This package aims to integrate GWAS-derived SNPs and coexpression networks to mine candidate genes associated with a particular phenotype. For that, users must define a set of guide genes, which are known genes involved in the studied phenotype. Additionally, the mined candidates can be given a score that favor candidates that are hubs and/or transcription factors. The scores can then be used to rank and select the top n most promising genes for downstream experiments.
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Integrate GWAS SNPs and coexpression networks to mine and score high-confidence candidate genes.
library(cageminer)
library(GenomicRanges)
# 1. Visualize SNP distribution across chromosomes
plot_snp_distribution(snp_pos)
plot_snp_circos(chr_length, gene_ranges, snp_pos)
# 2. Identify genes close to SNPs
candidates1 <- mine_step1(gene_ranges, snp_pos)
# 3. Infer a gene coexpression network
sft <- BioNERO::SFT_fit(pepper_se, net_type = "signed", cor_method = "pearson")
gcn <- BioNERO::exp2gcn(pepper_se, net_type = "signed", cor_method = "pearson",
module_merging_threshold = 0.8, SFTpower = sft$power)
# 4. Filter candidates in coexpression modules enriched in guide genes
candidates2 <- mine_step2(pepper_se, gcn = gcn, guides = guides$Gene, candidates = candidates1$ID)
# 5. Identify candidates with altered expression in a condition of interest
candidates3 <- mine_step3(pepper_se, candidates = candidates2$candidates, sample_group = "PRR_stress")
# Alternatively, perform steps 2-5 automatically using mine_candidates:
# candidates <- mine_candidates(gene_ranges = gene_ranges, marker_ranges = snp_pos,
# exp = pepper_se, gcn = gcn, guides = guides$Gene,
# sample_group = "PRR_stress")
# 6. Score and prioritize candidates
hubs <- BioNERO::get_hubs_gcn(pepper_se, gcn)
scored <- score_genes(candidates3, hubs$Gene, tfs$Gene_ID)
Note: Inputs are GRanges of SNP and gene coordinates, a SummarizedExperiment of expression data, and a vector of guide genes; output is a ranked data frame of scored candidate genes.
mine_step1.mine_step2.score_genes.mine_step2 relies on guide gene enrichment.GRanges or GRangesList (for multiple traits) objects.SummarizedExperiment object.GRanges object containing gene coordinates.GRanges or GRangesList object containing SNP positions.BioNERO::SFT_fit.plot_snp_distribution and plot_snp_circos to visually inspect SNP distributions across chromosomes before running the mining pipeline.simulate_windows to evaluate different sliding window sizes for selecting putative candidates in mine_step1.gene_ranges, pepper_se, and guides use the exact same nomenclature.BioNERO for general gene coexpression network analysis.rtracklayer for importing genomic coordinates from GFF/GTF files.还没有评价。欢迎分享你的使用感受。
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