context("PAC preprocessing and summary\n")
library(seqpac)
invisible(capture.output(
test_that("Testing PAC_filter and PAC_filtsep ...", {
load(system.file("extdata", "drosophila_sRNA_pac_filt_anno.Rdata",
package = "seqpac", mustWork = TRUE))
pac_lowfilt <- PAC_filter(pac, size=c(15,80), threshold=5,
coverage=20, norm = "counts",
pheno_target=NULL, anno_target=NULL)
pac_subset <- PAC_filter(pac_lowfilt, subset_only = TRUE,
pheno_target=list("batch", c("Batch1", "Batch2")),
anno_target=list("Size", "22"))
filtsep <- PAC_filtsep(pac_lowfilt, norm="counts", threshold=,
coverage=100, pheno_target= list("stage"),
output="binary")
pac_filt <- PAC_filter(pac_lowfilt, subset_only = TRUE,
anno_target= row.names(filtsep))
expect_true(PAC_check(pac_lowfilt))
expect_true(PAC_check(pac_subset))
expect_true(PAC_check(pac_filt))
})))
invisible(capture.output(
test_that("Testing PAC_norm and PAC_summary ...", {
load(system.file("extdata", "drosophila_sRNA_pac_filt_anno.Rdata",
package = "seqpac", mustWork = TRUE))
pac <- PAC_norm(pac, norm="cpm")
suppressMessages(
pac <- PAC_norm(pac, norm="vst", merge_pac = TRUE)
)
suppressMessages(
pac <- PAC_norm(pac, norm="rlog")
)
df_norm <- PAC_norm(pac, norm="cpm", merge_pac = FALSE)
pac <- PAC_summary(pac, norm="cpm", pheno_target=list("stage"))
pac <- PAC_summary(pac, norm="cpm", pheno_target=list("batch", c("Batch1", "Batch2")))
df_sum <- PAC_summary(pac, norm="cpm", pheno_target=list("batch", c("Batch1", "Batch2")), merge_pac = FALSE)
expect_true(PAC_check(pac))
expect_equal(norm(pac)$cpm, df_norm)
expect_equal(summary(pac)$cpmMeans_batch, df_sum[[1]])
})))
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