Nothing

```
#' Filter a co-elution profile matrix
#'
#' Filter a matrix of co-elution/co-fractionation profiles by removing
#' profiles without a certain number of non-mising or consecutive points.
#'
#' @param profile_matrix a numeric matrix of co-elution profiles, with proteins
#' in rows, or a \code{\linkS4class{MSnSet}} object
#' @param min_points filter profiles without at least this many total,
#' non-missing points
#' @param min_consecutive filter profiles without at least this many
#' consecutive, non-missing points
#'
#' @return the filtered profile matrix
#'
#' @examples
#' data(scott)
#' nrow(scott)
#' filtered <- filter_profiles(scott)
#' nrow(scott)
#'
#' @importFrom MSnbase exprs
#' @importFrom Biobase exprs<-
#' @importFrom methods is
#' @importFrom purrr map_int
#'
#' @export
filter_profiles <- function(profile_matrix, min_points = 1,
min_consecutive = 5) {
# filter profiles without N non-missing points
nas <- is.na(profile_matrix)
if (!is.na(min_points) & !is.null(min_points) & min_points > 0) {
profile_matrix <- profile_matrix[rowSums(!nas) >= min_points, ]
} else {
# need to at least filter profiles without any points
profile_matrix <- profile_matrix[rowSums(!nas) >= 1, ]
}
# filter profiles without N consecutive points after imputation
if (!is.na(min_consecutive) & !is.null(min_consecutive) &
min_consecutive > 0) {
if (is(profile_matrix, "MSnSet")) {
expr <- exprs(profile_matrix)
} else {
expr <- profile_matrix
}
imputed <- t(apply(expr, 1, impute_neighbors))
imputed_nas <- is.na(imputed)
rles <- apply(imputed_nas, 1, rle)
max_consecutive <- map_int(rles, ~ max(.$lengths[.$values == FALSE]))
profile_matrix <- profile_matrix[max_consecutive >= min_consecutive, ]
}
return(profile_matrix)
}
```

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