Adapted greedyMix examples (closes #15)

This commit is contained in:
Waldir Leoncio 2021-09-03 09:10:21 +02:00
parent 12edd330b9
commit 682555f8e3
2 changed files with 38 additions and 15 deletions

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@ -0,0 +1,20 @@
>1
AACGAAACGATCGCGTCACCGGAACGTTGTCCGTCTCGAATAGCACTGTGGGAACGTGTTTTACATTCGT
TAGTAACATGGTCAGCTGCTCATCCGTATT
>2
ATCAGCAAACGAGAAGTTGCAGAGGTCTTTGGTTTGAGCATTGCCCCCATACAATCGACTTCTGGCCTGG
AATGCACCACAAACATACCCCACAGGCTCG
>3
GCTTTTACTAAGGCCTATCGGATTCAACGTCACTAAGACTCGGCACTAACAGGCCGTTGTAAGCCGCTCT
GTCTGAGTATGGATGGTGGAGGCGGAGCCG
>4
ACCTGGACCTCTGTATTAACGGCTGTGATTCTGAGGGGGGTATCGCAGCGCACTTTCTAGCTATATCACG
CAAGGATAAAGTTCACCCATCACGTTGACC
>5
ACAATACGTCATCCACACCGCGCCTATGGAAGAATTTGCCCTTTCGGCGACAGCCCATGCTGTCAAGGAG
GTAACATAGCTACCAGGTCCCATTCCAGGA

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@ -1,15 +1,15 @@
context("Auxiliary functions to greedyMix") context("Auxiliary functions to greedyMix")
# Defining the relative path to current inst ------------- # # Defining the relative path to current inst -----------------------------------
if (interactive()) { if (interactive()) {
path_inst <- "../../inst/ext/BAPS_format_clustering_diploid.txt" path_inst <- "../../inst/ext"
} else { } else {
path_inst <- system.file( path_inst <- system.file("ext", "", package="rBAPS")
"ext", "BAPS_format_clustering_diploid.txt", package="rBAPS"
)
} }
# Reading datasets -------------------------------------------------------------
baps_diploid <- read.delim( baps_diploid <- read.delim(
file = path_inst, file = paste(path_inst, "BAPS_format_clustering_diploid.txt", sep="/"),
sep = " ", sep = " ",
header = FALSE header = FALSE
) )
@ -35,15 +35,18 @@ test_that("handleData works as expected", {
expect_equal(data_obs, data_exp) expect_equal(data_obs, data_exp)
}) })
context("Opening files on greedyMix/load_fasta") context("Opening files on greedyMix")
# # TODO: needs #12 to be fixed before this can be done without user intervention df_fasta <- greedyMix(
# greedyMix( data = paste(path_inst, "FASTA_clustering_haploid.fasta", sep="/"),
# tietue = "inst/ext/ExamplesDataFormatting/Example data in BAPS format for clustering of diploid individuals.txt", format ="fasta"
# format = "BAPS", )
# savePreProcessed = FALSE # TODO: add example reading VCF
# ) # Upper bounds 100 100 # TODO: add example reading SAM
# TODO #16: replace with load_fasta() # TODO: add example reading Genpop
test_that("Files are imported correctly", {
expect_equal(dim(df_fasta), c(5, 99))
})
context("Linkage") context("Linkage")