mine_candidates: Mine high-confidence candidate genes in a single step

In almeidasilvaf/cageminer: Candidate Gene Miner

Mine high-confidence candidate genes in a single step

Description

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

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")

almeidasilvaf/cageminer documentation built on Sept. 9, 2023, 5:18 p.m.