tests/testthat/test.mktest.r

In surh/HMVAR: Human Microbiome Variant Analysis in R

# (C) Copyright 2019 Sur Herrera Paredes
# 
# This file is part of HMVAR.
# 
# HMVAR is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# 
# HMVAR is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
# 
# You should have received a copy of the GNU General Public License
# along with HMVAR.  If not, see <http://www.gnu.org/licenses/>.

context("MK tests")
library(HMVAR)

test_that("SNP distribution (no-missing)",{
  # Set up data
  m <- dplyr::tibble(sample = letters[1:6],
                     Group = rep(LETTERS[1:2], each = 3))
  i <- dplyr::tibble(site_id = 's1')
  d <- dplyr::tibble(site_id = i$site_id,
                     a = 1, b = 1, c = 1 ,
                     d = 1, e = 1, f = 1)
  
  # Fixed
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0, b = 0, c = 0,
                     d = 1, e = 1, f = 1)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor("Fixed", levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0),
                   e,
                   info = "Perfect fixed")
  
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 1, b = 0, c = 0,
                     d = 1, e = 1, f = 0)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor("Polymorphic", levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0),
                   e,
                   info = "Perfect polymorphic")
  
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0, b = 0, c = 0,
                     d = 0, e = 0, f = 0)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor("Invariant", levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0),
                   e,
                   info = "Perfect invariant")
  
  
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 1),
                   determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0),
                   info = "Compare freq_thres & (1 - freq_thres)")
})

test_that("SNP distributions (missing data)",{
  # Set up data
  m <- dplyr::tibble(sample = letters[1:6],
                     Group = rep(LETTERS[1:2], each = 3))
  i <- dplyr::tibble(site_id = 's1')
  
  d <- dplyr::tibble(site_id = i$site_id,
                     a = 0, b = 0, c = 1 ,
                     d = 1, e = 1, f = 0)
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0, b = 0, c = 0,
                     d = 1, e = 1, f = 1)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor(NA, levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0,
                                      clean = FALSE),
                   e,
                   info = "Not enough samples in 1 group")
  
  d <- dplyr::tibble(site_id = i$site_id,
                     a = 0, b = 0, c = 1 ,
                     d = 1, e = 0, f = 0)
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0, b = 0, c = 0,
                     d = 1, e = 1, f = 1)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor(NA, levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0,
                                      clean = FALSE),
                   e,
                   info = "Not enough samples in either group")
  
  
  d <- dplyr::tibble(site_id = i$site_id,
                     a = 1, b = 1, c = 1 ,
                     d = 1, e = 1, f = 1)
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0.5, b = 0.5, c = 0,
                     d = 1, e = 1, f = 1)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor(NA, levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0,
                                      clean = FALSE),
                   e,
                   info = "Not enough samples with non 0.5 MAF in one group")
  
  d <- dplyr::tibble(site_id = i$site_id,
                     a = 1, b = 1, c = 1 ,
                     d = 1, e = 1, f = 1)
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0.2, b = 0.2, c = 0,
                     d = 1, e = 1, f = 1)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor(NA, levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0,
                                      clean = FALSE),
                   e,
                   info = "Not enough samples with valid MAF in one group")
  
  d <- dplyr::tibble(site_id = i$site_id,
                     a = 1, b = 0, c = 1 ,
                     d = 1, e = 1, f = 1)
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0.2, b = 0, c = 0,
                     d = 1, e = 1, f = 1)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor(NA, levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0,
                                      clean = FALSE),
                   e,
                   info = "Combination missing valid MAF and depth")
})

test_that("SNP distributions (fractional)",{
  m <- dplyr::tibble(sample = letters[1:6],
                     Group = rep(LETTERS[1:2], each = 3))
  i <- dplyr::tibble(site_id = 's1')
  d <- dplyr::tibble(site_id = i$site_id,
                     a = 1, b = 1, c = 1 ,
                     d = 1, e = 1, f = 1)
  
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0.1, b = 0.2, c = 0.3,
                     d = 0.9, e = 0.8, f = .7)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor("Fixed", levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0.3),
                   e,
                   info = "Fractional fixed")
  
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0.1, b = 0.7, c = 0.3,
                     d = 0.9, e = 0.8, f = .7)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor("Polymorphic", levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0.3),
                   e,
                   info = "Fractional plymorphic")
  
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0.8, b = 0.7, c = 0.4,
                     d = 0.9, e = 0.8, f = .7)
  e <- dplyr::tibble(site_id = i$site_id,
                     distribution = factor("Invariant", levels = c("Fixed", "Invariant", "Polymorphic")))
  expect_identical(determine_snp_dist(info = i,
                                      freq = f,
                                      depth = d,
                                      map = m,
                                      depth_thres = 1,
                                      freq_thres = 0.3),
                   e,
                   info = "Fractional invariant")
})

test_that("SNP distribution errors",{
  # Set up data
  m <- dplyr::tibble(sample = letters[1:6],
                     Group = rep(LETTERS[1:2], each = 3))
  i <- dplyr::tibble(site_id = 's1')
  d <- dplyr::tibble(site_id = i$site_id,
                     a = 1, b = 1, c = 1 ,
                     d = 1, e = 1, f = 0)
  f <- dplyr::tibble(site_id = i$site_id,
                     a = 0, b = 0, c = 0,
                     d = 1, e = 1, f = 1)
  expect_error(determine_snp_dist(info = i,
                                  freq = f,
                                  depth = d,
                                  map = m,
                                  depth_thres = 1,
                                  freq_thres = 2),
               info = "MAF threshold out of range")
})

test_that("SNP effects",{
  # Prepare data
  i <- dplyr::tibble(site_id = 's1', major_allele = 'A', minor_allele = 'C', amino_acids = 'A,A,A,A')
  e <- dplyr::tibble(site_id = 's1', major_allele = 'A', minor_allele = 'C', amino_acids = 'A,A,A,A',
                     snp_effect = factor('synonymous', levels = c("synonymous", "non-synonymous")))
  expect_identical(determine_snp_effect(info = i), e,
                   info = "All synonymous")
  
  i <- dplyr::tibble(site_id = 's1', major_allele = 'A', minor_allele = 'C', amino_acids = 'A,R,A,R')
  e <- dplyr::tibble(site_id = 's1', major_allele = 'A', minor_allele = 'C', amino_acids = 'A,R,A,R',
                     snp_effect = factor('non-synonymous', levels = c("synonymous", "non-synonymous")))
  expect_identical(determine_snp_effect(info = i), e,
                   info = "non- synonymous")
  
  i <- dplyr::tibble(site_id = 's1', major_allele = 'A', minor_allele = 'G', amino_acids = 'A,R,A,R')
  e <- dplyr::tibble(site_id = 's1', major_allele = 'A', minor_allele = 'G', amino_acids = 'A,R,A,R',
                     snp_effect = factor('synonymous', levels = c("synonymous", "non-synonymous")))
  expect_identical(determine_snp_effect(info = i), e,
                   info = "synonymous")
  
  i <- dplyr::tibble(site_id = 's1', major_allele = 'A', minor_allele = 'T', amino_acids = 'A,R,A,R')
  e <- dplyr::tibble(site_id = 's1', major_allele = 'A', minor_allele = 'T', amino_acids = 'A,R,A,R',
                     snp_effect = factor('non-synonymous', levels = c("synonymous", "non-synonymous")))
  expect_identical(determine_snp_effect(info = i), e,
                   info = "non- synonymous")
})

test_that("MK table", {
  # Prepare data
  i <- dplyr::tibble(distribution = factor(c("Fixed", "Fixed", "Fixed"),
                                           levels = c("Fixed", "Invariant", "Polymorphic")),
                     snp_effect = factor(c('synonymous', "synonymous", "synonymous"),
                                         levels = c("synonymous", "non-synonymous")))
  e <- dplyr::tibble(Dn = as.integer(0), Ds = as.integer(3), Pn = as.integer(0), Ps = as.integer(0))
  expect_identical(mkvalues(i), e,
                   info = "Count one present")
  
  i <- dplyr::tibble(distribution = factor(c("Fixed", "Fixed", "Fixed"),
                                           levels = c("Fixed", "Invariant", "Polymorphic")),
                     snp_effect = factor(c('synonymous', NA, "synonymous"),
                                         levels = c("synonymous", "non-synonymous")))
  e <- dplyr::tibble(Dn = as.integer(0), Ds = as.integer(2), Pn = as.integer(0), Ps = as.integer(0))
  expect_identical(mkvalues(i), e,
                   info = "Count one missing")
  
  i <- dplyr::tibble(distribution = factor(c(NA, "Fixed", NA),
                                           levels = c("Fixed", "Invariant", "Polymorphic")),
                     snp_effect = factor(c('synonymous', NA, "synonymous"),
                                         levels = c("synonymous", "non-synonymous")))
  e <- dplyr::tibble(Dn = as.integer(0), Ds = as.integer(0), Pn = as.integer(0), Ps = as.integer(0))
  expect_identical(mkvalues(i), e,
                   info = "Count all missing")
  
  i <- dplyr::tibble(snp_distribution = factor(c("Fixed", "Fixed", "Fixed"),
                                               levels = c("Fixed", "Invariant", "Polymorphic")),
                     snp_effect = factor(c('synonymous', "synonymous", "synonymous"),
                                         levels = c("synonymous", "non-synonymous")))
  expect_error(mkvalues(i), info = "Missing column")
})