plot_locus_multi: Plot multi-GWAS/QTL or multi-ancestry fine-mapping results

In RajLabMSSM/echoplot: echoverse module: Locus plot creation for fine-mapping and colocalization studies

Plot multi-GWAS/QTL or multi-ancestry fine-mapping results

Description

Plot multi-GWAS/QTL or multi-ancestry(i.e. trans-ethnic) fine-mapping results generated by tools like PAINTOR.

Usage

plot_locus_multi(
  dat_ls,
  LD_ls,
  locus_dir,
  conditions = names(dat_ls),
  show_plot = TRUE,
  verbose = TRUE,
  ...
)

Arguments

dat_ls	A named list of data.tables generated by echolocatoR::finemap_loci.
LD_ls	A named list of link disequilibrium (LD) matrices (one per item in dat_ls).
locus_dir	Storage directory to use.
conditions	Conditions to group dat_ls by. The length of conditions must equal the number of items in dat_ls.
show_plot	Print plot to screen.
verbose	Print messages.
...	Arguments passed on to plot_locus dataset_type Dataset type (e.g. "GWAS" or "eQTL"). color_r2 Whether to color data points (SNPs) by how strongly they correlate with the lead SNP (i.g. LD measured in terms of r2). finemap_methods Fine-mapping methods to plot tracks for, where the y-axis show the Posterior Probabilities (PP) of each SNP being causal. track_order The order in which tracks should appear (from top to bottom). track_heights The height of each track (from top to bottom). plot_full_window Include a track with a Manhattan plot of the full GWAS/eQTL locus (not just the zoomed-in portion). dot_summary Include a dot-summary plot that highlights the Lead, Credible Set, and Consensus SNPs. qtl_suffixes If columns with QTL data is included in dat, you can indicate which columns those are with one or more string suffixes (e.g. qtl_suffixes=c(".eQTL1",".eQTL2") to use the columns "P.QTL1", "Effect.QTL1", "P.QTL2", "Effect.QTL2"). mean.PP Include a track showing mean Posterior Probabilities (PP) averaged across all fine-mapping methods. sig_cutoff Filters out SNPs to plot based on an (uncorrected) p-value significance cutoff. gene_track Include a track showing gene bodies. max_transcripts Maximum number of transcripts per gene. tx_biotypes Transcript biotypes to include in the gene model track. By default (NULL), all transcript biotypes will be included. See get_tx_biotypes for a full list of all available biotypes point_size Size of each data point. point_alpha Opacity of each data point. snp_group_lines Include vertical lines to help highlight SNPs belonging to one or more of the following groups: Lead, Credible Set, Consensus. labels_subset Include colored shapes and RSID labels to help highlight SNPs belonging to one or more of the following groups: Lead, Credible Set, Consensus. xtext Include x-axis title and text for each track (not just the lower-most one). show_legend_genes Show the legend for the gene_track. zoom_exceptions_str Names of tracks to exclude when zooming. xgr_libnames Passed to XGR_plot. Which XGR annotations to check overlap with. For full list of libraries see here. Passed to the RData.customised argument in xRDataLoader. Examples: "ENCODE_TFBS_ClusteredV3_CellTypes" "ENCODE_DNaseI_ClusteredV3_CellTypes" "Broad_Histone" xgr_n_top Passed to XGR_plot. Number of top annotations to be plotted (passed to XGR_filter_sources and then XGR_filter_assays). nott_epigenome Include tracks showing brain cell-type-specific epigenomic data from Nott et al. (2019). nott_regulatory_rects Include track generated by NOTT2019_epigenomic_histograms. nott_show_placseq Include track generated by NOTT2019_plac_seq_plot. nott_binwidth When including Nott et al. (2019) epigenomic data in the track plots, adjust the bin width of the histograms. nott_bigwig_dir Instead of pulling Nott et al. (2019) epigenomic data from the UCSC Genome Browser, use a set of local bigwig files. roadmap Find and plot annotations from Roadmap. roadmap_n_top Passed to ROADMAP_plot. Number of top annotations to be plotted (passed to ROADMAP_query). roadmap_query Only plot annotations from Roadmap whose metadata contains a string or any items from a list of strings (e.g. "brain" or c("brain","liver","monocytes")). credset_thresh The minimum fine-mapped posterior probability for a SNP to be considered part of a Credible Set. For example, credset_thresh=.95 means that all Credible Set SNPs will be 95% Credible Set SNPs. facet_formula Formula to facet plots by. See facet_grid for details. save_plot Save plot as RDS file. plot_format Format to save plot as when saving with ggsave. save_RDS Save the tracks as an RDS file (Warning: These plots take up a lot disk space). return_list Return a named list with each track as a separate plot (default: FALSE). If TRUE, will return a merged plot using wrap_plots. dat Data to query transcripts with. LD_reference LD reference to use: "1KGphase1" : 1000 Genomes Project Phase 1 (genome build: hg19). "1KGphase3" : 1000 Genomes Project Phase 3 (genome build: hg19). "UKB" : Pre-computed LD from a British European-decent subset of UK Biobank. Genome build : hg19 "<vcf_path>" : User-supplied path to a custom VCF file to compute LD matrix from. Accepted formats: .vcf / .vcf.gz / .vcf.bgz Genome build : defined by user with target_genome. "<matrix_path>" : User-supplied path to a pre-computed LD matrix Accepted formats: .rds / .rda / .csv / .tsv / .txt Genome build : defined by user with target_genome. conda_env Conda environments to search in. If NULL (default), will search all conda environments. nThread Number of threads to parallelize over. LD_matrix LD matrix. zoom Zoom into the center of the locus when plotting (without editing the fine-mapping results file). You can provide either: The size of your plot window in terms of basepairs (e.g. zoom=50000 for a 50kb window). How much you want to zoom in (e.g. zoom="1x" for the full locus, zoom="2x" for 2x zoom into the center of the locus, etc.). You can pass a list of window sizes (e.g. c(50000,100000,500000)) to automatically generate multiple views of each locus. This can even be a mix of different style inputs: e.g. c("1x","4.5x",25000). genomic_units Which genomic units to return window limits in. density_adjust Passed to adjust argument in geom_density. strip.text.y.angle Angle of the y-axis facet labels. dpi dpi to use for raster graphics height height (defaults to the height of current plotting window) width width (defaults to the width of current plotting window) consensus_thresh The minimum number of fine-mapping tools in which a SNP is in the Credible Set in order to be included in the "Consensus_SNP" column.

Examples

locus_dir <- file.path(tempdir(),echodata::locus_dir)
#### Make dat_ls ####
dat <- echodata::filter_snps(echodata::BST1, bp_distance = 10000) 
dat_ls <- list(gwas1=dat, gwas2=dat)
#### Make LD_ls ####
LD_matrix <- echodata::BST1_LD_matrix
LD_ls <- list(ancestry1=LD_matrix, ancestry2=LD_matrix)
#### Make plot ####
plot_list <- plot_locus_multi(dat_ls = dat_ls, 
                              LD_ls = LD_ls,
                              locus_dir = locus_dir)

RajLabMSSM/echoplot documentation built on Oct. 24, 2023, 2:41 a.m.