Parameters

# Load packages in order of increasing importance
library(magrittr)
library(data.table)
library(matrixStats)
library(biomaRt)
library(NMF)
library(DESeq2)
library(maftools)
library(forcats)
library(tidyverse)

paths <- list()

# Metadata
paths$patient_md      <- project("data/metadata/patient_metadata.tsv")
paths$patient_icgc_md <- project("data/metadata/patient_metadata.icgc.tsv")
paths$genome_md       <- project("data/metadata/genome_metadata.bams.tsv")
paths$genome_icgc_md  <- project("data/metadata/genome_metadata.icgc.tsv")
paths$mrna_md         <- project("data/metadata/mrna_metadata.bams.tsv")
paths$mirna_md        <- project("data/metadata/mirna_metadata.bams.tsv")
paths$tn              <- project("data/metadata/tumour_nuclei_percent.tsv")

# Reference
paths$bl_genes      <- project("etc/bl.genes.txt")
paths$mbl_genes     <- project("etc/mbl_signature.genes.txt")
paths$morgan_genes  <- project("etc/morgan.genes.txt")
paths$wright_genes  <- project("etc/wright.genes.txt")
paths$malaria_genes <- project("etc/malaria.genes.txt")
paths$latency_genes <- project("etc/latency.genes.txt")
paths$seq           <- project("ref/GRCh38/Sequence")
paths$seq_grch37    <- project("ref/GRCh37-lite/Sequence")
paths$annot         <- project("ref/GRCh38/Annotation")
paths$genome        <- file.path(paths$seq, "WholeGenomeFasta/genome.simple_headers.fa")
paths$trans         <- file.path(paths$seq, "GencodeTranscriptome/25")
paths$tx2gene       <- file.path(paths$trans, "gencode_v25_and_NC_007605.tx2gene.tsv")
paths$gaps          <- file.path(paths$annot, "ExcludedRegions/gaps.bed")
paths$genome_grch37 <- file.path(paths$seq_grch37, "WholeGenomeFasta/genome.simple_headers.fa")

# Results
paths$ebv_dna  <- project("results/status/ebv_status.dna.txt")
paths$ebv_rna  <- project("results/status/ebv_status.rna.txt")
paths$sex      <- project("results/status/sex_status.txt")
paths$strelka  <- project("results/strelka/3-tabulate")
paths$tc       <- file.path(paths$strelka, "tumour_content.tsv")
paths$tc_icgc  <- file.path(paths$strelka, "icgc.tumour_content.tsv")
paths$maf      <- file.path(paths$strelka, "strelka.noncanonical.qss_filt.vaf_filt.aug.maf")
paths$maf_all  <- file.path(paths$strelka, "all.strelka.canonical.qss_filt.aug.maf")
paths$mmaf     <- project("results/smgs/data/BL_META.grch37.maf")
paths$smgs     <- project("results/smgs/results/meta_analysis/BL_META.genes.txt")
paths$sequenza <- project("results/sequenza/2-sequenza/force_tc")
paths$gistic   <- project("results/gistic")
paths$manta    <- project("results/manta/1-manta/*/results/variants/somaticSV.vcf.gz")
paths$salmon   <- project("results/salmon")
paths$mirna    <- project("results/gsc_mirna/mirna_expression.tsv")

# Set RNG seed for reproducibility
rng_seed <- 87510475  # Generated by runif(1, 0, 10^8)
set.seed(rng_seed)

# Use all available cores when multithreading
num_cores <- parallel::detectCores()
doMC::registerDoMC(cores = num_cores)
BiocParallel::register(BiocParallel::MulticoreParam(workers = num_cores))

# Effective genome size
genome_size <- 2934876451

# Number of most variably expressed genes
ntop <- 1000

# Other options
options(scipen=10)