Merge fixes

kgori · Jun 1, 2021 · 7e4f593 · 7e4f593
1 parent 42851d1
commit 7e4f593
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Showing 5 changed files with 1 addition and 238 deletions.
diff --git a/R/sigfit_utility.R b/R/sigfit_utility.R
@@ -28,13 +28,6 @@ build_opps_matrix <- function(nsamples, ncat, opps) {
             opps <- matrix(rep(human_trinuc_freqs(opps, strand), nsamples),
                            nrow = nsamples, byrow = TRUE)
         }
-<<<<<<< HEAD
-        else {
-            opps <- as.matrix(opps)
-        }
-        # Normalise to sum to nsamples (to avoid very large/small values)
-        opps / sum(opps) * nsamples
-=======
         else if (is.numeric(opps) & length(opps) == ncat) {
             opps <- matrix(rep(opps, nsamples), nrow = nsamples, byrow = TRUE)
         }
@@ -45,7 +38,6 @@ build_opps_matrix <- function(nsamples, ncat, opps) {
         #opps / sum(opps) * nsamples
         # Normalise each row to sum to 1
         opps / rowSums(opps)
->>>>>>> dev
     }
 }
 
@@ -482,23 +474,12 @@ build_catalogues <- function(variants) {
 #' @param signatures Either a numeric matrix of mutational signatures, with one row per signature
 #' and one column per mutation type, or a list of matrices generated via \code{\link{retrieve_pars}}.
 #' @param opportunities_from Mutational opportunities that are currently imposed on the signatures.
-<<<<<<< HEAD
-#' This can be a numeric matrix of mutational opportunities, with one row per signature and
-#' one column per mutation type (if the signatures were inferred together, then every row should
-#' contain the same opportunities). Character values \code{"human-genome"} or \code{"human-exome"}
-#' are also admitted, in which case the mutational opportunities of the reference human
-#' genome/exome will be used for every signature. If this argument is provided, the signatures will
-#' be normalised (divided) by the opportunities. Otherwise (if \code{opportunities_from = NULL}),
-#' the signatures will be interpreted as being already normalised (i.e. not relative to any
-#' opportunities).
-=======
 #' This can be a numeric vector of mutational opportunities, with one element per mutation type.
 #' Character values \code{"human-genome"} or \code{"human-exome"} are also admitted, in which case
 #' the mutational opportunities of the reference human genome/exome will be used.
 #' If this argument is provided, the signatures will be normalised (divided) by the opportunities.
 #' Otherwise (if \code{opportunities_from = NULL}), the signatures will be interpreted as being
 #' already normalised (i.e. not relative to any opportunities).
->>>>>>> dev
 #' @param opportunities_to Mutational opportunities that are to be imposed on the signatures.
 #' Admits the same values as \code{opportunities_from}. If this argument is provided, the
 #' signatures will be multiplied by the opportunities. Otherwise (if \code{opportunities_to = NULL}),
@@ -536,14 +517,6 @@ convert_signatures <- function(signatures, opportunities_from = NULL, opportunit
         stop("Either 'opportunities_from' or 'opportunities_to' must be provided.")
     }
     signatures <- to_matrix(signatures)
-<<<<<<< HEAD
-    opportunities_from <- build_opps_matrix(nrow(signatures), ncol(signatures), opportunities_from)
-    opportunities_to <- build_opps_matrix(nrow(signatures), ncol(signatures), opportunities_to)
-
-    conv_sigs <- signatures
-    for (i in 1:nrow(conv_sigs)) {
-        conv_sigs[i, ] <- conv_sigs[i, ] / opportunities_from[i, ] * opportunities_to[i, ]
-=======
     opportunities_from <- build_opps_matrix(1, ncol(signatures), opportunities_from)
     opportunities_to <- build_opps_matrix(1, ncol(signatures), opportunities_to)
     if (nrow(opportunities_from) > 1)
@@ -554,7 +527,6 @@ convert_signatures <- function(signatures, opportunities_from = NULL, opportunit
     conv_sigs <- signatures
     for (i in 1:nrow(conv_sigs)) {
         conv_sigs[i, ] <- conv_sigs[i, ] / opportunities_from * opportunities_to
->>>>>>> dev
         conv_sigs[i, ] <- conv_sigs[i, ] / sum(conv_sigs[i, ])
     }
     conv_sigs

diff --git a/README.md b/README.md
@@ -29,8 +29,6 @@ sigfit is an R package. As it is in early development it is not yet on CRAN, but
 
     devtools::install_github("kgori/sigfit", build_vignettes = TRUE,
                              build_opts = c("--no-resave-data", "--no-manual"))
-<<<<<<< HEAD
-=======
 
 The arguments `build_vignettes` and `build_opts` are necessary for the package vignette to be built.
 
@@ -41,7 +39,6 @@ For solutions to some of the problems that may arise during installation, see th
 Problem:
 
     Error: 'rstan_config' is not an exported object from 'namespace:rstantools'
->>>>>>> dev
 
 The arguments `build_vignettes` and `build_opts` are necessary for the package vignette to be built.
 

diff --git a/doc/sigfit_vignette.R b/doc/sigfit_vignette.R
@@ -1,22 +1,8 @@
-<<<<<<< HEAD
-## ----setup, include=FALSE------------------------------------------------
-=======
 ## ----setup, include=FALSE-----------------------------------------------------
->>>>>>> dev
 knitr::opts_chunk$set(echo = TRUE)
 suppressPackageStartupMessages(library(sigfit))
 par(mar = c(6, 4, 6, 4))
 
-<<<<<<< HEAD
-## ----devtools_instructions, eval=FALSE-----------------------------------
-#  devtools::install_github("kgori/sigfit", build_opts = c("--no-resave-data", "--no-manual"))
-
-## ----fetch---------------------------------------------------------------
-library(sigfit)
-data("cosmic_signatures_v2")
-
-## ----sim-----------------------------------------------------------------
-=======
 ## ----devtools_instructions, eval=FALSE----------------------------------------
 #  devtools::install_github("kgori/sigfit", build_opts = c("--no-resave-data", "--no-manual"))
 
@@ -25,37 +11,24 @@ library(sigfit)
 data("cosmic_signatures_v2")
 
 ## ----sim----------------------------------------------------------------------
->>>>>>> dev
 set.seed(1)
 probs <- c(0.4, 0.3, 0.2, 0.1) %*% as.matrix(cosmic_signatures_v2[c(1, 3, 7, 11), ])
 mutations <- matrix(rmultinom(1, 20000, probs), nrow = 1)
 colnames(mutations) <- colnames(cosmic_signatures_v2)
 
-<<<<<<< HEAD
-## ----plotsim, fig.width=20, fig.height=7, out.width="100%", echo=-1------
-par(mar = c(4.5,5.5,6.5,1))
-plot_spectrum(mutations, name = "Simulated counts")
-
-## ----fitting, warning=FALSE----------------------------------------------
-=======
 ## ----plotsim, fig.width=20, fig.height=7, out.width="100%", echo=-1-----------
 par(mar = c(4.5,5.5,6.5,1))
 plot_spectrum(mutations, name = "Simulated counts")
 
 ## ----fitting, warning=FALSE---------------------------------------------------
->>>>>>> dev
 mcmc_samples_fit <- fit_signatures(counts = mutations, 
                                    signatures = cosmic_signatures_v2,
                                    iter = 2000, 
                                    warmup = 1000, 
                                    chains = 1, 
                                    seed = 1756)
 
-<<<<<<< HEAD
-## ----retrieve_exp--------------------------------------------------------
-=======
 ## ----retrieve_exp-------------------------------------------------------------
->>>>>>> dev
 exposures <- retrieve_pars(mcmc_samples_fit, 
                            par = "exposures", 
                            hpd_prob = 0.90)
@@ -66,11 +39,7 @@ exposures$mean
 par(mar=c(8,5,3.5,0))
 plot_exposures(mcmc_samples = mcmc_samples_fit)
 
-<<<<<<< HEAD
-## ----refitting, eval=FALSE-----------------------------------------------
-=======
 ## ----refitting, eval=FALSE----------------------------------------------------
->>>>>>> dev
 #  selected_signatures <- c(1, 3, 7, 11)
 #  mcmc_samples_fit_2 <- fit_signatures(mutations,
 #                                       cosmic_signatures_v2[selected_signatures, ],
@@ -83,35 +52,20 @@ plot_exposures(mcmc_samples = mcmc_samples_fit)
 par(mar=c(5,6,6.5,1))
 plot_reconstruction(mcmc_samples = mcmc_samples_fit)
 
-<<<<<<< HEAD
-## ----plot_all, eval=FALSE------------------------------------------------
-=======
 ## ----plot_all, eval=FALSE-----------------------------------------------------
->>>>>>> dev
 #  plot_all(mcmc_samples = mcmc_samples_fit,
 #           out_path = "your/output/dir/here",
 #           prefix = "Fitting")
 
-<<<<<<< HEAD
-## ----load_mutations------------------------------------------------------
-=======
 ## ----load_mutations-----------------------------------------------------------
->>>>>>> dev
 library(sigfit)
 data("variants_21breast")
 head(variants_21breast)
 
-<<<<<<< HEAD
-## ----show_samples--------------------------------------------------------
-unique(variants_21breast[, 1])
-
-## ----build_catalogues----------------------------------------------------
-=======
 ## ----show_samples-------------------------------------------------------------
 unique(variants_21breast[, 1])
 
 ## ----build_catalogues---------------------------------------------------------
->>>>>>> dev
 counts_21breast <- build_catalogues(variants_21breast)
 dim(counts_21breast)
 counts_21breast[1:5, 1:8]
@@ -121,19 +75,12 @@ par(mar = c(5,6,7,2))
 par(mfrow = c(7, 3))
 plot_spectrum(counts_21breast)
 
-<<<<<<< HEAD
-## ----extraction, eval=FALSE----------------------------------------------
-=======
 ## ----extraction, eval=FALSE---------------------------------------------------
->>>>>>> dev
 #  mcmc_samples_extr <- extract_signatures(counts = counts_21breast,
 #                                          nsignatures = 2:7,
 #                                          iter = 1000,
 #                                          seed = 1756)
-<<<<<<< HEAD
-=======
 #  plot_gof(mcmc_samples_extr)
->>>>>>> dev
 
 ## ----plot_gof_silent, echo=FALSE, fig.width=9, fig.height=6, out.width="100%"----
 ## Plot precalculated GOF in order to avoid running the model
@@ -145,16 +92,6 @@ plot(nS, gof, type = "o", lty = 3, pch = 16, col = "dodgerblue4",
 points(nS[best], gof[best], pch = 16, col = "orangered", cex = 1.1)
 cat("Estimated best number of signatures:", nS[best], "\n")
 
-<<<<<<< HEAD
-## ----extr_names, eval=FALSE----------------------------------------------
-#  names(mcmc_samples_extr)
-
-## ----extr_names_silent, echo=FALSE---------------------------------------
-print(c("nsignatures=1", "nsignatures=2", "nsignatures=3", "nsignatures=4", "nsignatures=5", "nsignatures=6", "nsignatures=7", "best"))
-signatures <- extr_signatures
-
-## ----retrieve_sigs, eval=FALSE-------------------------------------------
-=======
 ## ----extr_names, eval=FALSE---------------------------------------------------
 #  names(mcmc_samples_extr)
 
@@ -163,68 +100,43 @@ print(c("nsignatures=1", "nsignatures=2", "nsignatures=3", "nsignatures=4", "nsi
 signatures <- extr_signatures
 
 ## ----retrieve_sigs, eval=FALSE------------------------------------------------
->>>>>>> dev
 #  ## Note: mcmc_samples_extr[[N]] contains the extraction results for N signatures
 #  signatures <- retrieve_pars(mcmc_samples_extr[[4]],
 #                              par = "signatures")
 
-<<<<<<< HEAD
-## ----show_signames-------------------------------------------------------
-=======
 ## ----show_signames------------------------------------------------------------
->>>>>>> dev
 rownames(signatures$mean)
 
 ## ----plot_sigs, warning=FALSE, fig.width=25, fig.height=10, out.width='100%', fig.align="center", echo=-1----
 par(mar = c(6,7,6,1))
 par(mfrow = c(2, 2))
 plot_spectrum(signatures)
 
-<<<<<<< HEAD
-## ----match_sigs----------------------------------------------------------
-data("cosmic_signatures_v2")
-match_signatures(signatures, cosmic_signatures_v2)
-
-## ----refitting2, eval=FALSE----------------------------------------------
-=======
 ## ----match_sigs---------------------------------------------------------------
 data("cosmic_signatures_v2")
 match_signatures(signatures, cosmic_signatures_v2)
 
 ## ----refitting2, eval=FALSE---------------------------------------------------
->>>>>>> dev
 #  signatures <- retrieve_pars(mcmc_samples_extr_2, "signatures")
 #  mcmc_samples_refit <- fit_signatures(counts = counts_21breast,
 #                                       signatures = signatures,
 #                                       iter = 2000,
 #                                       warmup = 1000)
 #  exposures <- retrieve_pars(mcmc_samples_refit, "exposures")
 
-<<<<<<< HEAD
-## ----strandwise, fig.width=22, fig.height=7, out.width="100%", echo=-1----
-=======
 ## ----strandwise, fig.width=22, fig.height=7, out.width="100%", echo=-1--------
->>>>>>> dev
 par(mar = c(4.5,5.5,6.5,1))
 # Load and plot a strand-wise catalogue
 data("counts_88liver_strand")
 plot_spectrum(counts_88liver_strand[1, ], name = rownames(counts_88liver_strand)[1])
 
-<<<<<<< HEAD
-## ----generic, fig.width=22, fig.height=8, out.width="100%", echo=-1------
-=======
 ## ----generic, fig.width=22, fig.height=8, out.width="100%", echo=-1-----------
->>>>>>> dev
 par(mar = c(6.5,5.5,6.5,1)); set.seed(0xC0FFEE)
 # Create and plot an arbitrary catalogue
 counts <- as.numeric(rmultinom(1, 5000, runif(100)))
 plot_spectrum(counts, name = "Arbitrary catalogue")
 
-<<<<<<< HEAD
-## ----convert_sigs, eval=F------------------------------------------------
-=======
 ## ----convert_sigs, eval=F-----------------------------------------------------
->>>>>>> dev
 #  # (Following from the signature extraction example presented above)
 #  # Retrieve genome-derived signatures
 #  genome_signatures <- retrieve_pars(mcmc_samples_extr[[4]],
@@ -247,11 +159,7 @@ par(mfrow = c(2, 1), mar = c(5,5.5,6.5,1))
 plot_spectrum(signatures$mean[4,], name="Signature D, Genome-relative probabilities")
 plot_spectrum(exome_signatures[4,], name="Signature D, Exome-relative probabilities")
 
-<<<<<<< HEAD
-## ----multichain, eval=F--------------------------------------------------
-=======
 ## ----multichain, eval=F-------------------------------------------------------
->>>>>>> dev
 #  # Load mutation counts
 #  data("counts_21breast")
 #  
@@ -276,18 +184,6 @@ plot_spectrum(exome_signatures[4,], name="Signature D, Exome-relative probabilit
 #                                       chains = ncores,
 #                                       init = inits)
 
-<<<<<<< HEAD
-## ------------------------------------------------------------------------
-    data("cosmic_signatures_v2")
-    data("cosmic_signatures_v3")
-    data("cosmic_signatures_v3_strand")
-
-## ------------------------------------------------------------------------
-    data("variants_21breast")
-    data("counts_21breast")
-
-## ------------------------------------------------------------------------
-=======
 ## -----------------------------------------------------------------------------
     data("cosmic_signatures_v2")
     data("cosmic_signatures_v3")
@@ -299,27 +195,18 @@ plot_spectrum(exome_signatures[4,], name="Signature D, Exome-relative probabilit
     data("counts_21breast")
 
 ## -----------------------------------------------------------------------------
->>>>>>> dev
     data("variants_119breast")
     data("variants_119breast_strand")
     data("counts_119breast")
     data("counts_119breast_strand")
 
-<<<<<<< HEAD
-## ------------------------------------------------------------------------
-=======
 ## -----------------------------------------------------------------------------
->>>>>>> dev
     data("variants_88liver")
     data("variants_88liver_strand")
     data("counts_88liver")
     data("counts_88liver_strand")
 
-<<<<<<< HEAD
-## ------------------------------------------------------------------------
-=======
 ## -----------------------------------------------------------------------------
->>>>>>> dev
     data("methylation_50breast")
     data("methylation_27normal")