jburos / bayesnmf Goto Github PK

Hi there! When I ran the bayesNMF code provided in your directory using a simulated cancer mutational catalog to en, I have encountered the following problem after the 30X optimization has finnished:

Error in plot.activity.barplot(H.mid, H.norm, 1, tumor.type) :
could not find function "melt"
In addition: Warning messages:
1: In this["plot"] <- p :
number of items to replace is not a multiple of replacement length
2: In this["signatures"] = W.norm :
number of items to replace is not a multiple of replacement length
3: In this["signature_mutations"] = H.mid :
number of items to replace is not a multiple of replacement length
4: In this["normalized_mutations"] = H.norm :
number of items to replace is not a multiple of replacement length

My code looks like this:
`

load BayesNMF functions

if (!require(mutsigNMF))
devtools::install_github('jburos/mutsigNMF')
library(mutsigNMF)
library(tidyr)
library(ggplot2)
library(dplyr)
library(rstan)
library(httr)
library(purrr)

input_file <- '/home/e0240162/practice/3_Signature_Challenge/Synthetic_Data/PCAWG-synthetic-tumors/pcawg.j.tumors.1000.no.noise.synthetic.tumors.0.2.txt'

#Read data from input file
dat <- read.table(input_file, sep = "\t", header = T, as.is = T)

#Decide the format of the data, and do respective data conversion
mat <- as.matrix(dat[,-(1:4)])
typeof(mat) #"integer"

#rownames(mat) <- gsub(dat$Mutation.Type, pattern = "[[:punct:]]", replacement = '', fixed = F)

bases <- c("A","C","G","T")
pyrimidines <- c("C","T")

Before <- rep(bases,each = 4,rep = 6)
Ref <- rep(pyrimidines,each = 48)
After <- rep(bases, rep = 24)
Var <- c( rep(c("A","G","T"),each = 16) , rep(c("A","G","C"),each = 16) )

#Input the base context for BayesNMF_Jaegil program
#Under this context, 4 bases: Before Ref Alt After are linked together as the rowname
rownames(mat) <- paste0(Before,Ref,Var,After)
colnames(mat) <- colnames(dat)[-(1:4)]

test bayesNMF method

as described here: https://www.broadinstitute.org/cancer/cga/msp

bayesNMF <- run_bayesNMF(mat = mat,tumor.type = gsub("[.][0-9]$","",colnames(mat)[1]), max_k = 40, n_runs = 30 )
`