diff --git a/reference/gtexr_arguments.html b/reference/gtexr_arguments.html
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+++ b/reference/gtexr_arguments.html
@@ -35,7 +35,7 @@
diff --git a/search.json b/search.json
index a742af7..d06f53d 100644
--- a/search.json
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@@ -1 +1 @@
-[{"path":"https://rmgpanw.github.io/gtexr/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 gtexr authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://rmgpanw.github.io/gtexr/articles/developer_guide.html","id":"functions","dir":"Articles","previous_headings":"","what":"Functions","title":"Developer guide","text":"Function name title API endpoint lower case, words separated underscores. @description section copied verbatim API documentation site ends link corresponding API endpoint documentation. notes may added @details. Names match API endpoint, except argument accepts array (vector R) values, case pluralised.1 Default values also match API endpoint. Query parameters flagged “required” GTEx Portal API documentation default values.2 documented gtexr_arguments.R. functions therefore use @inheritParams gtexr_arguments documentation. Use @family roxygen tag match categories API documentation. used categorise functions pkgdown site reference page. Return tibble. first example @examples must produce output single function call without assignment (e.g. get_news_items(), x <- get_news_items()). used pre-populate argument values gtexr shiny app working example. examples surrounded \\dontrun{}.","code":""},{"path":"https://rmgpanw.github.io/gtexr/articles/gtexr.html","id":"shiny-app","dir":"Articles","previous_headings":"","what":"Shiny app","title":"Introduction to gtexr","text":"Users can try functions interatively ⭐gtexr shiny app⭐, pre-populates query parameters first working example function’s documentation.","code":""},{"path":"https://rmgpanw.github.io/gtexr/articles/gtexr.html","id":"examples","dir":"Articles","previous_headings":"","what":"Examples","title":"Introduction to gtexr","text":"rest vignette outlines example applications gtexr.","code":"library(gtexr) library(dplyr) library(purrr)"},{"path":"https://rmgpanw.github.io/gtexr/articles/gtexr.html","id":"get-build-37-coordinates-for-a-variant","dir":"Articles","previous_headings":"Examples","what":"Get build 37 coordinates for a variant","title":"Introduction to gtexr","text":"","code":"get_variant(snpId = \"rs1410858\") |> tidyr::separate( col = b37VariantId, into = c( \"chromosome\", \"position\", \"reference_allele\", \"alternative_allele\", \"genome_build\" ), sep = \"_\", remove = FALSE ) |> select(snpId:genome_build) #> #> ── Paging info ───────────────────────────────────────────────────────────────── #> • numberOfPages = 1 #> • page = 0 #> • maxItemsPerPage = 250 #> • totalNumberOfItems = 1 #> # A tibble: 1 × 7 #> snpId b37VariantId chromosome position reference_allele alternative_allele #> #> 1 rs1410858 1_153182116… 1 1531821… C A #> # ℹ 1 more variable: genome_build "},{"path":"https://rmgpanw.github.io/gtexr/articles/gtexr.html","id":"convert-gene-symbol-to-versioned-gencode-id","dir":"Articles","previous_headings":"Examples","what":"Convert gene symbol to versioned GENCODE ID","title":"Introduction to gtexr","text":"Use get_gene() get_genes()","code":"get_genes(\"CRP\") |> select(geneSymbol, gencodeId) #> #> ── Paging info ───────────────────────────────────────────────────────────────── #> • numberOfPages = 1 #> • page = 0 #> • maxItemsPerPage = 250 #> • totalNumberOfItems = 1 #> # A tibble: 1 × 2 #> geneSymbol gencodeId #> #> 1 CRP ENSG00000132693.12"},{"path":"https://rmgpanw.github.io/gtexr/articles/gtexr.html","id":"convert-rsid-to-gtex-variant-id","dir":"Articles","previous_headings":"Examples","what":"Convert rsID to GTEx variant ID","title":"Introduction to gtexr","text":"Use get_variant()","code":"get_variant(snpId = \"rs1410858\") |> select(snpId, variantId) #> #> ── Paging info ───────────────────────────────────────────────────────────────── #> • numberOfPages = 1 #> • page = 0 #> • maxItemsPerPage = 250 #> • totalNumberOfItems = 1 #> # A tibble: 1 × 2 #> snpId variantId #> #> 1 rs1410858 chr1_153209640_C_A_b38"},{"path":"https://rmgpanw.github.io/gtexr/articles/gtexr.html","id":"for-a-gene-of-interest-which-tissues-have-significant-cis-eqtls","dir":"Articles","previous_headings":"Examples","what":"For a gene of interest, which tissues have significant cis-eQTLs?","title":"Introduction to gtexr","text":"Use get_significant_single_tissue_eqtls() (note requires versioned GENCODE IDs)","code":"gene_symbol_of_interest <- \"CRP\" gene_gencodeId_of_interest <- get_genes(gene_symbol_of_interest) |> pull(gencodeId) |> suppressMessages() gene_gencodeId_of_interest |> get_significant_single_tissue_eqtls() |> distinct(geneSymbol, gencodeId, tissueSiteDetailId) #> #> ── Paging info ───────────────────────────────────────────────────────────────── #> • numberOfPages = 1 #> • page = 0 #> • maxItemsPerPage = 250 #> • totalNumberOfItems = 93 #> # A tibble: 3 × 3 #> geneSymbol gencodeId tissueSiteDetailId #> #> 1 CRP ENSG00000132693.12 Thyroid #> 2 CRP ENSG00000132693.12 Esophagus_Gastroesophageal_Junction #> 3 CRP ENSG00000132693.12 Muscle_Skeletal"},{"path":"https://rmgpanw.github.io/gtexr/articles/gtexr.html","id":"get-data-for-non-eqtl-variants","dir":"Articles","previous_headings":"Examples","what":"Get data for non-eQTL variants","title":"Introduction to gtexr","text":"analyses (e.g. Mendelian randomisation) require data variants may may significant eQTLs. Use calculate_expression_quantitative_trait_loci() purrr::map() retrieve data multiple variants","code":"variants_of_interest <- c(\"rs12119111\", \"rs6605071\", \"rs1053870\") variants_of_interest |> set_names() |> map( \\(x) calculate_expression_quantitative_trait_loci( tissueSiteDetailId = \"Liver\", gencodeId = \"ENSG00000237973.1\", variantId = x ) ) |> bind_rows(.id = \"rsid\") |> # optionally, reformat output - first extract genomic coordinates and alleles tidyr::separate( col = \"variantId\", into = c( \"chromosome\", \"position\", \"reference_allele\", \"alternative_allele\", \"genome_build\" ), sep = \"_\" ) |> # ...then ascertain alternative_allele frequency mutate( alt_allele_count = (2 * homoAltCount) + hetCount, total_allele_count = 2 * (homoAltCount + hetCount + homoRefCount), alternative_allele_frequency = alt_allele_count / total_allele_count ) |> select( rsid, beta = nes, se = error, pValue, minor_allele_frequency = maf, alternative_allele_frequency, chromosome:genome_build, tissueSiteDetailId ) #> # A tibble: 3 × 12 #> rsid beta se pValue minor_allele_frequency alternative_allele_f…¹ #> #> 1 rs121191… 0.0270 0.0670 6.88e-1 0.365 0.635 #> 2 rs6605071 -0.601 0.166 3.88e-4 0.0409 0.959 #> 3 rs1053870 0.0247 0.0738 7.38e-1 0.214 0.214 #> # ℹ abbreviated name: ¹alternative_allele_frequency #> # ℹ 6 more variables: chromosome , position , reference_allele , #> # alternative_allele , genome_build , tissueSiteDetailId "},{"path":"https://rmgpanw.github.io/gtexr/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Alasdair Warwick. Author, maintainer, copyright holder. Benjamin Zuckerman. Author. Abraham Olvera-Barrios. Author. Chuin Ying Ung. Author. Robert Luben. Author.","code":""},{"path":"https://rmgpanw.github.io/gtexr/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Warwick , Zuckerman B, Olvera-Barrios , Ung C, Luben R (2024). gtexr: Query GTEx Portal API. R package version 0.1.0.9000, https://github.com/rmgpanw/gtexr, https://rmgpanw.github.io/gtexr/.","code":"@Manual{, title = {gtexr: Query the GTEx Portal API}, author = {Alasdair Warwick and Benjamin Zuckerman and Abraham Olvera-Barrios and Chuin Ying Ung and Robert Luben}, year = {2024}, note = {R package version 0.1.0.9000, https://github.com/rmgpanw/gtexr}, url = {https://rmgpanw.github.io/gtexr/}, }"},{"path":"https://rmgpanw.github.io/gtexr/index.html","id":"gtexr-","dir":"","previous_headings":"","what":"Query the GTEx Portal API","title":"Query the GTEx Portal API","text":"goal gtexr provide convenient R interface GTEx Portal API V2. New R? Try ⭐shiny app⭐.","code":""},{"path":"https://rmgpanw.github.io/gtexr/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Query the GTEx Portal API","text":"can install package CRAN: can install development version gtexr GitHub :","code":"install.packages(\"gtexr\") # install.packages(\"devtools\") devtools::install_github(\"rmgpanw/gtexr\")"},{"path":"https://rmgpanw.github.io/gtexr/index.html","id":"examples","dir":"","previous_headings":"","what":"Examples","title":"Query the GTEx Portal API","text":"Get general information GTEx service: Retrieve eQTL genes whole blood tissue: Retrieve significant eQTLs one genes:","code":"library(gtexr) get_service_info() #> # A tibble: 1 × 9 #> id name version organization_name organization_url description contactUrl #> #> 1 org.g… GTEx… 2.0.0 GTEx Project https://gtexpor… This servi… https://g… #> # ℹ 2 more variables: documentationUrl , environment get_eqtl_genes(\"Whole_Blood\") #> Warning: ! Total number of items (12360) exceeds maximum page size (250). #> ℹ Try increasing `itemsPerPage`. #> #> ── Paging info ───────────────────────────────────────────────────────────────── #> • numberOfPages = 50 #> • page = 0 #> • maxItemsPerPage = 250 #> • totalNumberOfItems = 12360 #> # A tibble: 250 × 10 #> tissueSiteDetailId ontologyId datasetId empiricalPValue gencodeId geneSymbol #> #> 1 Whole_Blood UBERON:001… gtex_v8 1.05e- 9 ENSG0000… WASH7P #> 2 Whole_Blood UBERON:001… gtex_v8 1.06e-25 ENSG0000… RP11-34P1… #> 3 Whole_Blood UBERON:001… gtex_v8 6.31e- 2 ENSG0000… CICP27 #> 4 Whole_Blood UBERON:001… gtex_v8 8.71e- 9 ENSG0000… RP11-34P1… #> 5 Whole_Blood UBERON:001… gtex_v8 6.01e-20 ENSG0000… RP11-34P1… #> 6 Whole_Blood UBERON:001… gtex_v8 6.96e- 9 ENSG0000… RP11-34P1… #> 7 Whole_Blood UBERON:001… gtex_v8 3.10e- 4 ENSG0000… RP11-34P1… #> 8 Whole_Blood UBERON:001… gtex_v8 1.92e- 3 ENSG0000… ABC7-4304… #> 9 Whole_Blood UBERON:001… gtex_v8 1.58e- 3 ENSG0000… RP11-34P1… #> 10 Whole_Blood UBERON:001… gtex_v8 7.82e- 2 ENSG0000… AP006222.2 #> # ℹ 240 more rows #> # ℹ 4 more variables: log2AllelicFoldChange , pValue , #> # pValueThreshold , qValue get_significant_single_tissue_eqtls(gencodeId = c(\"ENSG00000132693.12\", \"ENSG00000203782.5\")) #> #> ── Paging info ───────────────────────────────────────────────────────────────── #> • numberOfPages = 1 #> • page = 0 #> • maxItemsPerPage = 250 #> • totalNumberOfItems = 249 #> # A tibble: 249 × 13 #> snpId pos snpIdUpper variantId geneSymbol pValue geneSymbolUpper #> #> 1 rs12128960 159343657 RS12128960 chr1_1593… CRP 8.52e-5 CRP #> 2 rs12132451 159344052 RS12132451 chr1_1593… CRP 7.92e-5 CRP #> 3 rs12136402 159347493 RS12136402 chr1_1593… CRP 7.92e-5 CRP #> 4 rs10908709 159350390 RS10908709 chr1_1593… CRP 7.92e-5 CRP #> 5 rs10908710 159351189 RS10908710 chr1_1593… CRP 7.92e-5 CRP #> 6 rs11265178 159359256 RS11265178 chr1_1593… CRP 9.62e-5 CRP #> 7 rs35532309 159360755 RS35532309 chr1_1593… CRP 6.11e-5 CRP #> 8 rs6692378 159369451 RS6692378 chr1_1593… CRP 1.17e-6 CRP #> 9 rs10908714 159370563 RS10908714 chr1_1593… CRP 1.80e-5 CRP #> 10 rs6656924 159372915 RS6656924 chr1_1593… CRP 1.00e-6 CRP #> # ℹ 239 more rows #> # ℹ 6 more variables: datasetId , tissueSiteDetailId , #> # ontologyId , chromosome , gencodeId , nes "},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_expression_quantitative_trait_loci.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Expression Quantitative Trait Loci — calculate_expression_quantitative_trait_loci","title":"Calculate Expression Quantitative Trait Loci — calculate_expression_quantitative_trait_loci","text":"Calculate eQTLs service calculates gene-variant association given pair gene variant, may may significant. requires input GENCODE ID, GTEx variant ID, tissue site detail ID. default, calculation based latest GTEx release. GTEx Portal API documentation.","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_expression_quantitative_trait_loci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Expression Quantitative Trait Loci — calculate_expression_quantitative_trait_loci","text":"","code":"calculate_expression_quantitative_trait_loci( tissueSiteDetailId, gencodeId, variantId, datasetId = \"gtex_v8\" )"},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_expression_quantitative_trait_loci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Expression Quantitative Trait Loci — calculate_expression_quantitative_trait_loci","text":"tissueSiteDetailId String. ID tissue interest. Can GTEx specific ID (e.g. \"Whole_Blood\"; use get_tissue_site_detail() see valid values) Ontology ID. gencodeId String. Versioned GENCODE ID gene, e.g. \"ENSG00000065613.9\". variantId String. gtex variant ID. datasetId String. Unique identifier dataset. Usually includes data source data release. Options: \"gtex_v8\", \"gtex_snrnaseq_pilot\".","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_expression_quantitative_trait_loci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Expression Quantitative Trait Loci — calculate_expression_quantitative_trait_loci","text":"tibble.","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_expression_quantitative_trait_loci.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate Expression Quantitative Trait Loci — calculate_expression_quantitative_trait_loci","text":"Notes output: Beta standard error recorded columns nes error respectively (see GTEx FAQs) variantId contains (order) chromosome, position, reference allele, alternative allele human genome build separated underscores. reference alternative alleles \"chr1_13550_G_A_b38\" example \"G\" \"\" respectively. See examples calculate minor alternative allele frequencies. Notes input: Argument variantId also accepts RSIDs.","code":""},{"path":[]},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_expression_quantitative_trait_loci.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Expression Quantitative Trait Loci — calculate_expression_quantitative_trait_loci","text":"","code":"# \\dontrun{ # perform request - returns a tibble with a single row calculate_expression_quantitative_trait_loci(tissueSiteDetailId = \"Whole_Blood\", gencodeId = \"ENSG00000203782.5\", variantId = \"rs79641866\") #> # A tibble: 1 × 15 #> data error gencodeId geneSymbol genotypes hetCount homoAltCount #> #> 1 0.148 ENSG00000… LOR 38 0 #> # ℹ 8 more variables: homoRefCount , maf , nes , pValue , #> # pValueThreshold , tStatistic , tissueSiteDetailId , #> # variantId # unnest list columns with tidyr::unnest() calculate_expression_quantitative_trait_loci(tissueSiteDetailId = \"Whole_Blood\", gencodeId = \"ENSG00000203782.5\", variantId = \"rs79641866\") |> tidyr::unnest(c(\"data\", \"genotypes\")) #> # A tibble: 670 × 15 #> data error gencodeId geneSymbol genotypes hetCount homoAltCount #> #> 1 -1.11 0.148 ENSG00000203782.5 LOR 0 38 0 #> 2 -1.21 0.148 ENSG00000203782.5 LOR 0 38 0 #> 3 -0.791 0.148 ENSG00000203782.5 LOR 0 38 0 #> 4 1.77 0.148 ENSG00000203782.5 LOR 0 38 0 #> 5 0.926 0.148 ENSG00000203782.5 LOR 0 38 0 #> 6 -0.148 0.148 ENSG00000203782.5 LOR 0 38 0 #> 7 2.75 0.148 ENSG00000203782.5 LOR 0 38 0 #> 8 0.848 0.148 ENSG00000203782.5 LOR 0 38 0 #> 9 0.816 0.148 ENSG00000203782.5 LOR 0 38 0 #> 10 -0.114 0.148 ENSG00000203782.5 LOR 1 38 0 #> # ℹ 660 more rows #> # ℹ 8 more variables: homoRefCount , maf , nes , pValue , #> # pValueThreshold , tStatistic , tissueSiteDetailId , #> # variantId # to calculate minor and alternative allele frequencies calculate_expression_quantitative_trait_loci( tissueSiteDetailId = \"Liver\", gencodeId = \"ENSG00000237973.1\", variantId = \"rs12119111\" ) |> dplyr::bind_rows(.id = \"rsid\") |> tidyr::separate( col = \"variantId\", into = c( \"chromosome\", \"position\", \"reference_allele\", \"alternative_allele\", \"genome_build\" ), sep = \"_\" ) |> # ...then ascertain alternative_allele frequency dplyr::mutate( alt_allele_count = (2 * homoAltCount) + hetCount, total_allele_count = 2 * (homoAltCount + hetCount + homoRefCount), alternative_allele_frequency = alt_allele_count / total_allele_count ) |> dplyr::select( rsid, beta = nes, se = error, pValue, minor_allele_frequency = maf, alternative_allele_frequency, chromosome:genome_build, tissueSiteDetailId ) #> # A tibble: 1 × 12 #> rsid beta se pValue minor_allele_frequency alternative_allele_frequency #> #> 1 1 0.0270 0.0670 0.688 0.365 0.635 #> # ℹ 6 more variables: chromosome , position , reference_allele , #> # alternative_allele , genome_build , tissueSiteDetailId # }"},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_ieqtls.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Ieqtls — calculate_ieqtls","title":"Calculate Ieqtls — calculate_ieqtls","text":"Calculate Cell Specific eQTLs. service calculates gene-variant association given pair gene variant, may may significant. requires input GENCODE ID, GTEx variant ID, tissue site detail ID. default, calculation based latest GTEx release. GTEx Portal API documentation.","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_ieqtls.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Ieqtls — calculate_ieqtls","text":"","code":"calculate_ieqtls( cellType, tissueSiteDetailId, gencodeId, variantId, datasetId = \"gtex_v8\" )"},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_ieqtls.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Ieqtls — calculate_ieqtls","text":"cellType String. \"Adipocytes\", \"Epithelial_cells\", \"Hepatocytes\", \"Keratinocytes\", \"Myocytes\", \"Neurons\", \"Neutrophils\". tissueSiteDetailId String. ID tissue interest. Can GTEx specific ID (e.g. \"Whole_Blood\"; use get_tissue_site_detail() see valid values) Ontology ID. gencodeId String. Versioned GENCODE ID gene, e.g. \"ENSG00000065613.9\". variantId String. gtex variant ID. datasetId String. Unique identifier dataset. Usually includes data source data release. Options: \"gtex_v8\", \"gtex_snrnaseq_pilot\".","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_ieqtls.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Ieqtls — calculate_ieqtls","text":"tibble.","code":""},{"path":[]},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_ieqtls.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Ieqtls — calculate_ieqtls","text":"","code":"# \\dontrun{ # perform request calculate_ieqtls(cellType = \"Adipocytes\", tissueSiteDetailId = \"Adipose_Subcutaneous\", gencodeId = \"ENSG00000203782.5\", variantId = \"chr1_1099341_T_C_b38\") #> # A tibble: 1 × 9 #> cellType data datasetId enrichmentScores gencodeId genotypes regressionCoord #> #> 1 Adipocyt… gtex_v8 ENSG0000… #> # ℹ 2 more variables: tissueSiteDetailId , variantId # }"},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_isqtls.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Isqtls — calculate_isqtls","title":"Calculate Isqtls — calculate_isqtls","text":"Calculate Cell Specific sQTLs. service calculates gene-variant association given pair gene variant, may may significant. requires input GENCODE ID, GTEx variant ID, tissue site detail ID. default, calculation based latest GTEx release. GTEx Portal API documentation.","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_isqtls.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Isqtls — calculate_isqtls","text":"","code":"calculate_isqtls( cellType, tissueSiteDetailId, phenotypeId, variantId, datasetId = \"gtex_v8\" )"},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_isqtls.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Isqtls — calculate_isqtls","text":"cellType String. \"Adipocytes\", \"Epithelial_cells\", \"Hepatocytes\", \"Keratinocytes\", \"Myocytes\", \"Neurons\", \"Neutrophils\". tissueSiteDetailId String. ID tissue interest. Can GTEx specific ID (e.g. \"Whole_Blood\"; use get_tissue_site_detail() see valid values) Ontology ID. phenotypeId String. See GTEx portal FAQs details. variantId String. gtex variant ID. datasetId String. Unique identifier dataset. Usually includes data source data release. Options: \"gtex_v8\", \"gtex_snrnaseq_pilot\".","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_isqtls.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Isqtls — calculate_isqtls","text":"tibble.","code":""},{"path":[]},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_isqtls.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Isqtls — calculate_isqtls","text":"","code":"# \\dontrun{ # perform request calculate_isqtls(cellType = \"Neutrophils\", tissueSiteDetailId = \"Whole_Blood\", phenotypeId = \"chr1:15947:16607:clu_40980:ENSG00000227232.5\", variantId = \"chr1_1099341_T_C_b38\") #> # A tibble: 1 × 9 #> cellType data datasetId enrichmentScores phenotypeId tissueSiteDetailId #> #> 1 Neutrophils gtex_v8 chr1:15947:1… Whole_Blood #> # ℹ 3 more variables: variantId , genotypes , regressionCoord # }"},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_splicing_quantitative_trait_loci.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Splicing Quantitative Trait Loci — calculate_splicing_quantitative_trait_loci","title":"Calculate Splicing Quantitative Trait Loci — calculate_splicing_quantitative_trait_loci","text":"GTEx Portal API documentation.","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_splicing_quantitative_trait_loci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Splicing Quantitative Trait Loci — calculate_splicing_quantitative_trait_loci","text":"","code":"calculate_splicing_quantitative_trait_loci( tissueSiteDetailId, phenotypeId, variantId, datasetId = \"gtex_v8\" )"},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_splicing_quantitative_trait_loci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Splicing Quantitative Trait Loci — calculate_splicing_quantitative_trait_loci","text":"tissueSiteDetailId String. ID tissue interest. Can GTEx specific ID (e.g. \"Whole_Blood\"; use get_tissue_site_detail() see valid values) Ontology ID. phenotypeId String. See GTEx portal FAQs details. variantId String. gtex variant ID. datasetId String. Unique identifier dataset. Usually includes data source data release. Options: \"gtex_v8\", \"gtex_snrnaseq_pilot\".","code":""},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_splicing_quantitative_trait_loci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Splicing Quantitative Trait Loci — calculate_splicing_quantitative_trait_loci","text":"tibble.","code":""},{"path":[]},{"path":"https://rmgpanw.github.io/gtexr/reference/calculate_splicing_quantitative_trait_loci.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Splicing Quantitative Trait Loci — calculate_splicing_quantitative_trait_loci","text":"","code":"# \\dontrun{ # perform request - returns a tibble with a single row calculate_splicing_quantitative_trait_loci( tissueSiteDetailId = \"Whole_Blood\", phenotypeId = \"chr1:15947:16607:clu_40980:ENSG00000227232.5\", variantId = \"chr1_14677_G_A_b38\") #> # A tibble: 1 × 14 #> data error genotypes hetCount homoAltCount homoRefCount maf nes #> #> 1 0.139 69 0 601 0.0515 0.757 #> # ℹ 6 more variables: pValue
