\"]],\"shownColumns\":8,\"totalColumns\":11,\"truncatedColumns\":true},\"tests/fixtures/ld_prune_reference/protocol_example.ld_genotype.list\":{\"kind\":\"table\",\"rows\":[[\"tests/fixtures/ld_prune_reference/genotype/protocol_example.ld_genotype.chr22\"]],\"shownColumns\":1,\"totalColumns\":1,\"truncatedColumns\":false},\"tests/fixtures/genotype_formatting/geno/chr21.bed\":{\"kind\":\"plink\",\"lines\":[\"Object: PLINK 1 binary genotype (.bed/.bim/.fam)\",\" 17,321 variants x 60 samples\",\" Genotypes are packed binary. The .bim and .fam beside it are text.\",\"$variants (.bim) chr / id / cm / pos / a1 / a2\",\" 21 chr21:5091891_A_G 0 5091891 G A\",\" 21 chr21:5097593_CGTCCCTTCCC… 0 5097593 C CGTCCCTTCCCGAGGTTCCAGGCGG…\",\" 21 chr21:5097593_CGTCCCTTCCC… 0 5097593 CGTCCCTTCCCGAGGTTCCAGGCGG… CGTCCCTTCCCGAGGTTCCAGGCGG…\",\"$samples (.fam) fid / iid / pid / mid / sex / pheno\",\" 0 SAMPLE_001 0 0 0 -9\",\" 0 SAMPLE_002 0 0 0 -9\"]},\"tests/fixtures/ld_prune_reference/genotype/protocol_example.ld_genotype.chr22.bed\":{\"kind\":\"plink\",\"lines\":[\"Object: PLINK 1 binary genotype (.bed/.bim/.fam)\",\" 18,489 variants x 60 samples\",\" Genotypes are packed binary. The .bim and .fam beside it are text.\",\"$variants (.bim) chr / id / cm / pos / a1 / a2\",\" 22 chr22:10526333_CGCCGCCGCG… 0 10526333 * CGCCGCCGCGGGTTTTTTCCCCCGC…\",\" 22 chr22:10526566_AC_* 0 10526566 * AC\",\" 22 chr22:10657618_C_G 0 10657618 G C\",\"$samples (.fam) fid / iid / pid / mid / sex / pheno\",\" 0 SAMPLE_001 0 0 0 -9\",\" 0 SAMPLE_002 0 0 0 -9\"]},\"tests/fixtures/pca/protocol_example.unrelated.prune.bed\":{\"kind\":\"plink\",\"lines\":[\"Object: PLINK 1 binary genotype (.bed/.bim/.fam)\",\" 731 variants x 59 samples\",\" Genotypes are packed binary. The .bim and .fam beside it are text.\",\"$variants (.bim) chr / id / cm / pos / a1 / a2\",\" 20 chr20:5282_G_A 0 5282 A G\",\" 20 chr20:13922_T_C 0 13922 C T\",\" 20 chr20:16825_T_G 0 16825 G T\",\"$samples (.fam) fid / iid / pid / mid / sex / pheno\",\" SAMPLE_001 SAMPLE_001 0 0 0 -9\",\" SAMPLE_002 SAMPLE_002 0 0 0 -9\"]},\"tests/fixtures/qtl_mini/protocol_example.genotype.chr22.bed\":{\"kind\":\"plink\",\"lines\":[\"Object: PLINK 1 binary genotype (.bed/.bim/.fam)\",\" 1,995 variants x 49 samples\",\" Genotypes are packed binary. The .bim and .fam beside it are text.\",\"$variants (.bim) chr / id / cm / pos / a1 / a2\",\" 22 chr22:10414272:A:T 0 10414272 A T\",\" 22 chr22:10416111:A:T 0 10416111 A T\",\" 22 chr22:10416669:A:T 0 10416669 A T\",\"$samples (.fam) fid / iid / pid / mid / sex / pheno\",\" SAMPLE_001 SAMPLE_001 0 0 0 -9\",\" SAMPLE_002 SAMPLE_002 0 0 0 -9\"]},\"tests/fixtures/sldsc_enrichment/reference.2.bed\":{\"kind\":\"plink\",\"lines\":[\"Object: PLINK 1 binary genotype (.bed/.bim/.fam)\",\" 343 variants x 489 samples\",\" Genotypes are packed binary. The .bim and .fam beside it are text.\",\"$variants (.bim) chr / id / cm / pos / a1 / a2\",\" 2 rs10865542 1.2160932 1081594 G T\",\" 2 rs13015040 2.5067138 1861586 G A\",\" 2 rs719876 4.0279336 2654789 G A\",\"$samples (.fam) fid / iid / pid / mid / sex / pheno\",\" HG00096 HG00096 0 0 0 -9\",\" HG00097 HG00097 0 0 0 -9\"]},\"tests/fixtures/mnm_regression/expected/protocol_example.ENSG00000283047.multicontext_bvsr.rds\":{\"kind\":\"rds\",\"lines\":[\"Object: QtlFineMappingResult [8 columns]\",\" Components: study, context, trait, method, entry, jointContexts, region, traitPos\",\" Joint multi-context fit from the mnm step.\",\"$study : protocol_example\",\"$context : context1, context2\",\"$trait : ENSG00000283047\",\"$method : mvsusie\",\"$entry : FineMappingEntry, holds per-variant credible sets and PIPs\",\"$jointContexts: the contexts combined in the joint fit\"]},\"tests/fixtures/vcf_qc/expected/qc_2.variants.tsv\":{\"kind\":\"note\",\"lines\":[\"Empty file (0 bytes) — this is the expected result.\",\" On this toy data the GT-only variant-QC filters remove every record,\",\" so the variant table is empty. The fixture pins that outcome:\",\" test_qc_2 asserts the projection matches this empty file.\"]}};\n",
"function pvEsc(s){return String(s).replace(/[&<>\"']/g,c=>({'&':'&','<':'<','>':'>','\"':'"',\"'\":'''}[c]));}\n",
"function previewHTML(path){const p=PREVIEWS[path];if(!p)return '';\n",
- " if(p.kind==='summary'||p.kind==='rds')return `R object preview
${p.lines.map(pvEsc).join('\\n')}`;\n",
+ " if(p.kind==='summary'||p.kind==='rds')return `R object preview
${p.lines.map(pvEsc).join('\\n')}`;if(p.kind==='plink')return `PLINK binary genotype — not a text table
${p.lines.map(pvEsc).join('\\n')}`;if(p.kind==='note')return `File note
${p.lines.map(pvEsc).join('\\n')}`;\n",
" const rows=p.rows||[],n=p.shownColumns||0,head=rows[0]||[],body=rows.slice(1);\n",
" const cells=(r,tag)=>Array.from({length:n},(_,i)=>`<${tag}>${pvEsc(r[i]===undefined?'':r[i])}`).join('');\n",
" const note=`Showing ${n}${p.truncatedColumns?` of ${p.totalColumns}`:''} columns and ${rows.length} rows.`;\n",
" return `${note}
`;\n",
"}\n",
- "const FXWF={\"mixture_prior\":{\"mashr_input.rds\":[\"*\"],\"cov.flash.EE.rds\":[\"flash\"],\"cov.flash_nonneg.EE.rds\":[\"flash_nonneg\"],\"cov.pca.EE.rds\":[\"pca\"],\"cov.canonical.EE.rds\":[\"canonical\"],\"vhat.identity.EE.rds\":[\"vhat_identity\"],\"vhat.simple.EE.rds\":[\"vhat_simple\"],\"vhat.corshrink.EE.rds\":[\"vhat_corshrink_xcondition\"],\"vhat.simple_specific.EE.rds\":[\"vhat_simple_specific\"],\"prior.cov_ed.EE.rds\":[\"ed_bovy\"],\"mixture_prior.EE.prior.rds\":[\"ed_bovy\",\"ud\",\"ud_unconstrained\"]},\"phenotype_imputation\":{\"protocol_example.protein.missing.bed.gz\":[\"*\"],\"protocol_example.protein.missing.filtered.imputed.bed.gz\":[\"bed_filter_na\"],\"protocol_example.protein.missing.EBMF.imputed.bed.gz\":[\"EBMF\"],\"protocol_example.protein.missing.knn.imputed.bed.gz\":[\"knn\"],\"protocol_example.protein.missing.mean.imputed.bed.gz\":[\"mean\"],\"protocol_example.protein.missing.lod.imputed.bed.gz\":[\"lod\"],\"protocol_example.protein.missing.soft.imputed.bed.gz\":[\"soft\"]},\"covariate_hidden_factor\":{\"covariates.tsv\":[\"*\"],\"residual.bed.gz\":[\"*\"],\"Marchenko_PC.gz\":[\"Marchenko_PC\"],\"Buja_Eyuboglu_PC.gz\":[\"PCA\"],\"PEER.factors.tsv\":[\"PEER\"],\"PEER.weights.tsv\":[\"PEER\"],\"PEER.variance.tsv\":[\"PEER\"],\"PEER.gz\":[\"PEER\"]},\"gene_annotation\":{\"protocol_example.atac.tsv\":[\"annotate_coord\"],\"protocol_example.rnaseq.bed.gz\":[\"annotate_coord\"],\"protocol_example.rnaseq.bed.bed.gz\":[\"annotate_coord\"],\"protocol_example.rnaseq.bed.gene_list.tsv\":[\"annotate_coord\"],\"protocol_example.rnaseq.bed.region_list.txt\":[\"annotate_coord\"],\"protocol_example.protein.no_coord.bed.gz\":[\"annotate_coord\",\"annotate_coord_biomart\"],\"protocol_example.protein.no_coord.gene_list.tsv\":[\"annotate_coord\",\"annotate_coord_biomart\"],\"protocol_example.protein.no_coord.region_list.txt\":[\"annotate_coord\",\"annotate_coord_biomart\"],\"protocol_example.atac.bed.gz\":[\"annotate_coord\"],\"protocol_example.atac.region_list.txt\":[\"annotate_coord\"],\"protocol_example.leafcutter.intron_count.tsv.leafcutter.clusters_to_genes.txt\":[\"map_leafcutter_cluster_to_gene\"],\"protocol_example.leafcutter.phenotype.bed.formated.bed.gz\":[\"annotate_leafcutter_isoforms\"],\"protocol_example.leafcutter.phenotype.bed.phenotype_group.txt\":[\"annotate_leafcutter_isoforms\"],\"protocol_example.psichomics.phenotype.formated.bed.gz\":[\"annotate_psichomics_isoforms\"],\"protocol_example.psichomics.phenotype.phenotype_group.txt\":[\"annotate_psichomics_isoforms\"]},\"mnm_regression\":{\"univariate_bvsr.rds\":[\"susie_twas\"],\"univariate_twas_weights.rds\":[\"susie_twas\"],\"protocol_example.genotype.chr22.bed\":[\"*\"],\"protocol_example.pheno_manifest_context.tsv\":[\"*\"],\"example_covariates.tsv\":[\"*\"],\"association_windows.bed\":[\"*\"],\"protocol_example.ENSG00000283047.multicontext_bvsr.rds\":[\"*\"]},\"colocboost\":{\"protocol_example.genotype.chr22.bed\":[\"*\"],\"protocol_example.pheno_manifest_context.tsv\":[\"*\"],\"example_covariates.tsv\":[\"*\"],\"association_windows.bed\":[\"*\"],\"test_coloc.ENSG00000283047.colocboost.rds\":[\"*\"]},\"mash_posterior\":{\"region_strong.rds\":[\"*\"],\"fine_mapping.rds\":[\"*\"],\"orig.rds\":[\"*\"],\"posterior.rds\":[\"*\"]},\"ld_prune_reference\":{\"protocol_example.ld_genotype.chr22.bed\":[\"*\"],\"protocol_example.ld_genotype.list\":[\"*\"],\"LD_pruned_variants.txt\":[\"*\"]},\"rss_ld_sketch\":{\"protocol_example.genotype.chr22.vcf.gz\":[\"*\"],\"protocol_example.ld_blocks.bed\":[\"*\"],\"afreq_deterministic.tsv\":[\"*\"],\"event_id.tsv\":[\"*\"]},\"snRNAseq_preprocessing\":{\"protocol_example.snrnaseq.id_mapping.csv\":[\"*\"],\"protocol_example.snrnaseq.seurat_ref_SE.rds\":[\"*\"],\"expected_manifest.tsv\":[\"*\"]},\"RNA_calling\":{\"protocol_example.rnaseq.fastq.list.txt\":[\"*\"],\"adapters.fa\":[\"*\"],\"SAMPLE_001.strand.txt\":[\"*\"],\"fastq.list.trimmed.txt\":[\"*\"],\"rnaseqc.rnaseqc.exon_readsCount.gct.gz\":[\"*\"],\"rnaseqc.rnaseqc.gene_readsCount.gct.gz\":[\"*\"],\"rnaseqc.rnaseqc.gene_tpm.gct.gz\":[\"*\"],\"rnaseqc.rnaseqc.metrics.tsv\":[\"*\"]},\"apa_calling\":{\"chr22_3UTR.bed\":[\"*\"],\"expected_3UTR.bed\":[\"*\"],\"expected_gene_annotation.bed\":[\"*\"],\"protocol_example.expected_3UTR.bed\":[\"*\"],\"protocol_example.expected_gene_annotation.bed\":[\"*\"],\"chr22.hdr.gtf.gz\":[\"*\"],\"expected_pdui_data.txt\":[\"*\"],\"expected_transcript_to_geneName.txt\":[\"*\"]}};\n",
+ "const FXWF={\"mixture_prior\":{\"mashr_input.rds\":[\"*\"],\"cov.flash.EE.rds\":[\"*\"],\"cov.flash_nonneg.EE.rds\":[\"*\"],\"cov.pca.EE.rds\":[\"*\"],\"cov.canonical.EE.rds\":[\"*\"],\"vhat.identity.EE.rds\":[\"*\"],\"vhat.simple.EE.rds\":[\"*\"],\"vhat.corshrink.EE.rds\":[\"*\"],\"vhat.simple_specific.EE.rds\":[\"*\"],\"prior.cov_ed.EE.rds\":[\"*\"],\"mixture_prior.EE.prior.rds\":[\"*\"],\"region_strong.rds\":[\"*\"],\"Ast_De_Jager_eQTL.tsv\":[\"*\"]},\"phenotype_imputation\":{\"protocol_example.protein.missing.bed.gz\":[\"*\"],\"protocol_example.protein.missing.filtered.imputed.bed.gz\":[\"*\"],\"protocol_example.protein.missing.EBMF.imputed.bed.gz\":[\"*\"],\"protocol_example.protein.missing.knn.imputed.bed.gz\":[\"*\"],\"protocol_example.protein.missing.mean.imputed.bed.gz\":[\"*\"],\"protocol_example.protein.missing.lod.imputed.bed.gz\":[\"*\"],\"protocol_example.protein.missing.soft.imputed.bed.gz\":[\"*\"]},\"covariate_hidden_factor\":{\"covariates.tsv\":[\"*\"],\"residual.bed.gz\":[\"*\"],\"Marchenko_PC.gz\":[\"*\"],\"Buja_Eyuboglu_PC.gz\":[\"*\"],\"PEER.factors.tsv\":[\"*\"],\"PEER.weights.tsv\":[\"*\"],\"PEER.variance.tsv\":[\"*\"],\"PEER.gz\":[\"*\"]},\"gene_annotation\":{\"protocol_example.atac.tsv\":[\"*\"],\"protocol_example.rnaseq.bed.gz\":[\"*\"],\"protocol_example.rnaseq.bed.bed.gz\":[\"*\"],\"protocol_example.rnaseq.bed.gene_list.tsv\":[\"*\"],\"protocol_example.rnaseq.bed.region_list.txt\":[\"*\"],\"protocol_example.protein.no_coord.bed.gz\":[\"*\"],\"protocol_example.protein.no_coord.gene_list.tsv\":[\"*\"],\"protocol_example.protein.no_coord.region_list.txt\":[\"*\"],\"protocol_example.atac.bed.gz\":[\"*\"],\"protocol_example.atac.region_list.txt\":[\"*\"],\"protocol_example.leafcutter.intron_count.tsv.leafcutter.clusters_to_genes.txt\":[\"*\"],\"protocol_example.leafcutter.phenotype.bed.formated.bed.gz\":[\"*\"],\"protocol_example.leafcutter.phenotype.bed.phenotype_group.txt\":[\"*\"],\"protocol_example.psichomics.phenotype.formated.bed.gz\":[\"*\"],\"protocol_example.psichomics.phenotype.phenotype_group.txt\":[\"*\"]},\"mnm_regression\":{\"univariate_bvsr.rds\":[\"*\"],\"univariate_twas_weights.rds\":[\"*\"],\"protocol_example.genotype.chr22.bed\":[\"*\"],\"protocol_example.pheno_manifest_context.tsv\":[\"*\"],\"example_covariates.tsv\":[\"*\"],\"association_windows.bed\":[\"*\"],\"protocol_example.ENSG00000283047.multicontext_bvsr.rds\":[\"*\"]},\"colocboost\":{\"protocol_example.genotype.chr22.bed\":[\"*\"],\"protocol_example.pheno_manifest_context.tsv\":[\"*\"],\"example_covariates.tsv\":[\"*\"],\"association_windows.bed\":[\"*\"],\"test_coloc.ENSG00000283047.colocboost.rds\":[\"*\"]},\"mash_posterior\":{\"region_strong.rds\":[\"*\"],\"fine_mapping.rds\":[\"*\"],\"orig.rds\":[\"*\"],\"posterior.rds\":[\"*\"]},\"ld_prune_reference\":{\"protocol_example.ld_genotype.chr22.bed\":[\"*\"],\"protocol_example.ld_genotype.list\":[\"*\"],\"LD_pruned_variants.txt\":[\"*\"],\"protocol_example.ld_genotype.chr22.bim\":[\"*\"],\"protocol_example.ld_genotype.chr22.fam\":[\"*\"]},\"rss_ld_sketch\":{\"protocol_example.genotype.chr22.vcf.gz\":[\"*\"],\"protocol_example.ld_blocks.bed\":[\"*\"],\"afreq_deterministic.tsv\":[\"*\"],\"event_id.tsv\":[\"*\"],\"protocol_example.genotype.chr22.vcf.gz.tbi\":[\"*\"]},\"snRNAseq_preprocessing\":{\"protocol_example.snrnaseq.id_mapping.csv\":[\"*\"],\"protocol_example.snrnaseq.seurat_ref_SE.rds\":[\"*\"],\"expected_manifest.tsv\":[\"*\"]},\"RNA_calling\":{\"protocol_example.rnaseq.fastq.list.txt\":[\"*\"],\"adapters.fa\":[\"*\"],\"SAMPLE_001.strand.txt\":[\"*\"],\"fastq.list.trimmed.txt\":[\"*\"],\"rnaseqc.rnaseqc.exon_readsCount.gct.gz\":[\"*\"],\"rnaseqc.rnaseqc.gene_readsCount.gct.gz\":[\"*\"],\"rnaseqc.rnaseqc.gene_tpm.gct.gz\":[\"*\"],\"rnaseqc.rnaseqc.metrics.tsv\":[\"*\"],\"SAMPLE_001.rnaseqc.metrics.tsv\":[\"*\"],\"SAMPLE_002.rnaseqc.metrics.tsv\":[\"*\"]},\"apa_calling\":{\"chr22_3UTR.bed\":[\"*\"],\"expected_3UTR.bed\":[\"*\"],\"expected_gene_annotation.bed\":[\"*\"],\"protocol_example.expected_3UTR.bed\":[\"*\"],\"protocol_example.expected_gene_annotation.bed\":[\"*\"],\"chr22.hdr.gtf.gz\":[\"*\"],\"expected_pdui_data.txt\":[\"*\"],\"expected_transcript_to_geneName.txt\":[\"*\"],\"depth.txt\":[\"*\"]},\"methylation_calling\":{\"protocol_example.methylation.sample_sheet_int.csv\":[\"*\"],\"protocol_example.methylation.sample_sheet_int.sesame.beta.bed.gz\":[\"*\"],\"protocol_example.methylation.sample_sheet_int.sesame.M.bed.gz\":[\"*\"],\"protocol_example.methylation.sample_sheet_int.sesame.gene_id.annot.tsv\":[\"*\"],\"protocol_example.methylation.sample_sheet_int.sample_qcs.sesame.tsv\":[\"*\"]},\"GWAS_QC\":{\"protocol_example.pheno.bed\":[\"*\"],\"protocol_example.kin0\":[\"*\"],\"king.kin0\":[\"*\"],\"king_2.related_id\":[\"*\"],\"king_split.unrelated.fam\":[\"*\"],\"king_split.related.fam\":[\"*\"],\"qc_no_prune.bim\":[\"*\"],\"qc_ld_prune.prune.in\":[\"*\"],\"qc_ld_prune.bim\":[\"*\"],\"sample_overlap.txt\":[\"*\"],\"king_workflow.unrelated.fam\":[\"*\"]},\"PCA\":{\"protocol_example.pca_pheno.txt\":[\"*\"],\"protocol_example.unrelated.prune.bed\":[\"*\"],\"project_samples.rds\":[\"*\"],\"detect_outliers.maha.rds\":[\"*\"],\"detect_outliers.outliers.txt\":[\"*\"],\"pca_plink.eigenvec\":[\"*\"],\"flashpca.eigenvalues.tsv\":[\"*\"]},\"SuSiE_enloc\":{\"protocol_example.enloc.gwas_meta.tsv\":[\"*\"],\"protocol_example.enloc.xqtl_meta.tsv\":[\"*\"],\"coloc.rds\":[\"*\"],\"colocboost.rds\":[\"*\"],\"colocboost_manifest.tsv\":[\"*\"],\"enloc_manifest.enrichment.tsv\":[\"*\"],\"enloc_manifest.coloc.tsv\":[\"*\"]},\"VCF_QC\":{\"numeric_chr22.vcf.gz\":[\"*\"],\"genotype.chr22_48M.vcf.gz\":[\"*\"],\"rename_chrs.variants.tsv\":[\"*\"],\"qc_normalize.variants.tsv\":[\"*\"],\"qc_2.variants.tsv\":[\"*\"],\"qc_3.novel.tstv\":[\"*\"],\"qc_3.known.tstv\":[\"*\"]},\"apa_impute\":{\"protocol_example.apa_matchtable.txt\":[\"*\"],\"Dapars_result_result_temp.chr22.txt\":[\"*\"],\"expected.Dapars_result_impute_chr22.bed\":[\"*\"],\"expected.Dapars_allchrom.bed\":[\"*\"],\"expected.Dapars_result_impute_renamed_chr22.bed.gz\":[\"*\"],\"expected.Dapars_allchrom_renamed.bed\":[\"*\"]},\"bulk_expression_normalization\":{\"protocol_example.rnaseq.tpm.gct.gz\":[\"*\"],\"protocol_example.rnaseq.geneCount.gct.gz\":[\"*\"],\"protocol_example.rnaseq.sample_participant_lookup.txt\":[\"*\"],\"expected.qc_1.low_expression_filtered.tpm.gct.gz\":[\"*\"],\"expected.qc_2.outlier_removed.tpm.gct.gz\":[\"*\"],\"expected.qc_3.outlier_removed.geneCount.gct.gz\":[\"*\"]},\"covariate_formatting\":{\"covariates.base.tsv\":[\"*\"],\"merged.gz\":[\"*\"]},\"ems_prediction\":{\"protocol_example.gnomad_MAF_chr1.tsv\":[\"*\"],\"protocol_example.gnomad_MAF_chr2.tsv\":[\"*\"],\"model_config.yaml\":[\"*\"],\"features_importance_model5_chr_chr2_NPR_1.csv\":[\"*\"],\"model_5_summary_chr_chr2_NPR_1.json\":[\"*\"],\"predictions_weighted_model_chr2.tsv\":[\"*\"]},\"ems_training\":{\"protocol_example.gnomad_MAF_chr1.tsv\":[\"*\"],\"protocol_example.gnomad_MAF_chr2.tsv\":[\"*\"],\"model_config.yaml\":[\"*\"],\"features_importance_model5_chr_chr2_NPR_1.csv\":[\"*\"],\"model_5_summary_chr_chr2_NPR_1.json\":[\"*\"],\"predictions_weighted_model_chr2.tsv\":[\"*\"]},\"eoo_enrichment\":{\"protocol_example.eoo_baseline_annotation.tsv.gz\":[\"*\"],\"protocol_example.eoo_significant_variants.tsv.gz\":[\"*\"],\"enrichment_results.rds\":[\"*\"],\"enrichment_results_summary.tsv.gz\":[\"*\"]},\"generalized_TADB\":{\"protocol_example.brain_TADs.txt\":[\"*\"],\"protocol_example.gene_start_end.tsv\":[\"*\"],\"generalized_TAD.tsv\":[\"*\"],\"generalized_TADB.tsv\":[\"*\"],\"TADB_enhanced_cis.bed\":[\"*\"],\"extended_TADB.bed\":[\"*\"]},\"genotype_formatting\":{\"chr21.bed\":[\"*\"],\"chr21.bim\":[\"*\"],\"ld_by_region.float16.rds\":[\"*\"],\"plink_to_vcf.variants.tsv\":[\"*\"],\"vcf_to_plink.bim\":[\"*\"],\"genotype_by_region.bim\":[\"*\"],\"genotype_by_chrom.bim\":[\"*\"]},\"gregor\":{\"index.snps.txt\":[\"*\"],\"test_peaks.bed\":[\"*\"],\"example_enrichment_results.txt\":[\"*\"],\"enrichment_results.txt\":[\"*\"]},\"gsea\":{\"protocol_example.pathway_genes.tsv\":[\"*\"],\"pathway_go_results.rds\":[\"*\"]},\"intact\":{\"README.md\":[\"*\"],\"protocol_example.ptwas.output\":[\"*\"],\"intact.rds\":[\"*\"]},\"mash_fit\":{\"mashr_input.rds\":[\"*\"],\"region_strong.rds\":[\"*\"],\"Ast_De_Jager_eQTL.tsv\":[\"*\"],\"mash_model.EE.rds\":[\"*\"]},\"mash_preprocessing\":{\"mashr_input.rds\":[\"*\"],\"region_strong.rds\":[\"*\"],\"Ast_De_Jager_eQTL.tsv\":[\"*\"],\"mash_sumstats.region1.rds\":[\"*\"],\"mash_input.qss.rds\":[\"*\"],\"mash_input.fmr.rds\":[\"*\"],\"mash_input.indep.rds\":[\"*\"]},\"phenotype_formatting\":{\"regions.txt\":[\"*\"],\"tad_list.txt\":[\"*\"],\"keep_samples.txt\":[\"*\"],\"protocol_example.chr22.bed.gz\":[\"*\"],\"protocol_example.phenotype_by_chrom_files.txt\":[\"*\"],\"protocol_example.phenotype_by_chrom_files.region_list.txt\":[\"*\"],\"protocol_example.region1.bed.gz\":[\"*\"],\"protocol_example.region2.bed.gz\":[\"*\"],\"protocol_example.phenotype_by_region_files.txt\":[\"*\"],\"protocol_example.tpm.sample_matched.gct.gz\":[\"*\"],\"protocol_example.rnaseq.bed.bed.gz.tad_list.txt.2_pheno_per_region.region_list\":[\"*\"],\"protocol_example.chr22.gct\":[\"*\"]},\"pseudobulk_preprocessing\":{\"protocol_example.snrnaseq.seurat_MIC.rds\":[\"*\"],\"counts_MIC.csv.gz\":[\"*\"],\"atac_MIC_residuals.txt\":[\"*\"],\"expected_counts_MIC.remapped.csv.gz\":[\"*\"],\"expected_MIC_residuals_qn.txt\":[\"*\"]},\"qtl_association_postprocessing\":{\"protocol_example.cis_qtl.pairs.tsv.gz\":[\"*\"],\"protocol_example.cis_qtl.regional.tsv.gz\":[\"*\"],\"protocol_example.maf_0.01_window_1000000_cis_n_variants_stats.tsv.gz\":[\"*\"],\"qap.rds\":[\"*\"],\"qap.cis_regional.fdr.tsv.gz\":[\"*\"],\"qap.summary.tsv\":[\"*\"]},\"reference_data_preparation\":{\"hgnc_chr22.tsv.gz\":[\"*\"],\"mini.gff3\":[\"*\"],\"ERCC92.gtf\":[\"*\"],\"hg_reference_1.filtered.fasta\":[\"*\"],\"hg_gtf_1.reformatted.gtf\":[\"*\"],\"faidx.test_contigs.fa.fai\":[\"*\"],\"mini.gtf\":[\"*\"],\"hg38.chr22_SE_strict.ioe\":[\"*\"],\"chr22.SUPPA_annotation.rds\":[\"*\"]},\"rss_analysis\":{\"protocol_example.rss_mwe.gwas_meta.tsv\":[\"*\"],\"protocol_example.gwas_sumstats.chr22.tsv.gz\":[\"*\"],\"protocol_example.gwas_column_mapping.yml\":[\"*\"],\"gwas_sumstats.rds\":[\"*\"],\"gwas_finemap.rds\":[\"*\"]},\"sldsc_enrichment\":{\"target.tsv\":[\"*\"],\"reference.2.bed\":[\"*\"],\"reference.2.bim\":[\"*\"],\"sldsc_postprocess.rds\":[\"*\"],\"sldsc_meta_subset.rds\":[\"*\"],\"sldsc_meta_subset.notebook.rds\":[\"*\"]},\"splicing_calling\":{\"SAMPLE_001.junc.gz\":[\"*\"],\"SAMPLE_002.junc.gz\":[\"*\"],\"expected_junctions.txt\":[\"*\"]},\"splicing_normalization\":{\"raw_data.txt.gz\":[\"*\"],\"psi_raw_data.tsv.gz\":[\"*\"],\"expected.phen_chr22.gz\":[\"*\"],\"expected.prepare_phenotype.ave\":[\"*\"],\"expected.prepare_phenotype.phenotype_file_list.txt\":[\"*\"]},\"twas_ctwas\":{\"protocol_example.twas.gwas_meta.tsv\":[\"*\"],\"protocol_example.twas.xqtl_meta.tsv\":[\"*\"],\"gwas_sumstats.chr22.rds\":[\"*\"],\"twas.chr22.rds\":[\"*\"]},\"TensorQTL\":{\"protocol_example.genotype.chr22.bed\":[\"*\"],\"protocol_example.genotype.chr22.bim\":[\"*\"],\"protocol_example.genotype.chr22.fam\":[\"*\"],\"example_geneexpr.bed.gz\":[\"*\"],\"example_covariates.tsv\":[\"*\"],\"association_windows.bed\":[\"*\"],\"cis_qtl.pairs.tsv.gz\":[\"*\"],\"cis_qtl.regional.tsv.gz\":[\"*\"]},\"bulk_expression_QC\":{\"protocol_example.rnaseq.tpm.gct.gz\":[\"*\"],\"protocol_example.rnaseq.geneCount.gct.gz\":[\"*\"],\"protocol_example.rnaseq.sample_participant_lookup.txt\":[\"*\"],\"expected.qc_1.low_expression_filtered.tpm.gct.gz\":[\"*\"],\"expected.qc_2.outlier_removed.tpm.gct.gz\":[\"*\"],\"expected.qc_3.outlier_removed.geneCount.gct.gz\":[\"*\"]}};\n",
"const TERMNOTES={\"reference_data_preparation\":[[\"Reference genome build\",\"The coordinate system and allele reference used to align genotype, annotation, and molecular phenotype data.\"],[\"Gene annotation\",\"A catalog that links genomic intervals to genes, transcripts, and other functional features.\"]],\"generalized_TADB\":[[\"Topologically associating domain (TAD)\",\"A genomic region whose DNA sequences interact with one another more often than with sequences outside the region.\"],[\"Regulatory domain\",\"The genomic neighborhood in which variants are considered capable of regulating a molecular feature.\"]],\"ld_prune_reference\":[[\"Linkage disequilibrium (LD)\",\"Correlation between alleles at nearby variants caused by their shared inheritance.\"],[\"LD pruning\",\"Selection of a comparatively independent subset of variants by removing highly correlated markers.\"]],\"rss_ld_sketch\":[[\"LD matrix\",\"A matrix of correlations among variants in a genomic region.\"],[\"Summary-statistics fine-mapping\",\"Inference of causal variants from association statistics and an external LD reference rather than individual-level genotypes.\"]],\"RNA_calling\":[[\"Read alignment\",\"Placement of sequencing reads onto a reference genome or transcriptome.\"],[\"Gene-level count\",\"The number of aligned fragments assigned to a gene, used as a measure of RNA abundance.\"]],\"bulk_expression_QC\":[[\"Expression quality control\",\"Detection of samples or genes whose sequencing, mapping, or abundance profiles are inconsistent with the study population.\"],[\"Outlier sample\",\"A sample whose molecular profile differs unusually from the rest and may reflect technical failure or biological heterogeneity.\"]],\"bulk_expression_normalization\":[[\"Library-size normalization\",\"Adjustment for differences in sequencing depth and RNA composition across samples.\"],[\"Inverse-normal transformation\",\"A rank-based transformation that maps a phenotype to an approximately normal distribution.\"]],\"snRNAseq_preprocessing\":[[\"Single-nucleus RNA sequencing\",\"Measurement of RNA abundance in individual nuclei, often used for frozen tissue.\"],[\"Cell type\",\"A biologically defined class of cells or nuclei identified from characteristic expression patterns.\"]],\"pseudobulk_preprocessing\":[[\"Pseudobulk expression\",\"Counts aggregated across cells of the same donor and cell type to create a donor-level molecular phenotype.\"],[\"Donor\",\"The individual from whom molecular measurements and genotypes were obtained.\"]],\"splicing_calling\":[[\"Splice junction\",\"A boundary formed when an intron is removed and two exons are joined.\"],[\"Intron excision\",\"Removal of an intron from a precursor RNA molecule during splicing.\"]],\"splicing_normalization\":[[\"Intron excision ratio\",\"The relative usage of a splice junction or intron within its local cluster.\"],[\"Alternative splicing\",\"Production of different RNA isoforms through differential exon or splice-junction use.\"]],\"methylation_calling\":[[\"DNA methylation\",\"Addition of a methyl group to DNA, commonly measured at CpG sites as an epigenetic regulatory mark.\"],[\"Beta value\",\"The estimated fraction of methylated signal at a CpG probe.\"]],\"apa_calling\":[[\"Alternative polyadenylation\",\"Use of different transcript cleavage and polyadenylation sites, which changes the RNA 3-prime end.\"],[\"Polyadenylation site\",\"The transcript position at which RNA is cleaved before addition of the poly(A) tail.\"]],\"apa_impute\":[[\"Imputation\",\"Estimation of missing molecular measurements from patterns observed across features and samples.\"],[\"Missingness\",\"The pattern and proportion of unavailable measurements in a molecular phenotype matrix.\"]],\"VCF_QC\":[[\"Minor allele frequency (MAF)\",\"The frequency of the less common allele at a variant in the analyzed sample.\"],[\"Hardy-Weinberg equilibrium\",\"The expected genotype-frequency relationship under random mating, used as one signal of genotype quality.\"]],\"genotype_formatting\":[[\"Allele harmonization\",\"Alignment of variant identifiers, reference alleles, alternate alleles, and strand orientation across datasets.\"],[\"Dosage\",\"The expected number of alternate alleles carried by an individual, often ranging continuously from zero to two after imputation.\"]],\"GWAS_QC\":[[\"Genome-wide association study (GWAS)\",\"A scan for genetic variants associated with a complex trait or disease.\"],[\"Genomic inflation\",\"Systematic excess of association signal that can reflect confounding, relatedness, or polygenicity.\"]],\"PCA\":[[\"Population structure\",\"Systematic genetic differences among ancestry groups or subpopulations.\"],[\"Genotype principal component\",\"A major axis of genetic variation used to adjust association analyses for population structure.\"]],\"gene_annotation\":[[\"Transcription start site (TSS)\",\"The genomic position where transcription of a gene begins.\"],[\"Gene model\",\"The annotated genomic structure of a gene, including its exons, transcripts, and strand.\"]],\"phenotype_imputation\":[[\"Phenotype imputation\",\"Estimation of missing molecular phenotype values using information shared across samples or features.\"],[\"Limit of detection\",\"The smallest abundance that an assay can distinguish reliably from background.\"]],\"phenotype_formatting\":[[\"Molecular phenotype\",\"A quantitative molecular trait such as gene expression, splicing, methylation, or protein abundance.\"],[\"Genomic interval\",\"A chromosome, start, and end coordinate used to locate a molecular feature.\"]],\"covariate_formatting\":[[\"Covariate\",\"A measured variable included in a model to account for known biological or technical variation.\"],[\"Design matrix\",\"A numeric representation of model covariates across samples.\"]],\"covariate_hidden_factor\":[[\"Hidden factor\",\"An unmeasured source of variation, such as cell composition, technical batch, or RNA quality, inferred from the molecular phenotype matrix.\"],[\"Confounding\",\"Distortion of a genetic association by a variable related to both the tested genotype and molecular phenotype.\"]],\"TensorQTL\":[[\"xQTL\",\"A genetic variant associated with variation in a molecular phenotype such as expression, splicing, methylation, or protein abundance.\"],[\"cis association\",\"An association between a variant and a nearby molecular feature within a defined genomic window.\"],[\"False discovery rate (FDR)\",\"The expected proportion of false positives among results declared significant.\"]],\"qr_and_twas\":[[\"Quantile regression\",\"A model that estimates genetic effects at selected points of a phenotype distribution rather than only its mean.\"],[\"TWAS weight\",\"An estimated genetic effect used to predict a molecular trait from local variants.\"]],\"qtl_association_postprocessing\":[[\"Lead variant\",\"The variant with the strongest association signal for a molecular feature or region.\"],[\"Allelic effect\",\"The direction and magnitude of phenotype change associated with an allele.\"]],\"METAL\":[[\"Meta-analysis\",\"Statistical combination of association evidence across cohorts while allowing each cohort to retain its own participants.\"],[\"Heterogeneity\",\"Variation in estimated genetic effects across cohorts or studies.\"]],\"mash_preprocessing\":[[\"Effect-size matrix\",\"A matrix of association estimates arranged across variants or genes and biological conditions.\"],[\"Standard error\",\"The estimated uncertainty of an effect-size estimate.\"]],\"mixture_prior\":[[\"Covariance prior\",\"A learned representation of how genetic effects tend to be shared across tissues, cell types, or molecular traits.\"],[\"Residual correlation\",\"Correlation among association estimates that remains after accounting for true shared effects.\"]],\"mash_fit\":[[\"Empirical Bayes\",\"A framework that estimates a prior distribution from the observed data and uses it to update noisy effects.\"],[\"Shrinkage\",\"Pulling uncertain effect estimates toward patterns supported by the full dataset.\"],[\"Local false sign rate\",\"The posterior probability that the reported direction of an effect is wrong.\"]],\"mash_posterior\":[[\"Posterior distribution\",\"The updated probability distribution of an effect after combining the observed data with the fitted prior.\"],[\"Posterior contrast\",\"A probabilistic comparison of effects between biological conditions.\"]],\"mnm_regression\":[[\"Fine-mapping\",\"Prioritization of variants that may causally explain an association signal.\"],[\"Posterior inclusion probability (PIP)\",\"The posterior probability that a variant contributes to the genetic signal in the fitted model.\"],[\"Credible set\",\"A group of variants that jointly contains a causal regulatory variant with a stated posterior probability under the fitted model.\"]],\"rss_analysis\":[[\"Fine-mapping\",\"Prioritization of variants that may causally explain an association signal.\"],[\"Posterior inclusion probability (PIP)\",\"The posterior probability that a variant contributes to the genetic signal in the fitted model.\"],[\"Credible set\",\"A group of variants that jointly contains a causal regulatory variant with a stated posterior probability under the fitted model.\"]],\"SuSiE_enloc\":[[\"Colocalization\",\"Evidence that molecular-trait and complex-trait associations in a region are explained by the same underlying genetic signal.\"],[\"Regional enrichment\",\"Increased probability that a trait-associated region also contains a molecular QTL signal.\"]],\"twas_ctwas\":[[\"Transcriptome-wide association study (TWAS)\",\"A test relating genetically predicted molecular phenotypes to a complex trait.\"],[\"Mediated association\",\"A trait association consistent with a genetic effect acting through a measured molecular phenotype.\"]],\"colocboost\":[[\"Colocalization\",\"Evidence that molecular-trait and complex-trait associations in a region are explained by the same underlying genetic signal.\"],[\"Multiple causal signals\",\"More than one distinct causal association pattern within the same genomic region.\"]],\"intact\":[[\"Colocalization\",\"Evidence that molecular-trait and complex-trait associations in a region are explained by the same underlying genetic signal.\"],[\"Cross-tissue evidence\",\"Association information combined across tissues or molecular contexts.\"]],\"watershed\":[[\"Variant-to-gene prioritization\",\"Ranking variants by evidence that they regulate a particular gene and contribute to disease risk.\"],[\"Functional annotation\",\"Biological information about a variant or genomic region used to interpret its potential mechanism.\"]],\"eoo_enrichment\":[[\"Enrichment\",\"An excess of overlap between two sets of genomic signals relative to an appropriate null expectation.\"],[\"Observed-to-expected ratio\",\"The observed overlap divided by the overlap expected under a null model.\"]],\"gsea\":[[\"Gene set enrichment analysis (GSEA)\",\"A test for coordinated concentration of association evidence within a predefined group of genes.\"],[\"Gene set\",\"A collection of genes sharing a pathway, function, annotation, or experimental signature.\"]],\"gregor\":[[\"Regulatory enrichment\",\"Overrepresentation of associated variants in regulatory annotations compared with matched control variants.\"],[\"Matched control variant\",\"A background variant selected to resemble an associated variant in properties such as allele frequency and LD.\"]],\"sldsc_enrichment\":[[\"Stratified LD score regression (S-LDSC)\",\"A method that partitions SNP heritability across genomic annotations using GWAS summary statistics and LD.\"],[\"SNP heritability\",\"The proportion of trait variation attributable to the additive effects of measured or tagged variants.\"]],\"ems_training\":[[\"Expression modifier score (EMS)\",\"A learned score estimating the probability that a variant has a regulatory effect on a gene.\"],[\"Training label\",\"An observed outcome used to teach a predictive model which genomic patterns distinguish regulatory variants.\"]],\"ems_prediction\":[[\"Expression modifier score (EMS)\",\"A learned score estimating the probability that a variant has a regulatory effect on a gene.\"],[\"Calibration\",\"Agreement between predicted probabilities and the observed frequency of the corresponding outcome.\"]]};\n",
"function open(btn){curBtn=btn;\n",
" const nb=btn.closest('.mw').dataset.nb; cur=nb; initM(nb);\n",