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Resolve conflict in a vector of taxonomy values

Source: R/taxonomy.R
resolve_vector_ranks.Rd

lifecycle-experimental

Internally used in the function assign_blastn() with method="vote"

Usage

resolve_vector_ranks(
  vec,
  method = c("consensus", "rel_majority", "abs_majority", "preference", "unanimity"),
  strict = FALSE,
  second_method = c("consensus", "rel_majority", "abs_majority", "unanimity"),
  nb_agree_threshold = 1,
  preference_index = NULL,
  collapse_string = "/",
  replace_collapsed_rank_by_NA = FALSE
)

Arguments

vec

(required) A vector of (taxonomic) values

method

One of "consensus", "rel_majority", "abs_majority", "preference" or "unanimity". See details.

strict

(logical, default FALSE). If TRUE, NA are considered as informative in resolving conflict (i.e. NA are taking into account in vote). See details for more informations.

second_method

One of "consensus", "rel_majority", "abs_majority", or "unanimity". Only used if method = "preference". See details.

nb_agree_threshold

(Int, default 1) The minimum number of times a value must arise to be selected using vote. If 2, we only kept taxonomic value present at least 2 times in the vector.

preference_index

(Int. default NULL). Required if method="preference". Useless for other method. The preference index is the index of the value in vec for which we have a preference.

collapse_string

(default '/'). The character to collapse taxonomic names when multiple assignment is done.

replace_collapsed_rank_by_NA

(logical, default FALSE). If set to TRUE, all multiple assignments (all taxonomic rank including the 'collapse_string' parameter) are replaced by NA.

Value

a vector of length 1 (one character value)

Details

  • unanimity: Only keep taxonomic value when all methods are agree

    • By default, the value with NA are not taking into account (strict=FALSE)

    • If strict , one NA in the row is sufficient to return a NA

  • consensus: Keep all taxonomic values separated by a '/' (separation can be modify using param collapse_string)

    • If strict is TRUE, NA are also added to taxonomic vector such as 'Tiger/Cat/NA' instead of 'Tiger/Cat'

  • abs_majority: Keep the most found taxonomic value if it represent at least half of all taxonomic values.

    • If strict is TRUE, NA values are also count to determine the majority. For example, a vector of taxonomic rank c("A", "A", "A", "B", NA, NA) will give a value of 'A' if strict is FALSE (default) but a value of NA if strict is TRUE.

  • rel_majority: Keep the most found taxonomic value. In case of equality, apply a consensus strategy (collapse values separated by a '/') across the most found taxonomic values.

    • If strict is TRUE, NA are considered as a rank and can win the relative majority vote. If strict is FALSE (default), NA are removed before ranking the taxonomic values.

    • nb_agree_threshold: Only keep return value when at least x methods agreed with x is set by parameter nb_agree_threshold. By default, (nb_agree_threshold = 1): a majority of one is enough.

  • preference: Keep the value from a preferred column.

    • when the value is NA in the preferred column, apply a second strategy (by default consensus) to the other column (parameter second_method). Note that the parameters strict and nb_agree_threshold are used for the second_method consensus.

Author

Adrien Taudière

Examples


resolve_vector_ranks(c("A"))
#> [1] "A"
resolve_vector_ranks(c("A"),
  method = "preference",
  preference_index = 1
)
#> [1] "A"
resolve_vector_ranks(c("A"), method = "abs_majority")
#> [1] "A"
resolve_vector_ranks(c("A"), method = "rel_majority")
#> [1] "A"
resolve_vector_ranks(c("A"),
  method = "rel_majority",
  nb_agree_threshold = 2
)
#> [1] NA
resolve_vector_ranks(c("A"), method = "unanimity")
#> [1] "A"

resolve_vector_ranks(c("A", "A", "A"))
#> [1] "A"
resolve_vector_ranks(c("A", "A", "A"),
  method = "preference",
  preference_index = 1
)
#> [1] "A"
resolve_vector_ranks(c("A", "A", "A"), method = "abs_majority")
#> [1] "A"
resolve_vector_ranks(c("A", "A", "A"), method = "rel_majority")
#> [1] "A"
resolve_vector_ranks(c("A", "A", "A"), method = "unanimity")
#> [1] "A"

resolve_vector_ranks(c(NA, NA, NA))
#> [1] NA
resolve_vector_ranks(c(NA, NA, NA),
  method = "preference",
  preference_index = 1
)
#> [1] NA
resolve_vector_ranks(c(NA, NA, NA), method = "abs_majority")
#> [1] NA
resolve_vector_ranks(c(NA, NA, NA), method = "rel_majority")
#> [1] NA
resolve_vector_ranks(c(NA, NA, NA), method = "unanimity")
#> [1] NA

resolve_vector_ranks(c("A", "A", NA))
#> [1] "A"
resolve_vector_ranks(c("A", "A", NA),
  method = "preference",
  preference_index = 1
)
#> [1] "A"
resolve_vector_ranks(c("A", "A", NA), method = "rel_majority")
#> [1] "A"
resolve_vector_ranks(c("A", "A", NA), method = "abs_majority")
#> [1] "A"
resolve_vector_ranks(c("A", "A", NA, NA),
  method = "abs_majority",
  strict = FALSE
)
#> [1] "A"
resolve_vector_ranks(c("A", "A", NA, NA),
  method = "abs_majority",
  strict = TRUE
)
#> [1] NA
resolve_vector_ranks(c("A", "A", NA), method = "unanimity")
#> [1] "A"
resolve_vector_ranks(c("A", "A", NA),
  method = "unanimity",
  strict = TRUE
)
#> [1] NA

resolve_vector_ranks(c("A", "B", NA))
#> [1] "A/B"
resolve_vector_ranks(c("A", "B", NA), strict = TRUE)
#> [1] "A/B/NA"
resolve_vector_ranks(c("A", "B", NA),
  method = "preference",
  preference_index = 1
)
#> [1] "A"
resolve_vector_ranks(c("A", "B", NA), method = "abs_majority")
#> [1] NA
resolve_vector_ranks(c("A", "B", NA), method = "rel_majority")
#> [1] "A/B"
resolve_vector_ranks(c("A", "B", NA),
  method = "rel_majority",
  strict = TRUE
)
#> [1] "A/B/NA"
resolve_vector_ranks(c("A", "B", NA),
  method = "rel_majority",
  nb_agree_threshold = 2
)
#> [1] "A/B"
resolve_vector_ranks(c("A", "B", NA), method = "unanimity")
#> [1] NA

resolve_vector_ranks(c("A", NA, NA))
#> [1] "A"
resolve_vector_ranks(c("A", NA, NA), method = "rel_majority")
#> [1] "A"
resolve_vector_ranks(c("A", NA, NA), method = "unanimity")
#> [1] "A"
resolve_vector_ranks(c("A", NA, NA),
  method = "preference",
  preference_index = 1
)
#> [1] "A"
resolve_vector_ranks(c("A", NA, NA),
  method = "preference",
  preference_index = 2
)
#> [1] "A"
resolve_vector_ranks(c("A", NA, "B"),
  method = "preference",
  preference_index = 2
)
#> [1] "A/B"
resolve_vector_ranks(c("A", NA, "B"),
  method = "preference",
  preference_index = 2, second_method = "abs_majority"
)
#> [1] NA

resolve_vector_ranks(c("A", "B", "B"))
#> [1] "A/B"
resolve_vector_ranks(c("A", "B", "B"),
  method = "preference",
  preference_index = 1
)
#> [1] "A"
resolve_vector_ranks(c("A", "B", "B"), method = "abs_majority")
#> [1] "B"
resolve_vector_ranks(c("A", "B", "B"), method = "rel_majority")
#> [1] "B"
resolve_vector_ranks(c("A", "B", "B"), method = "unanimity")
#> [1] NA


resolve_vector_ranks(c("A", "A", "A", "B", NA, NA))
#> [1] "A/B"
resolve_vector_ranks(c("A", "A", "A", "B", NA, NA),
  strict = TRUE
)
#> [1] "A/B/NA"
resolve_vector_ranks(c("A", "A", "A", "B", NA, NA),
  method = "abs_majority"
)
#> [1] "A"
resolve_vector_ranks(c("A", "A", "A", "B", NA, NA),
  method = "abs_majority",
  strict = TRUE
)
#> [1] NA
resolve_vector_ranks(c("A", "A", "A", "B", NA, NA),
  method = "preference", preference_index = 6, second_method = "abs_majority"
)
#> [1] "A"
resolve_vector_ranks(c("A", "A", "A", "B", NA, NA, NA),
  method = "preference", preference_index = 6, second_method = "abs_majority"
)
#> [1] "A"
resolve_vector_ranks(c("A", "A", "A", "B", NA, NA, NA),
  method = "preference", preference_index = 6, second_method = "abs_majority",
  strict = TRUE
)
#> [1] NA