## Simulated data to test PhIPData functions
set.seed(20210106)
## Import library
virscan_file <- system.file("extdata", "virscan.tsv", package = "PhIPData")
virscan_info <- readr::read_tsv(virscan_file,
col_types = readr::cols(
pep_id = readr::col_character(),
pep_dna = readr::col_character(),
pep_aa = readr::col_character(),
pep_pos = readr::col_character(),
pro_len = readr::col_double(),
uniprot_acc = readr::col_character(),
refseq = readr::col_character(),
species = readr::col_character(),
interspecies_specific = readr::col_character(),
product = readr::col_character(),
description = readr::col_character(),
go = readr::col_character(),
kegg = readr::col_character(),
pfam = readr::col_character(),
embl = readr::col_character(),
interpro = readr::col_character(),
pep_name = readr::col_character()
)
) %>%
as.data.frame()
n_samples <- 96L
n_peptides <- nrow(virscan_info)
## Generate data
counts <- matrix(sample(1:1e6, n_samples * n_peptides, replace = TRUE),
nrow = n_peptides
)
logfc <- matrix(rnorm(n_samples * n_peptides, mean = 0, sd = 10),
nrow = n_peptides
)
prob <- matrix(rbeta(n_samples * n_peptides, shape1 = 1, shape2 = 1),
nrow = n_peptides
)
sampleInfo <- S4Vectors::DataFrame(
sample_name = paste0("sample", 1:n_samples),
gender = sample(c("M", "F"), n_samples,
replace = TRUE
),
group = sample(c("beads", "ART", "no ART"),
n_samples,
replace = TRUE
)
)
## Set names
rownames(counts) <- rownames(logfc) <-
rownames(prob) <- rownames(virscan_info) <-
paste0("pep_", 1:n_peptides)
colnames(counts) <- colnames(logfc) <-
colnames(prob) <- rownames(sampleInfo) <-
paste0("sample_", 1:n_samples)
## default object
phip_obj <- PhIPData(
counts = counts, logfc = logfc, prob = prob,
sampleInfo = sampleInfo, peptideInfo = virscan_info
)
withr::defer(
unlink(system.file(package = "PhIPData", "extdata/defaults.rda")),
teardown_env()
)
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