QFeatures-filtering {QFeatures} | R Documentation

## Filter features based on their rowData

### Description

The `filterFeatures` methods enables users to filter features based on a variable in their `rowData`. The features matching the filter will be returned as a new object of class `QFeatures`. The filters can be provided as instances of class `AnnotationFilter` (see below) or as formulas.

### Usage

    VariableFilter(field, value, condition = "==", not = FALSE)

    ## S4 method for signature 'QFeatures,AnnotationFilter'
    filterFeatures(object, filter, na.rm = FALSE, ...)

    ## S4 method for signature 'QFeatures,formula'
    filterFeatures(object, filter, na.rm = FALSE, ...)

### Arguments

`field` | `character(1)` refering to the name of the variable to apply the filter on.
`value` | `character()` or `integer()` value for the `CharacterVariableFilter` and `NumericVariableFilter` filters respectively.
`condition` | `character(1)` defining the condition to be used in the filter. For `NumericVariableFilter`, one of `"=="`, `"!="`, `">"`, `"<"`, `">="` or `"<="`. For `CharacterVariableFilter`, one of `"=="`, `"!="`, `"startsWith"`, `"endsWith"` or `"contains"`. Default condition is `"=="`.
`not` | `logical(1)` indicating whether the filtering should be negated or not. `TRUE` indicates is negated (!). `FALSE` indicates not negated. Default `not` is `FALSE`, so no negation.
`object` | An instance of class QFeatures.
`filter` | Either an instance of class AnnotationFilter or a formula.
`na.rm` | `logical(1)` indicating whether missing values should be removed. Default is `FALSE`.
`...` | Additional parameters. Currently ignored.

### Value

An filtered `QFeature` object.

### Variable filters

The variable filters are filters as defined in the AnnotationFilter package. In addition to the pre-defined filter, users can arbitrarily set a field on which to operate. These arbitrary filters operate either on a character variables (as `CharacterVariableFilter` objects) or numerics (as `NumericVariableFilters` objects), which can be created with the `VariableFilter` constructor.

### Author(s)

Laurent Gatto

### See Also

The QFeatures man page for subsetting and the `QFeatures` vignette provides an extended example.

### Examples

    ## ----------------------------------------
    ## Creating character and numberic
    ## variable filters
    ## ----------------------------------------

    VariableFilter(field = "my_var",
                   value = "value_to_keep",
                   condition = "==")

    VariableFilter(field = "my_num_var",
                   value = 0.05,
                   condition = "<=")

    example(aggregateFeatures)

    ## ----------------------------------------------------------------
    ## Filter all features that are associated to the Mitochondrion in
    ## the location feature variable. This variable is present in all
    ## assays.
    ## ----------------------------------------------------------------

    ## using the forumla interface, exact mathc
    filterFeatures(feat1, ~  location == "Mitochondrion")

    ## using the forumula intefrace, martial match
    filterFeatures(feat1, ~startsWith(location, "Mito"))

    ## using a user-defined character filter
    filterFeatures(feat1, VariableFilter("location", "Mitochondrion"))

    ## using a user-defined character filter with partial match
    filterFeatures(feat1, VariableFilter("location", "Mito", "startsWith"))
    filterFeatures(feat1, VariableFilter("location", "itochon", "contains"))

    ## ----------------------------------------------------------------
    ## Filter all features that aren't marked as unknown (sub-cellular
    ## location) in the feature variable
    ## ----------------------------------------------------------------

    ## using a user-defined character filter
    filterFeatures(feat1, VariableFilter("location", "unknown", condition = "!="))

    ## using the forumula interface
    filterFeatures(feat1, ~ location != "unknown")

    ## ----------------------------------------------------------------
    ## Filter features that have a p-values lower or equal to 0.03
    ## ----------------------------------------------------------------

    ## using a user-defined numeric filter
    filterFeatures(feat1, VariableFilter("pval", 0.03, "<="))

    ## using the formula interface
    filterFeatures(feat1, ~ pval <= 0.03)

    ## you can also remove all p-values that are NA (if any)
    filterFeatures(feat1, ~ !is.na(pval))

    ## ----------------------------------------------------------------
    ## Negative control - filtering for an non-existing markers value
    ## or a missing feature variable, returning empty results
    ## ----------------------------------------------------------------

    filterFeatures(feat1, VariableFilter("location", "not"))

    filterFeatures(feat1, ~ location == "not")

    filterFeatures(feat1, VariableFilter("foo", "bar"))

    filterFeatures(feat1, ~ foo == "bar")

    ## ----------------------------------------------------------------
    ## Example with missing values
    ## ----------------------------------------------------------------

    data(feat1)
    rowData(feat1[[1]])[1, "location"] <- NA
    rowData(feat1[[1]])

    ## The row with the NA is not removed
    rowData(filterFeatures(feat1, ~ location == "Mitochondrion")[[1]])
    rowData(filterFeatures(feat1, ~ location == "Mitochondrion", na.rm = FALSE)[[1]])

    ## The row with the NA is removed
    rowData(filterFeatures(feat1, ~ location == "Mitochondrion", na.rm = TRUE)[[1]])

    ## Note that in situations with missing values, it is possible to
    ## use the `%in%` operator or filter missing values out
    ## explicitly.

    rowData(filterFeatures(feat1, ~ location %in% "Mitochondrion")[[1]])
    rowData(filterFeatures(feat1, ~ location %in% c(NA, "Mitochondrion"))[[1]])

    ## Explicit handling
    filterFeatures(feat1, ~ !is.na(location) & location == "Mitochondrion")

    ## Using the pipe operator
    library("magrittr")
    feat1 %>%
       filterFeatures( ~ !is.na(location)) %>%
       filterFeatures( ~ location == "Mitochondrion")

[Package QFeatures version 1.0.0 Index]