Man pages for RajLabMSSM/echoannot
echoverse module: Annotate fine-mapping results
| add_mb | Add Mb |
| annotate_missense | Annotate any missense variants |
| annotate_snps | Annotate merged fine-mapping results from all loci |
| annotation_file_name | Annotation file name |
| biomart_snp_info | Download SNP-wise annotations from Biomart |
| biomart_snps_to_geneInfo | Identify which genes SNPs belong to using Biomart |
| cell_type_specificity | Get cell-type-specifity score for each cell type |
| clean_granges | Clean GRanges object |
| coloc_nominated_eGenes | Nominate target genes within each locus |
| convert_plots | Convert plots to various formats |
| CORCES2020_get_ATAC_peak_overlap | Get overlap between datatable of SNPs and scATAC peaks |
| CORCES2020_get_hichip_fithichip_overlap | Get overlap between data table of SNPs and HiChIP_FitHiChIP... |
| CORCES2020_prepare_bulkATAC_peak_overlap | Prepare data to plot overlap between datatable of SNPs and... |
| CORCES2020_prepare_scATAC_peak_overlap | Prepare CORCES2020 scATAC-seq peak overlap data |
| CS_bin_plot | Plot CS bin counts |
| CS_counts_plot | Bar plot of tool-specific CS sizes |
| filter_chromatin_states | Filter chromatin states |
| find_top_consensus | Find the top Consensus SNP |
| get_bpparam | Get BiocParallel parameters |
| get_CORCES2020_bulkATACseq_peaks | bulkATACseq peaks from human brain tissue |
| get_CORCES2020_cicero_coaccessibility | Cicero_coaccessibility from human brain tissue |
| get_CORCES2020_hichip_fithichip_loop_calls | FitHiChIP loop calls from human brain tissue |
| get_CORCES2020_scATACseq_celltype_peaks | scATACseq cell type-specific peaks from human brain tissue |
| get_CORCES2020_scATACseq_peaks | scATACseq peaks from human brain tissue |
| get_data | Get data |
| get_max_histogram_height | get_max_histogram_height |
| get_NOTT2019_interactome | Brain cell type-specific enhancers, promoters, and... |
| get_NOTT2019_superenhancer_interactome | Brain cell type-specific interactomes with superenhancers |
| get_top_consensus_pos | Get top consensus position |
| get_window_limits | Get widow limits |
| granges_overlap | Find GenomicRanges overlap Find overlap genomic position... |
| haplor_epigenetics_enrichment | Test for enrichment of 'HaploR' annotations |
| haplor_epigenetics_summary | Summarise 'HaploR' annotations |
| haplor_haploreg | Download SNP-wise annotations from HaploReg |
| haplor_regulomedb | Download SNP-wise annotations from RegulomeDB |
| IMPACT_files | IMPACT files |
| IMPACT_process | Process IMPACT files |
| IMPACT_query | Query IMPACT annotations |
| import_bigwig_filtered | Import filtered bigwig |
| import_ucsc_bigwigs | Import bigwig files from the UCSC Genome Browser |
| merge_celltype_specific_epigenomics | Merge all cell-type-specific epigenomics |
| message_parallel | Send messages to console even from within parallel processes |
| MOTIFBREAKR | Run 'motifbreakR' |
| MOTIFBREAKR_calc_pvals | Calculate 'motifbreakR' p-values |
| MOTIFBREAKR_filter | Merge and filter 'motifbreakR' + 'echolocatoR' results |
| MOTIFBREAKR_filter_by_metadata | Filter 'motifbreakR' results |
| MOTIFBREAKR_make_id | MOTIFBREAKR: make ID |
| MOTIFBREAKR_plot | Plot 'motifbreakR' results |
| MOTIFBREAKR_summarize | Summarize 'motifbreakR' + 'echolocatoR' results |
| name_filter_convert | name_filter_convert |
| NOTT2019_bigwig_metadata | Metadata and links to data |
| NOTT2019_epigenomic_histograms | Plot brain cell-specific epigenomic data |
| NOTT2019_get_epigenomic_peaks | Download cell type-specific epigenomic peaks |
| NOTT2019_get_interactions | Import cell type-specific interactomes |
| NOTT2019_get_interactome | Import cell type-specific interactomes |
| NOTT2019_get_promoter_celltypes | Get promoter cell types |
| NOTT2019_get_promoter_interactome_data | Get cell type-specific promoter/emhancer/interactome data |
| NOTT2019_get_regulatory_regions | Get regulatory regions: Nott2019 |
| NOTT2019_plac_seq_plot | Plot brain cell-specific interactome data |
| NOTT2019_superenhancers | Get cell type-specific superenhancer data |
| order_loci | Order loci by UCS size, or alphabetically |
| PAINTOR_process | Process PAINTOR files |
| peak_overlap | Get overlap between SNPs and epigenomic peaks |
| peak_overlap_plot | Plot overlap between some SNP group and various epigenomic... |
| plot_dataset_overlap | Plot inter-study SNP overlap |
| plot_missense | Plot any missense variants |
| rbind_granges | Bind GRanges with different mcols |
| ROADMAP_construct_reference | Gather Roadmap annotation metadata |
| ROADMAP_merge_and_process | Standardize Roadmap query |
| ROADMAP_query | Query Roadmap Query Roadmap annotations using a set of... |
| ROADMAP_tabix | Query Roadmap API |
| select_genome | Select genome build |
| snps_by_mutation_type | Return only the missense SNPs |
| super_summary_plot | Merge all summary plots into one super plot |
| test_enrichment | Test enrichment |
| tracks_to_ggplot_list | Convert ggbio tracks plot to ggplot2 list |
| XGR_enrichment | XGR enrichment |
| XGR_enrichment_bootstrap | XGR enrichment (bootstrapped) |
| XGR_enrichment_plot | Plot enrichment results |
| xgr_example | Example XGR query |
| XGR_filter_assays | Filter assays |
| XGR_filter_sources | Filter sources |
| XGR_import_annotations | Download XGR annotations |
| XGR_iterate_enrichment | Conduct enrichment tests for each annotation |
| XGR_iterate_overlap | Check overlap with XGR annotations |
| XGR_merge_and_process | Standardize XGR annotations |
| XGR_parse_metadata | XGR_parse_metadata |
| XGR_plot_enrichment | Plot XGR enrichment |
| XGR_prepare_foreground_background | Prepare SNP sets for enrichment |
| xgr_query | Download, standardize, and merge XGR annotations |
| XGR_sep_handler | XGR_sep_handler |
