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run.r
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run.r
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library(Biostrings)
library(iimi)
library(mltools)
library(data.table)
library(dplyr)
library(randomForest)
library(Rsamtools)
library(GenomicAlignments)
args <- commandArgs(trailingOnly=TRUE)
bam_path <- args[1]
mappability_profile_path <- args[2]
model_path <- args[3]
nucleotide_info_path <- args[4]
output_path <- args[5]
mappability_profile <- readRDS(mappability_profile_path)
model <- readRDS(model_path)
nucleotide_info <- read.csv(nucleotide_info_path, sep="\t", header=TRUE)
# Convert BAM file.
data <- convert_bam_to_cov(
bam_file = bam_path,
mappability_profile = mappability_profile,
nucleotide_info = nucleotide_info
)
newdata <- data$ML_df
par(mar = c(1,2,1,1))
layout(matrix(c(1,1,2,5,5,6,3,3,4,7,7,8), nrow = 6))
# Run Model
prediction_virus <- predict_iimi(
newdata = newdata,
method = "rf",
trained_model = trained_rf,
report_result_level = 2
)
prediction_isolate <- predict_iimi(
newdata = newdata,
method = "rf",
trained_model = trained_rf,
report_result_level = 1
)
write.csv(prediction_virus, file.path(output_path, "prediction_virus.csv"), row.names = FALSE)
write.csv(prediction_isolate, file.path(output_path, "prediction_sequence.csv"), row.names = FALSE)
write_coverage <- function(cov, path) {
cov_table <- data.frame(matrix(ncol=3, nrow=0))
colnames(cov_table) <- c(
"sequence_id",
"lengths",
"values"
)
for (sequence_id in names(cov)) {
lengths <- cov[[sequence_id]]@lengths
values <- cov[[sequence_id]]@values
cs_lengths <- paste(lengths, collapse = ",")
cs_values <- paste(values, collapse = ",")
new_row <- list(
sequence_id=sequence_id,
lengths = cs_lengths,
values=cs_values
)
cov_table <- rbind(cov_table, new_row)
}
write.csv(cov_table, path, row.names = FALSE)
}
write_untrustworthy <- function(mappability_profile, path) {
unt_table <- data.frame(matrix(ncol=2, nrow=0))
colnames(unt_table) <- c(
"sequence_id",
"ranges"
)
for (sequence_id in names(mappability_profile)) {
number_list <- mappability_profile[[sequence_id]]
if (length(number_list) > 0) {
breaks <- which(diff(number_list) > 1)
# Create the pairs
pairs <- matrix(nrow = length(breaks) + 1, ncol = 2)
# Fill in the start and end points of each range
pairs[, 1] <- c(number_list[1], number_list[breaks + 1])
pairs[, 2] <- c(number_list[breaks], number_list[length(number_list)])
# Convert to a list of coordinate pairs
coordinate_pairs <- split(pairs, row(pairs))
formatted_pairs <- vector("character", length(coordinate_pairs))
# Iterate over the coordinate pairs and format them
for (i in seq_along(coordinate_pairs)) {
pair <- coordinate_pairs[[i]]
formatted_pairs[i] <- paste(pair[1], pair[2], sep = "-")
}
# Combine all formatted pairs into a single string, separated by commas
stringified <- paste(formatted_pairs, collapse = ",")
unt_table <- rbind(unt_table, list(sequence_id, stringified))
} else {
unt_table <- rbind(unt_table, list(sequence_id, ""))
}
}
colnames(unt_table) <- c(
"sequence_id",
"ranges"
)
write.csv(unt_table, path, row.names = FALSE)
}
unfiltered_coverage <- coverage(readGAlignments(BamFile(bam_path)))
write_coverage(unfiltered_coverage, file.path(output_path, "coverage.csv"))
write_untrustworthy(mappability_profile, file.path(output_path,"untrustworthy.csv"))