Mine high-confidence candidate genes in a single step

Usage

mine_candidates(
  gene_ranges = NULL,
  marker_ranges = NULL,
  window = 2,
  expand_intervals = TRUE,
  gene_col = "ID",
  exp = NULL,
  gcn = NULL,
  guides = NULL,
  metadata,
  metadata_cols = 1,
  sample_group,
  min_cor = 0.2,
  alpha = 0.05,
  ...
)

Arguments

gene_ranges: A GRanges object with genomic coordinates of all genes in the genome.
marker_ranges: Genomic positions of SNPs. For a single trait, a GRanges object. For multiple traits, a GRangesList or CompressedGRangesList object, with each element of the list representing SNP positions for a particular trait.
window: Sliding window (in Mb) upstream and downstream relative to each SNP. Default: 2.
expand_intervals: Logical indicating whether or not to expand markers that are represented by intervals. This is particularly useful if users want to use a custom interval defined by linkage disequilibrium, for example. Default: TRUE.
gene_col: Column of the GRanges object containing gene ID. Default: "ID", the default for gff/gff3 files imported with rtracklayer::import.
exp: Expression data frame with genes in row names and samples in column names or a SummarizedExperiment object.
gcn: Gene coexpression network returned by BioNERO::exp2gcn().
guides: Guide genes as a character vector or as a data frame with genes in the first column and gene annotation class in the second column.
metadata: Sample metadata with samples in row names and sample information in the first column. Ignored if exp is a SummarizedExperiment object, as the colData will be extracted from the object.
metadata_cols: A vector (either numeric or character) indicating which columns should be extracted from column metadata if exp is a SummarizedExperiment object. The vector can contain column indices (numeric) or column names (character). By default, all columns are used.
sample_group: Level of sample metadata to be used for filtering in gene-trait correlation.
min_cor: Minimum correlation value for BioNERO::gene_significance(). Default: 0.2
alpha: Numeric indicating significance level. Default: 0.05
...: Additional arguments to BioNERO::gene_significance.

Value

A data frame with mined candidate genes and their correlation to the condition of interest.

Examples

# \donttest{
data(pepper_se)
data(snp_pos)
data(gene_ranges)
data(guides)
data(gcn)
set.seed(1)
candidates <- mine_candidates(gene_ranges, snp_pos, exp = pepper_se,
                              gcn = gcn, guides = guides$Gene,
                              sample_group = "PRR_stress")
#> Enrichment analysis for module cyan...
# }