filterfun: Creates a first FALSE exiting function from the list

GITHUB
Bioconductor/genefilter: genefilter: methods for filtering genes from high-throughput experiments

returns FALSE otherwise it returns TRUE.
Usage
filterfun(...)

filterfun: Creates a first FALSE exiting function from the list

BIOC
genefilter: genefilter: methods for filtering genes from high-throughput experiments

otherwise it returns TRUE.
Usage
filterfun(...)

n_filterfun: A custom 'filterfun' that creates a n-FALSE exiting function...

GITHUB
jenzopr/singlecellutils: Utility functions for single-cell data

R: A custom 'filterfun' that creates a n-FALSE exiting function...
n_filterfunR Documentation
A custom filterfun

R/subset_pop_dectree.R:

GITHUB
n8thangreen/LTBIscreeningproject: LTBI screening cost-effectiveness analysis

",
filterFun = function(x) x$node_names == 'LTBI')
nonLTBI_trees <- Traverse(osNode, traversal = "post-order

R/get_biclusters.R:

GITHUB
tdrose/mosbi: Molecular Signature identification using Biclustering

") | (method == "biclust-unibic"))
extract_bf <- function(bics, mat, method, transposed, filterfun, ...){

R/subset_pop_dectree.R:

GITHUB
n8thangreen/ltbiScreenLite: ltbiScreenLite

",
filterFun = function(x) x$node_names == 'LTBI')
nonLTBI_trees <- Traverse(osNode, traversal = "post-order

getShortestPathSif: Get the shortest between two IDs (HGNC or CHEBI

BIOC
paxtoolsr: PaxtoolsR: Access Pathways from Multiple Databases through BioPAX and Pathway Commons

idB,
mode = c("all", "out", "in"),
weights = NULL,

getShortestPathSif: Get the shortest between two IDs (HGNC or CHEBI

GITHUB
cannin/paxtoolsr: Access Pathways from Multiple Databases Through BioPAX and Pathway Commons

idA,
idB,
mode = c("all", "out", "in"),

getShortestPathSif: Get the shortest between two IDs (HGNC or CHEBI

GITHUB
BioPAX/paxtoolsr: Access Pathways from Multiple Databases Through BioPAX and Pathway Commons

idA,
idB,
mode = c("all", "out", "in"),

R/assign_branch_vals.R:

GITHUB
n8thangreen/treeSimR: treeSimR

osNode$Set(p = vals,
filterFun = function(x) x$name == node_p)
if (all(c("pmin", "pmax

R/node_methods_traversal.R:

CRAN
data.tree: General Purpose Hierarchical Data Structure

in a specific order. It returns a list of
#' \code{\link{Node}} objects, filtered and pruned by \code{filterFun} and \code

R/snpinfo.R:

GITHUB
DavisBrian/seqtools: Sequence Analysis Tools

#' @param .filterFun (optional) a function to apply to multiple '.filterBy' fields via \code{Reduce}. See Details.
#' @param

scripts/prep-decisiontree.R:

GITHUB
n8thangreen/LTBIscreeningproject: LTBI screening cost-effectiveness analysis

= p_incid_grp[i],
pmax = p_incid_grp[i],
filterFun = function(x) x$name == names

R/filter_biclusters.R:

GITHUB
tdrose/mosbi: Molecular Signature identification using Biclustering

#' @param filterfun A function to filter biclusters. Only if the function
#' returns \code{True}, the bicluster is added

R/node_methods_traversal.R:

GITHUB
gluc/data.tree: General Purpose Hierarchical Data Structure

in a specific order. It returns a list of
#' \code{\link{Node}} objects, filtered and pruned by \code{filterFun} and \code

getFabiaClusters: Extract a list of bicluster objects from an fabia

GITHUB
tdrose/mosbi: Molecular Signature identification using Biclustering

object.
Usage
getFabiaClusters(bics, mat, transposed = FALSE, filterfun = NULL, ...)

getBiclustpyClusters: Extract a list of bicluster objects from an biclustpy output

GITHUB
tdrose/mosbi: Molecular Signature identification using Biclustering

output file.
Usage
getBiclustpyClusters(bics, mat, transposed = FALSE, filterfun = NULL, ...)

R/rxs_get_values.R:

GITHUB
Matherion/metabefor: Facilitating systematic review and meta-analyses

study
if (is.null(entityName) && is.null(withinEntity)) {
filterFun = NULL;

R/extract_biclust.R:

GITHUB
tdrose/mosbi: Molecular Signature identification using Biclustering

",
#' "biclust-unibic".
#' @param filterfun A function to filter biclusters. Only if the function

R/calculate.R:

GITHUB
gluc/ahp: Analytic Hierarchy Process

. from priority/weight into weight matrix
prefTrees <- ahpTree$Get(attribute = function(x) x$preferences, filterFun