdata +Tetmer*tar.gz +.DS_Store +Tetmer.Rcheck/* diff --git a/Tetmer/DESCRIPTION b/Tetmer/DESCRIPTION index 29785a6..709e691 100644 --- a/Tetmer/DESCRIPTION +++ b/Tetmer/DESCRIPTION @@ -1,7 +1,7 @@ Package: Tetmer Type: Package Title: Fitting Population Parameters to k-mer Spectra -Version: 2.1.0 +Version: 2.1.1 Author: Hannes Becher Maintainer: The package maintainer Description: This package contains a shiny app for fitting population parameters to k-mer spectra. diff --git a/Tetmer/R/formulae.R b/Tetmer/R/formulae.R index 4d3d21b..9113bed 100644 --- a/Tetmer/R/formulae.R +++ b/Tetmer/R/formulae.R @@ -54,6 +54,33 @@ factorAll <- expression( ) +factorTse <- expression( + pal * c( + 4*exp(-3*tth*tdiverg)*tth*( + -2*exp(tdiverg*(tth-2)) + + exp(3*tdiverg*tth) * (2+tth)^2 * (3 + tth) - + 2*exp(2*tth*tdiverg)*(3+4*tth+tth^2) + ), + 2*exp(-1/2*tdiverg*(4+5*tth))*( + 6*exp(tdiverg*tth/2)*tth+ + exp(1/2*tdiverg*(4+5*tth)) * (2+tth)^2 * (3 + tth) + + 2*exp(2*tdiverg+3/2*tdiverg*tth)* + (-6-8*tth+tth^2+tth^3) + ), + 8*exp(-tdiverg*(3+4*tth))*tth*( + -exp(tdiverg+2*tdiverg*tth)+ + exp(3+tdiverg*(1+tth))*(3+tth) + ), + 2*exp(-2*tdiverg*(1+tth))*( + tth + 2*exp(tdiverg*(2+tth))*(3+tth) + ) + )/ (1+tth) / (2+tth)^2 / (3+tth) + + (1-pal) * c(4*tth/(3+tth), + 6*tth/(6+5*tth+tth^2), + 8*tth/(6+11*tth+6*tth^2+tth^3), + 6/(6+11*tth+6*tth^2+tth^3)) +) + factorTraaa <- expression( c( 3*tth / (2 + tth), diff --git a/Tetmer/R/tetmer.R b/Tetmer/R/tetmer.R index 0df6c01..537ef61 100644 --- a/Tetmer/R/tetmer.R +++ b/Tetmer/R/tetmer.R @@ -9,6 +9,7 @@ tbias <- 0.5 tth <- 0.04 tyadj <- 200 tdiverg <- 30 +pallo <- 0 # starting ranges for auto fitting #### @@ -24,6 +25,8 @@ adivl <- 0.1 adivh <- 100 axrangel <- 5 axrangeh <- 200 +apallol <- 0.01 +apalloh <- 0.99 #' Run the Tetmer app @@ -77,8 +80,8 @@ tet.server <- function(input, output) { } -# The user interface -tet.ui <- fluidPage(titlePanel("Tetmer v2.1.0"), +# User interface #### +tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), "Fitting population paramters to k-mer spectra (by Hannes Becher)", fluidRow( column(8, plotOutput('plot')), @@ -95,11 +98,14 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.0"), "Autofit" = "auto") ), radioButtons("mod", "Model", - c("Tetraploid (aabb)" = "tal", - "Tetraploid (aaaa)" = "tau", - "Diploid" = "d", + c("Diploid" = "d", "Triploid (aaa)" = "traaa", - "Triploid (aab)" = "traab" + "Triploid (aab)" = "traab", + "Tetraploid (aaaa)" = "tau", + "Tetraploid (aabb)" = "tal", + "Tetraploid (seg.)" = "tse" + + ) ) ) @@ -121,11 +127,15 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.0"), numericInput('tyadj', 'Monoploid non-rep GS (Mbp)', tyadj) ))), column(3, - conditionalPanel(condition = "(input.fitmod == 'man') && (['tal', 'traab'].includes(input.mod))", + conditionalPanel(condition = "(input.fitmod == 'man') && (['tal', 'traab', 'tse'].includes(input.mod))", wellPanel(h4("4th: Only allopolyploids, adjust sub-genome split time"), numericInput('tdiverg', 'T (in units of 2Ne)', tdiverg) - ) - )), + )), + conditionalPanel(condition = "(input.fitmod == 'man') && (['tse'].includes(input.mod))", + wellPanel(h4("4th: Only seg. allopolyploids, adjust p-allo"), + numericInput('pallo', 'p-allo', pallo) + )) + ), column(3, conditionalPanel(condition = "input.fitmod == 'auto'", wellPanel(h4("2nd: Adjust the fitting area, make all data peaks visible"), @@ -141,12 +151,12 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.0"), wellPanel(h4("3rd: Param ranges"), sliderInput('akcov', 'k-mer multiplicity', - min=5, max = 200, + min=5, max = 300, value=c(akcovl, akcovh)), sliderInput('abias', 'Peak width', min=0.01, max = 4, value=c(abiasl, abiash)), - sliderInput('ath', "log10 of θ", + sliderInput('ath', "log10 of theta", min=-4, max = 1, step = 0.05, value=c(athl, athh)), sliderInput('ayadj', 'Monoploid non-rep GS (Mbp)', @@ -154,17 +164,25 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.0"), value=c(agsl, agsh)) ))), column(3, - conditionalPanel(condition = "(input.fitmod == 'auto') && (['tal', 'traab'].includes(input.mod))", + conditionalPanel(condition = "(input.fitmod == 'auto') && (['tal', 'traab', 'tse'].includes(input.mod))", wellPanel(h4("4th: Allopolyploids only, adjst sub-genome split time"), sliderInput('adiv', 'T (in units of 2Ne)', min=0.001, max=100, value=c(adivl, adivh)) - ) - )) + )), + conditionalPanel(condition = "(input.fitmod == 'auto') && (['tse'].includes(input.mod))", + wellPanel(h4("5th: Proportion of genome that is allopolyploid"), + sliderInput('apallo', 'p-allo', + min=0.0, max=1.0, + value=c(apallol, apalloh)) + )) + + ) ) ) +# function #### #' Run the interactive Tetmer app #' @@ -280,7 +298,7 @@ addvertlines <- function(input, optimised=0){ text(input$tkcov[1]*2, input$tymax*.7*1000, "2x", col="grey", cex=4) text(input$tkcov[1]*3, input$tymax*.7*1000, "3x", col="grey", cex=4) } - if(input$mod %in% c("tau", "tal")){ + if(input$mod %in% c("tau", "tal", "tse")){ abline(v=c(1,2,3,4)*input$tkcov, lty=2,col="grey") text(input$tkcov[1], input$tymax*.7*1000, "1x", col="grey", cex=4) text(input$tkcov[1]*2, input$tymax*.7*1000, "2x", col="grey", cex=4) @@ -301,7 +319,7 @@ addvertlines <- function(input, optimised=0){ text(optimised$par[1]*3, input$ymax*.7*1000000, "3x", col="grey", cex=4) } - if(input$mod%in%c("tau", "tal")){ + if(input$mod%in%c("tau", "tal", "tse")){ abline(v=c(1,2,3,4)*optimised$par[1], lty=2,col="grey") text(optimised$par[1], input$ymax*.7*1000000, "1x", col="grey", cex=4) text(optimised$par[1]*2, input$ymax*.7*1000000, "2x", col="grey", cex=4) @@ -388,6 +406,13 @@ pointsFit <- function(input, optimised=0){ col="red", type = 'l', lty=1, lwd=2 ) } + if(input$mod == "tse"){ + points( + colSums(eval(probs, envir = list(txmin= 1, txmax=input$txmax, tkcov=input$tkcov, tbias=input$tbias)) * + eval(factors, envir=list(tth=input$tth, tdiverg=input$tdiverg, pal=input$pallo)))*input$tyadj*1000000, + col="red", type = 'l', lty=1, lwd=2 + ) + } } if(input$fitmod=="auto"){ if(input$mod %in% c("d", "tau", "traaa")){ @@ -414,9 +439,23 @@ pointsFit <- function(input, optimised=0){ col="red", type = 'l', lty=1, lwd=2 ) + } + if(input$mod == "tse"){ + points(input$axrange[1]:input$axrange[2], + colSums(eval(probs, + envir = list(txmin=input$axrange[1], + txmax=input$axrange[2], + tkcov=optimised$par[1], + tbias=optimised$par[2] + )) * + eval(factors, + envir=list(tth=optimised$par[3], + tdiverg=optimised$par[5], + pal=optimised$par[6])) + )*optimised$par[4]*1000000, + col="red", type = 'l', lty=1, lwd=2 - - + ) } } } @@ -439,6 +478,13 @@ gsFit <- function(input, optimised=0){ ) / input$tkcov /1000000 ) } + if(input$mod == "tse"){ + print(sum(1:1000 * + colSums(eval(probs, envir = list(txmin= 1, txmax=1000, tkcov=input$tkcov, tbias=input$tbias)) * + eval(factors, envir=list(tth=input$tth, tdiverg=input$tdiverg, pal=input$pallo)))*input$tyadj*1000000 + ) / input$tkcov /1000000 + ) + } } if(input$fitmod=="auto"){ if(input$mod %in% c("d", "tau", "traaa")){ @@ -467,9 +513,21 @@ gsFit <- function(input, optimised=0){ tdiverg=optimised$par[5])) )*optimised$par[4]*1000000 ) / optimised$par[1] / 1000000) - - - + } + if(input$mod == "tse"){ + print(sum(1:1000 * + colSums(eval(probs, + envir = list(txmin=1, + txmax=1000, + tkcov=optimised$par[1], + tbias=optimised$par[2] + )) * + eval(factors, + envir=list(tth=optimised$par[3], + tdiverg=optimised$par[5], + pal=optimised$par[6])) + )*optimised$par[4]*1000000 + ) / optimised$par[1] / 1000000) } } } @@ -500,6 +558,22 @@ pointsExtrap <- function(input, optimised){ col="red", type = 'l', lty=2, lwd=2 ) } + if(input$mod == "tse"){ + points(1:input$axrange[1], + colSums(eval(probs, + envir = list(txmin=1, + txmax=input$axrange[1], + tkcov=optimised$par[1], + tbias=optimised$par[2] + )) * + eval(factors, + envir=list(tth=optimised$par[3], + tdiverg=optimised$par[5], + pal=optimised$par[6])) + )*optimised$par[4]*1000000, + col="red", type = 'l', lty=2, lwd=2 + ) + } } pointsContam <- function(input, optimised, spect){ @@ -536,7 +610,25 @@ pointsContam <- function(input, optimised, spect){ ) * optimised$par[4] * 1000000, type = 'l', col = 4, lwd=2 ) -} + } + if(input$mod == "se"){ + + points(1:input$axrange[1], + spect@data[1:input$axrange[1], 2] - + colSums(eval(probs, + envir = list(txmin=1, + txmax=input$axrange[1], + tkcov=optimised$par[1], + tbias=optimised$par[2] + )) * + eval(factors, + envir=list(tth=optimised$par[3], + tdiverg=optimised$par[5], + pal=optimised$par[6])) + ) * optimised$par[4] * 1000000, + type = 'l', col = 4, lwd=2 + ) + } } #' Generate text for Tetmer window @@ -555,8 +647,8 @@ textOut <- function(input, optimised, spec){ "DIPLOID MODEL, MANUAL FIT", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, - "\n θ per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per k-mer:", input$tth, + "\n theta per nucleotide:", round(input$tth/spec@k, 4), "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) @@ -568,8 +660,8 @@ textOut <- function(input, optimised, spec){ "AUTOTETRAPLOID MODEL, MANUAL FIT", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, - "\n θ per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per k-mer:", input$tth, + "\n theta per nucleotide:", round(input$tth/spec@k, 4), "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) @@ -581,8 +673,8 @@ textOut <- function(input, optimised, spec){ "AUTOTRIPLOID MODEL, MANUAL FIT", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, - "\n θ per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per k-mer:", input$tth, + "\n theta per nucleotide:", round(input$tth/spec@k, 4), "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) @@ -594,8 +686,8 @@ textOut <- function(input, optimised, spec){ "ALLOTRIPLOID MODEL, MANUAL FIT", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, - "\n θ per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per k-mer:", input$tth, + "\n theta per nucleotide:", round(input$tth/spec@k, 4), "\n T:", input$tdiverg, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias, @@ -610,8 +702,8 @@ textOut <- function(input, optimised, spec){ "ALLOTETRAPLOID MODEL, MANUAL FIT", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, - "\n θ per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per k-mer:", input$tth, + "\n theta per nucleotide:", round(input$tth/spec@k, 4), "\n T:", input$tdiverg, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias, @@ -620,6 +712,23 @@ textOut <- function(input, optimised, spec){ )) ) } + if(input$mod=="tse"){ + return( + renderText(paste( + "SEG. ALLOTET. MODEL, MANUAL FIT", + "\n k-mer length:", spec@k, + "\n monoploid k-mer cov:", input$tkcov, + "\n theta per k-mer:", input$tth, + "\n theta per nucleotide:", round(input$tth/spec@k, 4), + "\n T:", input$tdiverg, + "\n non-rep GS (Mbp):", input$tyadj, + "\n bias (peak width):", input$tbias, + "\n diverg per k-mer:", round(input$tth*input$tdiverg, 4), + "\ndiverg per nucleotide:", round(input$tth*input$tdiverg/spec@k, 4), + "\n prop. allotet.:", input$pallo + )) + ) + } } # if man if(input$fitmod == "auto"){ if(input$mod=="tal"){ @@ -628,8 +737,8 @@ textOut <- function(input, optimised, spec){ "ALLOTETRAPLOID MODEL, AUTO FITTED", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), - "\n θ per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per k-mer:", round(optimised$par[3],4), + "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), "\n T:", round(optimised$par[5],2), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), @@ -637,7 +746,7 @@ textOut <- function(input, optimised, spec){ "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/spec@k, 4), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n T:", input$adiv[1], input$adiv[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], @@ -645,14 +754,39 @@ textOut <- function(input, optimised, spec){ )) ) } # if allotet + if(input$mod=="tse"){ + return( + renderText(paste( + "ALLOTETRAPLOID MODEL, AUTO FITTED", + "\n k-mer length:", spec@k, + "\n monoploid k-mer cov:", round(optimised$par[1],1), + "\n theta per k-mer:", round(optimised$par[3],4), + "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n T:", round(optimised$par[5],2), + "\n non-rep GS (Mbp):", round(optimised$par[4],1), + "\n bias (peak width):", round(optimised$par[2],1), + "\n diverg per k-mer:", round(optimised$par[3]*optimised$par[5], 4), + "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/spec@k, 4), + "\n prop. allotet.:", round(optimised$par[6], 2), + "\n\nSTARTING RANGES (MIN MAX)", + "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], + "\n T:", input$adiv[1], input$adiv[2], + "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], + "\n bias (peak width):", input$abias[1], input$abias[2], + "\n x range:", input$axrange[1],input$axrange[2], + "\n prop. allotet.:", input$apallo[1], input$apallo[2] + )) + ) + } # if allotet if(input$mod=="traab"){ return( renderText(paste( "ALLOTRIPLOID MODEL, AUTO FITTED", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), - "\n θ per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per k-mer:", round(optimised$par[3],4), + "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), "\n T:", round(optimised$par[5],2), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), @@ -660,7 +794,7 @@ textOut <- function(input, optimised, spec){ "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/spec@k, 4), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n T:", input$adiv[1], input$adiv[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], @@ -674,13 +808,13 @@ textOut <- function(input, optimised, spec){ "AUTOTETRAPLOID MODEL, AUTO FITTED", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), - "\n θ per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per k-mer:", round(optimised$par[3],4), + "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] @@ -693,13 +827,13 @@ textOut <- function(input, optimised, spec){ "AUTOTRIPLOID MODEL, AUTO FITTED", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), - "\n θ per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per k-mer:", round(optimised$par[3],4), + "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] @@ -712,13 +846,13 @@ textOut <- function(input, optimised, spec){ "DIPLOID MODEL, AUTO FITTED", "\n k-mer length:", spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), - "\n θ per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per k-mer:", round(optimised$par[3],4), + "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] @@ -732,7 +866,7 @@ textOut <- function(input, optimised, spec){ return(renderText(paste( "DIPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, + "\n theta per k-mer:", input$tth, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) @@ -743,7 +877,7 @@ textOut <- function(input, optimised, spec){ renderText(paste( "AUTOTETRAPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, + "\n theta per k-mer:", input$tth, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) @@ -754,7 +888,7 @@ textOut <- function(input, optimised, spec){ renderText(paste( "AUTOTRIPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, + "\n theta per k-mer:", input$tth, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) @@ -765,7 +899,7 @@ textOut <- function(input, optimised, spec){ renderText(paste( "ALLOTRIPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, + "\n theta per k-mer:", input$tth, "\n T:", input$tdiverg, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias, @@ -778,7 +912,7 @@ textOut <- function(input, optimised, spec){ renderText(paste( "ALLOTETRAPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, - "\n θ per k-mer:", input$tth, + "\n theta per k-mer:", input$tth, "\n T:", input$tdiverg, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias, @@ -793,14 +927,14 @@ textOut <- function(input, optimised, spec){ renderText(paste( "ALLOTETRAPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), + "\n theta per k-mer:", round(optimised$par[3],4), "\n T:", round(optimised$par[5],2), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n per k-mer diverg:", round(optimised$par[3]*optimised$par[5], 3), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n T:", input$adiv[1], input$adiv[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], @@ -813,14 +947,14 @@ textOut <- function(input, optimised, spec){ renderText(paste( "ALLOTRIPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), + "\n theta per k-mer:", round(optimised$par[3],4), "\n T:", round(optimised$par[5],2), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n per k-mer diverg:", round(optimised$par[3]*optimised$par[5], 3), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n T:", input$adiv[1], input$adiv[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], @@ -833,12 +967,12 @@ textOut <- function(input, optimised, spec){ renderText(paste( "AUTOTETRAPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), + "\n theta per k-mer:", round(optimised$par[3],4), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] @@ -850,12 +984,12 @@ textOut <- function(input, optimised, spec){ renderText(paste( "AUTOTRIPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), + "\n theta per k-mer:", round(optimised$par[3],4), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] @@ -867,12 +1001,12 @@ textOut <- function(input, optimised, spec){ renderText(paste( "DIPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), - "\n θ per k-mer:", round(optimised$par[3],4), + "\n theta per k-mer:", round(optimised$par[3],4), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], - "\n log10 θ per k-mer:", input$ath[1], input$ath[2], + "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], "\n non-rep GS (Mbp):", input$ayadj[1], input$ayadj[2], "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] @@ -946,7 +1080,20 @@ makeMinFun <- function(input){ ) } ) - } + } # allo + if(input$mod == "tse"){ + # parameter vector: 1 - k-mer cov, 2 - peak width, 3 - theta, 4 - GS in Mbp, 5 - divergence + return(function(x, xlimits, spec) { + sum( + + (spec@data$count[xlimits[1]:xlimits[2]] - + colSums(eval(probs, envir = list(txmin=xlimits[1], txmax=xlimits[2], tkcov=x[1], tbias=x[2])) * + eval(factors, envir=list(tth=x[3], tdiverg=x[5], pal=x[6])))*x[4]*1000000) ^2 + + ) + } + ) + } # tse if(input$mod %in% c("tau", "traaa")){ # parameter vector: 1 - k-mer cov, 2 - peak width, 3 - theta, 4 - GS in Mbp return(function(x,xlimits, spec) { @@ -992,6 +1139,19 @@ getStartingVals <- function(input){ ) ) } + if(input$mod == "tse"){ + return( + # kmer coverage, bias, theta, genome size, divergence, p-allo + c( + cov=(input$akcov[1]+input$akcov[2])/2, + bias=(input$abias[1]+input$abias[2])/2, + theta=(10^input$ath[1]+10^input$ath[2])/2, + haplSize=(input$ayadj[1]+input$ayadj[2])/2, + diverg=(input$adiv[1]+input$adiv[2])/2, + pallo=(input$apallo[1]+input$apallo[2])/2 + ) + ) + } } doOptimisation <- function(input, sp){ @@ -1009,6 +1169,20 @@ doOptimisation <- function(input, sp){ ) } # if tal + if(input$mod == "tse"){ + + return( + optim(startingVals, # starting values (vector of) + minFun, + lower=c(input$akcov[1], input$abias[1], 10^input$ath[1], input$ayadj[1], input$adiv[1], input$apallo[1]), + upper=c(input$akcov[2], input$abias[2], 10^input$ath[2], input$ayadj[2], input$adiv[2], input$apallo[2]), + xlimits=c(input$axrange[1],input$axrange[2]), + spec=sp, + method = "L-BFGS-B" + ) + ) + + } # if tse if(input$mod %in% c("d", "tau", "traaa")){ return( optim(startingVals, # starting values (vector of) @@ -1037,6 +1211,9 @@ getFactors <- function(input){ if(input$mod=="tal"){ return(factorAll) } + if(input$mod=="tse"){ + return(factorTse) + } if(input$mod=="traaa"){ return(factorTraaa) } @@ -1056,7 +1233,7 @@ getFactors <- function(input){ #' #' @keywords internal getProbs <- function(input){ - if(input$mod %in% c("tau", "tal")){ + if(input$mod %in% c("tau", "tal", "tse")){ return(probsTet) } if(input$mod %in% c("traaa", "traab")){ From 4b333e4ba0efa56edd6248c22b6cf0e790fb0ab4 Mon Sep 17 00:00:00 2001 From: hannesbecher Date: Thu, 25 Nov 2021 16:45:27 +0000 Subject: [PATCH 2/5] GUI --- Tetmer/R/tetmer.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Tetmer/R/tetmer.R b/Tetmer/R/tetmer.R index 537ef61..2320e7e 100644 --- a/Tetmer/R/tetmer.R +++ b/Tetmer/R/tetmer.R @@ -132,7 +132,7 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), numericInput('tdiverg', 'T (in units of 2Ne)', tdiverg) )), conditionalPanel(condition = "(input.fitmod == 'man') && (['tse'].includes(input.mod))", - wellPanel(h4("4th: Only seg. allopolyploids, adjust p-allo"), + wellPanel(h4("5th: Only seg. allopolyploids, adjust p-allo"), numericInput('pallo', 'p-allo', pallo) )) ), From 6a09092988d01efca1d1375a11aea826a558fc6e Mon Sep 17 00:00:00 2001 From: hannesbecher Date: Fri, 26 Nov 2021 16:11:17 +0000 Subject: [PATCH 3/5] file upload, save fit --- Tetmer/R/tetmer.R | 368 +++++++++++++++++++++++++++------------------- 1 file changed, 213 insertions(+), 155 deletions(-) diff --git a/Tetmer/R/tetmer.R b/Tetmer/R/tetmer.R index 2320e7e..af338b0 100644 --- a/Tetmer/R/tetmer.R +++ b/Tetmer/R/tetmer.R @@ -46,15 +46,15 @@ tet.server <- function(input, output) { factors <<- getFactors(input) # read spectrum - spec <- prepare.spectrum(.sp) + #spec <- prepare.spectrum(.sp) if(input$fitmod=="man"){ - plotSpecApp(input, spec) + plotSpecApp(input, .spec) addvertlines(input) # vertical lines, multiples of n pointsFit(input) - output$outText <- textOut(input, 0, spec) + output$outText <- renderText(textOut(input, 0)) #gsFit(input, 0) # debug return() @@ -62,21 +62,75 @@ tet.server <- function(input, output) { if(input$fitmod == "auto"){ - plotSpecApp(input, spec) + plotSpecApp(input, .spec) minFun <<- makeMinFun(input) startingVals <<- getStartingVals(input) - optimised <- doOptimisation(input, spec) - addvertlines(input, optimised) - pointsFit(input, optimised) - pointsExtrap(input, optimised) - pointsContam(input, optimised, spec) - output$outText <- textOut(input, optimised, spec) + .optimised <<- doOptimisation(input, .spec) + addvertlines(input, .optimised) + pointsFit(input, .optimised) + pointsExtrap(input, .optimised) + pointsContam(input, .optimised, .spec) + output$outText <- renderText(textOut(input, .optimised)) #gsFit(input, optimised) # debug }# if auto }) + observeEvent(input$saveFit, { + outF <- paste0(getwd(), "/", .spec@name, ".fit.txt") + print(paste("Saving fit to", outF)) + #print(textOut(input, 0)) + writeLines(ifelse(input$fitmod=="man", + textOut(input, 0), + textOut(input, .optimised)), + con=outF) + + }) + observeEvent(input$histFile, { + fPath <- input$histFile$datapath + fName <- input$histFile$name + .spec <<- prepare.spectrum(read.spectrum(fPath, + nam=strsplit(fName, "[.]")[[1]][[1]], + k=input$kVal)) + output$plot <- renderPlot({ + + probs <<- getProbs(input) + factors <<- getFactors(input) + + # read spectrum + #spec <- prepare.spectrum(.sp) + + if(input$fitmod=="man"){ + + + plotSpecApp(input, .spec) + addvertlines(input) # vertical lines, multiples of n + pointsFit(input) + output$outText <- renderText(textOut(input, 0)) + #gsFit(input, 0) # debug + return() + + } + + if(input$fitmod == "auto"){ + + plotSpecApp(input, .spec) + minFun <<- makeMinFun(input) + startingVals <<- getStartingVals(input) + .optimised <<- doOptimisation(input, .spec) + addvertlines(input, .optimised) + pointsFit(input, .optimised) + pointsExtrap(input, .optimised) + pointsContam(input, .optimised, .spec) + output$outText <- renderText(textOut(input, .optimised)) + #gsFit(input, optimised) # debug + + }# if auto + + + }) + }) } @@ -86,7 +140,10 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), fluidRow( column(8, plotOutput('plot')), column(4, - verbatimTextOutput("outText") + verbatimTextOutput("outText"), + fluidRow(actionButton("saveFit", "Save Fit"), + numericInput("kVal", "k", 0), + fileInput("histFile", "Choose or drop spectrum file")) ) ), fluidRow( @@ -135,7 +192,7 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), wellPanel(h4("5th: Only seg. allopolyploids, adjust p-allo"), numericInput('pallo', 'p-allo', pallo) )) - ), + ), column(3, conditionalPanel(condition = "input.fitmod == 'auto'", wellPanel(h4("2nd: Adjust the fitting area, make all data peaks visible"), @@ -177,7 +234,7 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), value=c(apallol, apalloh)) )) - ) + ) ) ) @@ -194,7 +251,8 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), #' @examples \dontrun{tetmer(E028)} #' \dontrun{tetmer(E030)} tetmer <- function(sp){ - .sp <<- sp + #.sp <<- sp + .spec <<- prepare.spectrum(sp) shinyApp(ui = tet.ui, server = tet.server) } @@ -354,7 +412,7 @@ plotSpecApp <- function(input, spec){ lty=c(0, 1), pch=c(1, NA), legend=c("Data", "Fit") - ) + ) } if(input$fitmod=="auto"){ @@ -393,11 +451,11 @@ pointsFit <- function(input, optimised=0){ if(input$fitmod=="man"){ if(input$mod %in% c("d", "tau", "traaa")){ - points( - colSums(eval(probs, envir = list(txmin= 1, txmax=input$txmax, tkcov=input$tkcov, tbias=input$tbias)) * - eval(factors, envir=list(tth=input$tth)))*input$tyadj*1000000, - col="red", type = 'l', lty=1, lwd=2 - ) + points( + colSums(eval(probs, envir = list(txmin= 1, txmax=input$txmax, tkcov=input$tkcov, tbias=input$tbias)) * + eval(factors, envir=list(tth=input$tth)))*input$tyadj*1000000, + col="red", type = 'l', lty=1, lwd=2 + ) } if(input$mod %in% c("tal", "traab")){ points( @@ -417,11 +475,11 @@ pointsFit <- function(input, optimised=0){ if(input$fitmod=="auto"){ if(input$mod %in% c("d", "tau", "traaa")){ # fit within range - points(input$axrange[1]:input$axrange[2], - colSums(eval(probs, envir = list(txmin=input$axrange[1], txmax=input$axrange[2], tkcov=optimised$par[1], tbias=optimised$par[2])) * - eval(factors, envir=list(tth=optimised$par[3])))*optimised$par[4]*1000000, - col="red", type = 'l', lty=1, lwd=2 - ) + points(input$axrange[1]:input$axrange[2], + colSums(eval(probs, envir = list(txmin=input$axrange[1], txmax=input$axrange[2], tkcov=optimised$par[1], tbias=optimised$par[2])) * + eval(factors, envir=list(tth=optimised$par[3])))*optimised$par[4]*1000000, + col="red", type = 'l', lty=1, lwd=2 + ) } if(input$mod %in% c("tal", "traab")){ @@ -431,11 +489,11 @@ pointsFit <- function(input, optimised=0){ txmax=input$axrange[2], tkcov=optimised$par[1], tbias=optimised$par[2] - )) * + )) * eval(factors, envir=list(tth=optimised$par[3], tdiverg=optimised$par[5])) - )*optimised$par[4]*1000000, + )*optimised$par[4]*1000000, col="red", type = 'l', lty=1, lwd=2 ) @@ -466,15 +524,15 @@ gsFit <- function(input, optimised=0){ if(input$fitmod=="man"){ if(input$mod %in% c("d", "tau", "traaa")){ print(sum(1:1000 * - colSums(eval(probs, envir = list(txmin= 1, txmax=1000, tkcov=input$tkcov, tbias=input$tbias)) * - eval(factors, envir=list(tth=input$tth)))*input$tyadj*1000000 + colSums(eval(probs, envir = list(txmin= 1, txmax=1000, tkcov=input$tkcov, tbias=input$tbias)) * + eval(factors, envir=list(tth=input$tth)))*input$tyadj*1000000 ) / input$tkcov /1000000 ) } if(input$mod %in% c("tal", "traab")){ print(sum(1:1000 * - colSums(eval(probs, envir = list(txmin= 1, txmax=1000, tkcov=input$tkcov, tbias=input$tbias)) * - eval(factors, envir=list(tth=input$tth, tdiverg=input$tdiverg)))*input$tyadj*1000000 + colSums(eval(probs, envir = list(txmin= 1, txmax=1000, tkcov=input$tkcov, tbias=input$tbias)) * + eval(factors, envir=list(tth=input$tth, tdiverg=input$tdiverg)))*input$tyadj*1000000 ) / input$tkcov /1000000 ) } @@ -490,28 +548,28 @@ gsFit <- function(input, optimised=0){ if(input$mod %in% c("d", "tau", "traaa")){ # fit within range print(sum(1:1000 * - colSums(eval(probs, envir = list(txmin=1, - txmax=1000, - tkcov=optimised$par[1], - tbias=optimised$par[2])) * - eval(factors, envir=list(tth=optimised$par[3])) - )*optimised$par[4]*1000000 + colSums(eval(probs, envir = list(txmin=1, + txmax=1000, + tkcov=optimised$par[1], + tbias=optimised$par[2])) * + eval(factors, envir=list(tth=optimised$par[3])) + )*optimised$par[4]*1000000 ) / optimised$par[1] / 1000000 ) } if(input$mod %in% c("tal", "traab")){ print(sum(1:1000 * - colSums(eval(probs, - envir = list(txmin=1, - txmax=1000, - tkcov=optimised$par[1], - tbias=optimised$par[2] - )) * - eval(factors, - envir=list(tth=optimised$par[3], - tdiverg=optimised$par[5])) - )*optimised$par[4]*1000000 + colSums(eval(probs, + envir = list(txmin=1, + txmax=1000, + tkcov=optimised$par[1], + tbias=optimised$par[2] + )) * + eval(factors, + envir=list(tth=optimised$par[3], + tdiverg=optimised$par[5])) + )*optimised$par[4]*1000000 ) / optimised$par[1] / 1000000) } if(input$mod == "tse"){ @@ -582,14 +640,14 @@ pointsContam <- function(input, optimised, spect){ points(1:input$axrange[1], spect@data[1:input$axrange[1], 2] - - colSums(eval(probs, - envir = list(txmin=1, - txmax=input$axrange[1], - tkcov=optimised$par[1], - tbias=optimised$par[2]) - ) * - eval(factors, envir=list(tth=optimised$par[3])) - ) * optimised$par[4]*1000000, + colSums(eval(probs, + envir = list(txmin=1, + txmax=input$axrange[1], + tkcov=optimised$par[1], + tbias=optimised$par[2]) + ) * + eval(factors, envir=list(tth=optimised$par[3])) + ) * optimised$par[4]*1000000, type='l', col=4, lwd=2 ) @@ -598,16 +656,16 @@ pointsContam <- function(input, optimised, spect){ points(1:input$axrange[1], spect@data[1:input$axrange[1], 2] - - colSums(eval(probs, - envir = list(txmin=1, - txmax=input$axrange[1], - tkcov=optimised$par[1], - tbias=optimised$par[2] - )) * - eval(factors, - envir=list(tth=optimised$par[3], - tdiverg=optimised$par[5])) - ) * optimised$par[4] * 1000000, + colSums(eval(probs, + envir = list(txmin=1, + txmax=input$axrange[1], + tkcov=optimised$par[1], + tbias=optimised$par[2] + )) * + eval(factors, + envir=list(tth=optimised$par[3], + tdiverg=optimised$par[5])) + ) * optimised$par[4] * 1000000, type = 'l', col = 4, lwd=2 ) } @@ -639,111 +697,111 @@ pointsContam <- function(input, optimised, spect){ #' @return A string of the fitted parameters produced by \code{renderText()} #' to be displayed in the Tetmer window. #' @keywords internal -textOut <- function(input, optimised, spec){ - if(spec@k > 0){ +textOut <- function(input, optimised){ + if(.spec@k > 0){ if(input$fitmod == "man"){ if(input$mod=="d"){ - return(renderText(paste( + return(paste( "DIPLOID MODEL, MANUAL FIT", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, - "\n theta per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per nucleotide:", round(input$tth/.spec@k, 4), "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) - ) + } if(input$mod=="tau"){ return( - renderText(paste( + paste( "AUTOTETRAPLOID MODEL, MANUAL FIT", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, - "\n theta per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per nucleotide:", round(input$tth/.spec@k, 4), "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) - ) + } if(input$mod=="traaa"){ return( - renderText(paste( + paste( "AUTOTRIPLOID MODEL, MANUAL FIT", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, - "\n theta per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per nucleotide:", round(input$tth/.spec@k, 4), "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) - ) + } if(input$mod=="traab"){ return( - renderText(paste( + paste( "ALLOTRIPLOID MODEL, MANUAL FIT", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, - "\n theta per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per nucleotide:", round(input$tth/.spec@k, 4), "\n T:", input$tdiverg, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias, "\n diverg per k-mer:", round(input$tth*input$tdiverg, 4), - "\ndiverg per nucleotide:", round(input$tth*input$tdiverg/spec@k, 4) + "\ndiverg per nucleotide:", round(input$tth*input$tdiverg/.spec@k, 4) )) - ) + } if(input$mod=="tal"){ return( - renderText(paste( + paste( "ALLOTETRAPLOID MODEL, MANUAL FIT", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, - "\n theta per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per nucleotide:", round(input$tth/.spec@k, 4), "\n T:", input$tdiverg, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias, "\n diverg per k-mer:", round(input$tth*input$tdiverg, 4), - "\ndiverg per nucleotide:", round(input$tth*input$tdiverg/spec@k, 4) + "\ndiverg per nucleotide:", round(input$tth*input$tdiverg/.spec@k, 4) )) - ) + } if(input$mod=="tse"){ return( - renderText(paste( + paste( "SEG. ALLOTET. MODEL, MANUAL FIT", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, - "\n theta per nucleotide:", round(input$tth/spec@k, 4), + "\n theta per nucleotide:", round(input$tth/.spec@k, 4), "\n T:", input$tdiverg, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias, "\n diverg per k-mer:", round(input$tth*input$tdiverg, 4), - "\ndiverg per nucleotide:", round(input$tth*input$tdiverg/spec@k, 4), + "\ndiverg per nucleotide:", round(input$tth*input$tdiverg/.spec@k, 4), "\n prop. allotet.:", input$pallo )) - ) + } } # if man if(input$fitmod == "auto"){ if(input$mod=="tal"){ return( - renderText(paste( + paste( "ALLOTETRAPLOID MODEL, AUTO FITTED", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), - "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per nucleotide:", round(optimised$par[3] / .spec@k,5), "\n T:", round(optimised$par[5],2), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n diverg per k-mer:", round(optimised$par[3]*optimised$par[5], 4), - "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/spec@k, 4), + "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/.spec@k, 4), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], @@ -752,21 +810,21 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } # if allotet if(input$mod=="tse"){ return( - renderText(paste( + paste( "ALLOTETRAPLOID MODEL, AUTO FITTED", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), - "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per nucleotide:", round(optimised$par[3] / .spec@k,5), "\n T:", round(optimised$par[5],2), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n diverg per k-mer:", round(optimised$par[3]*optimised$par[5], 4), - "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/spec@k, 4), + "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/.spec@k, 4), "\n prop. allotet.:", round(optimised$par[6], 2), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], @@ -777,21 +835,21 @@ textOut <- function(input, optimised, spec){ "\n x range:", input$axrange[1],input$axrange[2], "\n prop. allotet.:", input$apallo[1], input$apallo[2] )) - ) + } # if allotet if(input$mod=="traab"){ return( - renderText(paste( + paste( "ALLOTRIPLOID MODEL, AUTO FITTED", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), - "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per nucleotide:", round(optimised$par[3] / .spec@k,5), "\n T:", round(optimised$par[5],2), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n diverg per k-mer:", round(optimised$par[3]*optimised$par[5], 4), - "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/spec@k, 4), + "\ndiverg per nucleotide:", round(optimised$par[3]*optimised$par[5]/.spec@k, 4), "\n\nSTARTING RANGES (MIN MAX)", "\n monoploid k-mer cov:", input$akcov[1], input$akcov[2], "\nlog10 theta per k-mer:", input$ath[1], input$ath[2], @@ -800,16 +858,16 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } # if allotrip if(input$mod=="tau"){ return( - renderText(paste( + paste( "AUTOTETRAPLOID MODEL, AUTO FITTED", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), - "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per nucleotide:", round(optimised$par[3] / .spec@k,5), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", @@ -819,16 +877,16 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } # if tau if(input$mod=="traaa"){ return( - renderText(paste( + paste( "AUTOTRIPLOID MODEL, AUTO FITTED", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), - "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per nucleotide:", round(optimised$par[3] / .spec@k,5), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", @@ -838,16 +896,16 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } # if traab if(input$mod=="d"){ return( - renderText(paste( + paste( "DIPLOID MODEL, AUTO FITTED", - "\n k-mer length:", spec@k, + "\n k-mer length:", .spec@k, "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), - "\n theta per nucleotide:", round(optimised$par[3] / spec@k,5), + "\n theta per nucleotide:", round(optimised$par[3] / .spec@k,5), "\n non-rep GS (Mbp):", round(optimised$par[4],1), "\n bias (peak width):", round(optimised$par[2],1), "\n\nSTARTING RANGES (MIN MAX)", @@ -857,46 +915,46 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } #if d } # if auto fit } # if k > 0 if(input$fitmod == "man"){ if(input$mod=="d"){ - return(renderText(paste( + return(paste( "DIPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) - ) + } if(input$mod=="tau"){ return( - renderText(paste( + paste( "AUTOTETRAPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) - ) + } if(input$mod=="traaa"){ return( - renderText(paste( + paste( "AUTOTRIPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, "\n non-rep GS (Mbp):", input$tyadj, "\n bias (peak width):", input$tbias )) - ) + } if(input$mod=="traab"){ return( - renderText(paste( + paste( "ALLOTRIPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, @@ -905,11 +963,11 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$tbias, "\n diverg per k-mer:", round(input$tth*input$tdiverg, 4) )) - ) + } if(input$mod=="tal"){ return( - renderText(paste( + paste( "ALLOTETRAPLOID MODEL, MANUAL FIT", "\n monoploid k-mer cov:", input$tkcov, "\n theta per k-mer:", input$tth, @@ -918,13 +976,13 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$tbias, "\n diverg per k-mer:", round(input$tth*input$tdiverg, 4) )) - ) + } } # if man if(input$fitmod == "auto"){ if(input$mod=="tal"){ return( - renderText(paste( + paste( "ALLOTETRAPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), @@ -940,11 +998,11 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } # if allotet if(input$mod=="traab"){ return( - renderText(paste( + paste( "ALLOTRIPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), @@ -960,11 +1018,11 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } # if allotrip if(input$mod=="tau"){ return( - renderText(paste( + paste( "AUTOTETRAPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), @@ -977,11 +1035,11 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } # if tau if(input$mod=="traaa"){ return( - renderText(paste( + paste( "AUTOTRIPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), @@ -994,11 +1052,11 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } # if traab if(input$mod=="d"){ return( - renderText(paste( + paste( "DIPLOID MODEL, AUTO FITTED", "\n monoploid k-mer cov:", round(optimised$par[1],1), "\n theta per k-mer:", round(optimised$par[3],4), @@ -1011,7 +1069,7 @@ textOut <- function(input, optimised, spec){ "\n bias (peak width):", input$abias[1], input$abias[2], "\n x range:", input$axrange[1],input$axrange[2] )) - ) + } #if d } # if auto fit } @@ -1159,13 +1217,13 @@ doOptimisation <- function(input, sp){ return( optim(startingVals, # starting values (vector of) - minFun, - lower=c(input$akcov[1], input$abias[1], 10^input$ath[1], input$ayadj[1], input$adiv[1]), - upper=c(input$akcov[2], input$abias[2], 10^input$ath[2], input$ayadj[2], input$adiv[2]), - xlimits=c(input$axrange[1],input$axrange[2]), - spec=sp, - method = "L-BFGS-B" - ) + minFun, + lower=c(input$akcov[1], input$abias[1], 10^input$ath[1], input$ayadj[1], input$adiv[1]), + upper=c(input$akcov[2], input$abias[2], 10^input$ath[2], input$ayadj[2], input$adiv[2]), + xlimits=c(input$axrange[1],input$axrange[2]), + spec=sp, + method = "L-BFGS-B" + ) ) } # if tal @@ -1186,13 +1244,13 @@ doOptimisation <- function(input, sp){ if(input$mod %in% c("d", "tau", "traaa")){ return( optim(startingVals, # starting values (vector of) - minFun, - lower=c(input$akcov[1], input$abias[1], 10^input$ath[1], input$ayadj[1]), - upper=c(input$akcov[2], input$abias[2], 10^input$ath[2], input$ayadj[2]), - xlimits=c(input$axrange[1],input$axrange[2]), - spec = sp, - method = "L-BFGS-B" - ) + minFun, + lower=c(input$akcov[1], input$abias[1], 10^input$ath[1], input$ayadj[1]), + upper=c(input$akcov[2], input$abias[2], 10^input$ath[2], input$ayadj[2]), + xlimits=c(input$axrange[1],input$axrange[2]), + spec = sp, + method = "L-BFGS-B" + ) ) } From e5069aacc216d892b88a71538f173ace5ace4975 Mon Sep 17 00:00:00 2001 From: hannesbecher Date: Tue, 30 Nov 2021 11:10:45 +0000 Subject: [PATCH 4/5] save fit, drag'n'drop, and seg tet --- Tetmer/NAMESPACE | 4 + Tetmer/R/data.R | 2 +- Tetmer/R/tetmer.R | 193 +++++++++++++++++++++++++++++------ Tetmer/man/read.spectrum.Rd | 12 +-- Tetmer/man/spectrum-class.Rd | 4 +- Tetmer/man/textOut.Rd | 2 +- 6 files changed, 174 insertions(+), 43 deletions(-) diff --git a/Tetmer/NAMESPACE b/Tetmer/NAMESPACE index eacf3dc..0dadad6 100644 --- a/Tetmer/NAMESPACE +++ b/Tetmer/NAMESPACE @@ -1,7 +1,11 @@ # Generated by roxygen2: do not edit by hand S3method(plot,spectrum) +export(allowSegTet) +export(makeExpectedSpectrum) export(read.spectrum) +export(setSliderRanges) +export(sliderRanges) export(tetmer) exportClasses(spectrum) importFrom(methods,new) diff --git a/Tetmer/R/data.R b/Tetmer/R/data.R index 132e9c1..a219dea 100644 --- a/Tetmer/R/data.R +++ b/Tetmer/R/data.R @@ -1,4 +1,4 @@ -# Descriptioins of the data sets. +# Descriptions of the data sets. #' K-mer spectrum of \emph{Euphrasia arctica} individual E028 #' diff --git a/Tetmer/R/tetmer.R b/Tetmer/R/tetmer.R index af338b0..c61da50 100644 --- a/Tetmer/R/tetmer.R +++ b/Tetmer/R/tetmer.R @@ -28,6 +28,33 @@ axrangeh <- 200 apallol <- 0.01 apalloh <- 0.99 +.sliderRanges <-list(gsMin=1, + gsMax=2000, + kcovMin=5, + kcovMax=300, + biasMin=0.01, + biasMax=4, + thMin=-4, + thMax=1, + divMin=0.001, + divMax=100, + xrangeMin=0, + xrangeMax=500, + palloMin=0, + palloMax=1, + ymax=30) + + +modelClasses <- + list("Diploid" = "d", + "Triploid (aaa)" = "traaa", + "Triploid (aab)" = "traab", + "Tetraploid (aaaa)" = "tau", + "Tetraploid (aabb)" = "tal"#, + #"Tetraploid (seg.)" = "tse" +) + + #' Run the Tetmer app #' @@ -66,6 +93,7 @@ tet.server <- function(input, output) { minFun <<- makeMinFun(input) startingVals <<- getStartingVals(input) .optimised <<- doOptimisation(input, .spec) + .model <<- input$mod addvertlines(input, .optimised) pointsFit(input, .optimised) pointsExtrap(input, .optimised) @@ -85,6 +113,19 @@ tet.server <- function(input, output) { textOut(input, 0), textOut(input, .optimised)), con=outF) + }) + + observeEvent(input$saveFitAs, { + outF <- file.choose(new=T) + if(!endsWith(outF, "txt")) {outF <- paste0(outF, ".txt")} + #paste0(getwd(), "/", .spec@name, ".fit.txt") + print(paste("Saving fit to", outF)) + #print(textOut(input, 0)) + writeLines(ifelse(input$fitmod=="man", + textOut(input, 0), + textOut(input, .optimised)), + con=outF) + }) observeEvent(input$histFile, { @@ -135,37 +176,37 @@ tet.server <- function(input, output) { # User interface #### -tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), + + + + +makeUI <- function(){ + fluidPage(titlePanel("Tetmer v2.1.1"), "Fitting population paramters to k-mer spectra (by Hannes Becher)", fluidRow( column(8, plotOutput('plot')), column(4, verbatimTextOutput("outText"), - fluidRow(actionButton("saveFit", "Save Fit"), - numericInput("kVal", "k", 0), + fluidRow(actionButton("saveFit", "Save fit"), + actionButton("saveFitAs", "Save fit as..."), + numericInput("kVal", "k-mer size (only for Drag'n'Drop)", 0), fileInput("histFile", "Choose or drop spectrum file")) ) ), fluidRow( column(3, - wellPanel(h4("1st: Select fitting mode and model"), - checkboxInput("showData", "Show data", value = TRUE), - radioButtons("fitmod", "Fitting mode", - c("Manual" = "man", - "Autofit" = "auto") - ), - radioButtons("mod", "Model", - c("Diploid" = "d", - "Triploid (aaa)" = "traaa", - "Triploid (aab)" = "traab", - "Tetraploid (aaaa)" = "tau", - "Tetraploid (aabb)" = "tal", - "Tetraploid (seg.)" = "tse" - - - ) - ) - ) + + wellPanel(h4("1st: Select fitting mode and model"), + checkboxInput("showData", "Show data", value = TRUE), + radioButtons("fitmod", "Fitting mode", + c("Manual" = "man", + "Autofit" = "auto") + ), + radioButtons("mod", "Model", modelClasses + + ) + ) + ), column(3, conditionalPanel(condition = "input.fitmod == 'man'", @@ -180,7 +221,7 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), h4("3rd: Param ranges"), numericInput('tkcov', 'Monoploid k-mer multiplicity', tkcov), numericInput('tbias', 'Peak width', tbias), - numericInput('tth', 'θ', tth), + numericInput('tth', 'theta', tth), numericInput('tyadj', 'Monoploid non-rep GS (Mbp)', tyadj) ))), column(3, @@ -197,10 +238,10 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), conditionalPanel(condition = "input.fitmod == 'auto'", wellPanel(h4("2nd: Adjust the fitting area, make all data peaks visible"), sliderInput("axrange", "x limits for fitting", - min=0, max = 500, + min=.sliderRanges$xrangeMin, max = .sliderRanges$xrangeMax, value=c(axrangel,axrangeh)), sliderInput("ymax", "y axis max (does not affect fit)", - min=0, max = 100, + min=0, max = .sliderRanges$ymax, value=10) ))), column(3, @@ -208,29 +249,29 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), wellPanel(h4("3rd: Param ranges"), sliderInput('akcov', 'k-mer multiplicity', - min=5, max = 300, + min=.sliderRanges$kcovMin, max = .sliderRanges$kcovMax, value=c(akcovl, akcovh)), sliderInput('abias', 'Peak width', - min=0.01, max = 4, + min=.sliderRanges$biasMin, max = .sliderRanges$biasMax, value=c(abiasl, abiash)), sliderInput('ath', "log10 of theta", - min=-4, max = 1, step = 0.05, + min=.sliderRanges$thMin, max = .sliderRanges$thMax, step = 0.05, value=c(athl, athh)), sliderInput('ayadj', 'Monoploid non-rep GS (Mbp)', - min=1, max =2000, + min=.sliderRanges$gsMin, max = .sliderRanges$gsMax, value=c(agsl, agsh)) ))), column(3, conditionalPanel(condition = "(input.fitmod == 'auto') && (['tal', 'traab', 'tse'].includes(input.mod))", wellPanel(h4("4th: Allopolyploids only, adjst sub-genome split time"), sliderInput('adiv', 'T (in units of 2Ne)', - min=0.001, max=100, + min=.sliderRanges$divMin, max=.sliderRanges$divMax, value=c(adivl, adivh)) )), conditionalPanel(condition = "(input.fitmod == 'auto') && (['tse'].includes(input.mod))", wellPanel(h4("5th: Proportion of genome that is allopolyploid"), sliderInput('apallo', 'p-allo', - min=0.0, max=1.0, + min=.sliderRanges$palloMin, max=.sliderRanges$palloMax, value=c(apallol, apalloh)) )) @@ -238,6 +279,9 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), ) ) +} + + # function #### @@ -253,15 +297,16 @@ tet.ui <- fluidPage(titlePanel("Tetmer v2.1.1"), tetmer <- function(sp){ #.sp <<- sp .spec <<- prepare.spectrum(sp) - shinyApp(ui = tet.ui, server = tet.server) + #shinyApp(ui = tet.ui, server = tet.server) + shinyApp(ui = makeUI(), server = tet.server) } #' A named k-mer spectrum class #' #' @slot name A string indicating the name of the spectrum (or sample) #' -#' @slot data A `data.frame` with numeric cloumns mult and count. -#' @slot k A `numeric` indiciating the k-mer length. +#' @slot data A `data.frame` with numeric columns `mult` and `count`. +#' @slot k A `numeric` indicating the k-mer length. #' #' @export setClass("spectrum", slots=list(name="character", data="data.frame", k="numeric")) @@ -1302,3 +1347,85 @@ getProbs <- function(input){ } } +#' @export +sliderRanges <- function(){ + return(.sliderRanges) +} + + +#' @export +setSliderRanges <- function(x){ + assignInMyNamespace(".sliderRanges", x) +} + + +#' @export +allowSegTet <- function(){ + + assignInMyNamespace("modelClasses", + list("Diploid" = "d", + "Triploid (aaa)" = "traaa", + "Triploid (aab)" = "traab", + "Tetraploid (aaaa)" = "tau", + "Tetraploid (aabb)" = "tal", + "Tetraploid (seg.)" = "tse" + ) + ) +} + +#' @export +makeExpectedSpectrum <- function(params, modelType, nam="", k=0){ + input <- params + input$mod <- modelType + probs <<- getProbs(input) + factors <<- getFactors(input) + + + if(modelType %in% c("d", "tau", "traaa")){ + # fit within range + points(input$axrange[1]:input$axrange[2], + colSums(eval(probs, envir = list(txmin=input$axrange[1], txmax=input$axrange[2], tkcov=optimised$par[1], tbias=optimised$par[2])) * + eval(factors, envir=list(tth=optimised$par[3])))*optimised$par[4]*1000000, + col="red", type = 'l', lty=1, lwd=2 + ) + + } + if(modelType %in% c("tal", "traab")){ + points(input$axrange[1]:input$axrange[2], + colSums(eval(probs, + envir = list(txmin=input$axrange[1], + txmax=input$axrange[2], + tkcov=optimised$par[1], + tbias=optimised$par[2] + )) * + eval(factors, + envir=list(tth=optimised$par[3], + tdiverg=optimised$par[5])) + )*optimised$par[4]*1000000, + col="red", type = 'l', lty=1, lwd=2 + + ) + } + if(modelType == "tse"){ + points(input$axrange[1]:input$axrange[2], + colSums(eval(probs, + envir = list(txmin=input$axrange[1], + txmax=input$axrange[2], + tkcov=optimised$par[1], + tbias=optimised$par[2] + )) * + eval(factors, + envir=list(tth=optimised$par[3], + tdiverg=optimised$par[5], + pal=optimised$par[6])) + )*optimised$par[4]*1000000, + col="red", type = 'l', lty=1, lwd=2 + + ) + } + + return(new("spectrum", + name=nam, + data=data.frame(mult=, count=), + k=k)) +} diff --git a/Tetmer/man/read.spectrum.Rd b/Tetmer/man/read.spectrum.Rd index 9fe04ce..35fb5d7 100644 --- a/Tetmer/man/read.spectrum.Rd +++ b/Tetmer/man/read.spectrum.Rd @@ -23,10 +23,10 @@ k-mer spectrum Uses \code{read.table()} to read in a k-mer spectrum. } \examples{ -testdf <- data.frame(mult=1:100, count = 100:1) -tf <- tempfile() -write.table(testdf, tf) -sp <- read.spectrum(tf, nam = "Test spectrum") -unlink(tf) -plot(sp) +\dontrun{testdf <- data.frame(mult=1:100, count = 100:1)} +\dontrun{tf <- tempfile()} +\dontrun{write.table(testdf, tf)} +\dontrun{sp <- read.spectrum(tf, nam = "Test spectrum")} +\dontrun{unlink(tf)} +\dontrun{plot(sp)} } diff --git a/Tetmer/man/spectrum-class.Rd b/Tetmer/man/spectrum-class.Rd index eb59b67..1cbe683 100644 --- a/Tetmer/man/spectrum-class.Rd +++ b/Tetmer/man/spectrum-class.Rd @@ -12,8 +12,8 @@ A named k-mer spectrum class \describe{ \item{\code{name}}{A string indicating the name of the spectrum (or sample)} -\item{\code{data}}{A \code{data.frame} with numeric cloumns mult and count.} +\item{\code{data}}{A \code{data.frame} with numeric columns \code{mult} and \code{count}.} -\item{\code{k}}{A \code{numeric} indiciating the k-mer length.} +\item{\code{k}}{A \code{numeric} indicating the k-mer length.} }} diff --git a/Tetmer/man/textOut.Rd b/Tetmer/man/textOut.Rd index 21029ba..1158b27 100644 --- a/Tetmer/man/textOut.Rd +++ b/Tetmer/man/textOut.Rd @@ -4,7 +4,7 @@ \alias{textOut} \title{Generate text for Tetmer window} \usage{ -textOut(input, optimised = 0) +textOut(input, optimised) } \arguments{ \item{input}{Input from the GUI (contains plotting range, model, etc.)} From 36b15ff37a3e156c82b3431758fd2a127edc6011 Mon Sep 17 00:00:00 2001 From: hannesbecher Date: Tue, 30 Nov 2021 13:19:24 +0000 Subject: [PATCH 5/5] rearranged buttons etc. --- Tetmer/DESCRIPTION | 6 +-- Tetmer/R/tetmer.R | 67 +++++++++++++++++++++------------ Tetmer/data-raw/save_spectra.R | 2 +- Tetmer/data/E030.rda | Bin 272801 -> 4647 bytes Tetmer/man/read.spectrum.Rd | 2 +- Tetmer/man/tetmer.Rd | 2 +- 6 files changed, 49 insertions(+), 30 deletions(-) diff --git a/Tetmer/DESCRIPTION b/Tetmer/DESCRIPTION index 709e691..259679c 100644 --- a/Tetmer/DESCRIPTION +++ b/Tetmer/DESCRIPTION @@ -1,10 +1,10 @@ Package: Tetmer Type: Package Title: Fitting Population Parameters to k-mer Spectra -Version: 2.1.1 +Version: 2.2.0 Author: Hannes Becher -Maintainer: The package maintainer -Description: This package contains a shiny app for fitting population parameters to k-mer spectra. +Maintainer: Hannes Becher +Description: A shiny app for fitting population parameters to k-mer spectra generated from whole-genome DNA sequencing data. License: GPL (>= 3) Depends: R (>= 2.10), diff --git a/Tetmer/R/tetmer.R b/Tetmer/R/tetmer.R index c61da50..33a51df 100644 --- a/Tetmer/R/tetmer.R +++ b/Tetmer/R/tetmer.R @@ -181,18 +181,30 @@ tet.server <- function(input, output) { makeUI <- function(){ - fluidPage(titlePanel("Tetmer v2.1.1"), + fluidPage(titlePanel("Tetmer v2.2.0"), "Fitting population paramters to k-mer spectra (by Hannes Becher)", fluidRow( column(8, plotOutput('plot')), column(4, verbatimTextOutput("outText"), - fluidRow(actionButton("saveFit", "Save fit"), - actionButton("saveFitAs", "Save fit as..."), - numericInput("kVal", "k-mer size (only for Drag'n'Drop)", 0), - fileInput("histFile", "Choose or drop spectrum file")) + ) ), + fluidRow( + column(4, + numericInput("kVal", "Specify k-mer size before loading data", .spec@k) + ), + column(4, + fileInput("histFile", "Choose or drop spectrum file") + ), + column(4, + fluidRow( + actionButton("saveFit", "Save fit", icon=icon("save")), + actionButton("saveFitAs", "Save fit as...", icon=icon("save")) + ) + ) + + ), fluidRow( column(3, @@ -294,7 +306,7 @@ makeUI <- function(){ #' #' @examples \dontrun{tetmer(E028)} #' \dontrun{tetmer(E030)} -tetmer <- function(sp){ +tetmer <- function(sp=E028){ #.sp <<- sp .spec <<- prepare.spectrum(sp) #shinyApp(ui = tet.ui, server = tet.server) @@ -337,15 +349,18 @@ setClass("spectrum", slots=list(name="character", data="data.frame", k="numeric" read.spectrum <- function(f, nam="MySpectrum", k=0, + cropAt=1000, ...){ - sp = read.table(f, ...) + sp <- read.table(f, ...) + sp <- sp[sp[,1] <= cropAt,] names(sp) = c("mult", "count") - return(new("spectrum", + spc <- new("spectrum", name=nam, data=sp, k=k ) - ) + return(prepare.spectrum(spc)) + } @@ -473,7 +488,7 @@ plotSpecApp <- function(input, spec){ lwd=c(1, 2, 2, 2), lty=c(0, 1, 2, 1), pch=c(1, NA, NA, NA), - legend=c("Data", "Fit", "Extrapolation", "Contaminations")) + legend=c("Data", "Fit", "Extrap.", "Contam.")) } @@ -714,7 +729,7 @@ pointsContam <- function(input, optimised, spect){ type = 'l', col = 4, lwd=2 ) } - if(input$mod == "se"){ + if(input$mod == "tse"){ points(1:input$axrange[1], spect@data[1:input$axrange[1], 2] - @@ -1131,18 +1146,22 @@ textOut <- function(input, optimised){ prepare.spectrum <- function(spe){ sp <- spe # cut off first row if 0-based spectrum - - if(sp@data[1,1] == 0) { - # print("Cutting off multiplicity zero.") - sp@data <- sp@data[2:nrow(sp@data),] - } - # add lines if spectrum starts with multiplicity > 1 - offs = sp@data[1,1] - 1 - if(offs > 0){ - # print("Padding with zeros to fill in lower multiplicities.") - prepDF = data.frame(mult=1:offs, count=rep(NA_real_, offs)) - sp@data <- rbind(prepDF, sp@data) - } +# +# if(sp@data[1,1] == 0) { +# # print("Cutting off multiplicity zero.") +# sp@data <- sp@data[2:nrow(sp@data),] +# } +# # add lines if spectrum starts with multiplicity > 1 +# offs = sp@data[1,1] - 1 +# if(offs > 0){ +# # print("Padding with zeros to fill in lower multiplicities.") +# prepDF = data.frame(mult=1:offs, count=rep(NA_real_, offs)) +# sp@data <- rbind(prepDF, sp@data) +# } + maxMult <- sp@data[nrow(sp@data), 1] + allMults <- data.frame(mult=1:maxMult) + sp@data <- merge(allMults, sp@data, on="mult", all.x=T) + sp@data[is.na(sp@data[, 2]), 2] <- 0 return(sp) } @@ -1374,7 +1393,7 @@ allowSegTet <- function(){ } #' @export -makeExpectedSpectrum <- function(params, modelType, nam="", k=0){ +makeExpectedSpectrum <- function(params, modelType, nam="", k=0){ # needs work! input <- params input$mod <- modelType probs <<- getProbs(input) diff --git a/Tetmer/data-raw/save_spectra.R b/Tetmer/data-raw/save_spectra.R index e2cc4d1..b5473f3 100644 --- a/Tetmer/data-raw/save_spectra.R +++ b/Tetmer/data-raw/save_spectra.R @@ -1,5 +1,5 @@ library(usethis) -E030 <- read.spectrum("~/Dropbox/manuscripts/2108_kmers_gs/data/analyseSpectra/spectra/E030full.hist.no0", "E. anglica, E030", 21) +E030 <- 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