{"action":"closed","issue":{"url":"https://api.github.com/repos/mcanouil/NACHO/issues/10","repository_url":"https://api.github.com/repos/mcanouil/NACHO","labels_url":"https://api.github.com/repos/mcanouil/NACHO/issues/10/labels{/name}","comments_url":"https://api.github.com/repos/mcanouil/NACHO/issues/10/comments","events_url":"https://api.github.com/repos/mcanouil/NACHO/issues/10/events","html_url":"https://github.com/mcanouil/NACHO/issues/10","id":494493789,"node_id":"MDU6SXNzdWU0OTQ0OTM3ODk=","number":10,"title":"Changing housekeeping genes seems 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v0.6.0","description":null,"creator":{"login":"mcanouil","id":8896044,"node_id":"MDQ6VXNlcjg4OTYwNDQ=","avatar_url":"https://avatars0.githubusercontent.com/u/8896044?v=4","gravatar_id":"","url":"https://api.github.com/users/mcanouil","html_url":"https://github.com/mcanouil","followers_url":"https://api.github.com/users/mcanouil/followers","following_url":"https://api.github.com/users/mcanouil/following{/other_user}","gists_url":"https://api.github.com/users/mcanouil/gists{/gist_id}","starred_url":"https://api.github.com/users/mcanouil/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mcanouil/subscriptions","organizations_url":"https://api.github.com/users/mcanouil/orgs","repos_url":"https://api.github.com/users/mcanouil/repos","events_url":"https://api.github.com/users/mcanouil/events{/privacy}","received_events_url":"https://api.github.com/users/mcanouil/received_events","type":"User","site_admin":false},"open_issues":1,"closed_issues":5,"state":"open","created_at":"2019-07-03T10:34:05Z","updated_at":"2019-10-03T13:11:56Z","due_on":null,"closed_at":null},"comments":1,"created_at":"2019-09-17T09:00:46Z","updated_at":"2019-10-03T13:11:55Z","closed_at":"2019-10-03T13:11:55Z","author_association":"OWNER","body":"**NACHO** still guess housekeeping genes even when a list of housekeeping genes is provided.\r\n\r\n---\r\n\r\n``` r\r\nlibrary(GEOquery)\r\ngse <- getGEO(\"GSE70970\")\r\ntargets <- pData(phenoData(gse[[1]]))\r\ngetGEOSuppFiles(GEO = \"GSE70970\", baseDir = tempdir())\r\nuntar(\r\n  tarfile = paste0(tempdir(), \"/GSE70970/GSE70970_RAW.tar\"), \r\n  exdir = paste0(tempdir(), \"/GSE70970/Data\")\r\n)\r\n# Add IDs\r\ntargets$IDFILE <- list.files(paste0(tempdir(), \"/GSE70970/Data\"))\r\n\r\nlibrary(NACHO)\r\nGSE70970_sum <- summarise(\r\n  data_directory = paste0(tempdir(), \"/GSE70970/Data\"), # Where the data is\r\n  ssheet_csv = targets, # The samplesheet\r\n  id_colname = \"IDFILE\", # Name of the column that contains the identfiers\r\n  housekeeping_genes = NULL, # Custom list of housekeeping genes\r\n  housekeeping_predict = TRUE, # Predict the housekeeping genes based on the data?\r\n  normalisation_method = \"GEO\", # Geometric mean or GLM\r\n  n_comp = 5 # Number indicating the number of principal components to compute. \r\n)\r\n#> [NACHO] Importing RCC files.\r\n#> [NACHO] Performing QC and formatting data.\r\n#> [NACHO] Searching for the best housekeeping genes.\r\n#> [NACHO] Computing normalisation factors using \"GEO\" method for housekeeping genes prediction.\r\n#> [NACHO] The following predicted housekeeping genes will be used for normalisation:\r\n#>   - hsa-miR-103\r\n#>   - hsa-let-7e\r\n#>   - hsa-miR-1260\r\n#>   - hsa-miR-500+hsa-miR-501-5p\r\n#>   - hsa-miR-1274b\r\n#> [NACHO] Computing normalisation factors using \"GEO\" method.\r\n#> [NACHO] Missing values have been replaced with zeros for PCA.\r\n#> [NACHO] Normalising data using \"GEO\" method with housekeeping genes.\r\n#> [NACHO] Returning a list.\r\n#>   $ access              : character\r\n#>   $ housekeeping_genes  : character\r\n#>   $ housekeeping_predict: logical\r\n#>   $ housekeeping_norm   : logical\r\n#>   $ normalisation_method: character\r\n#>   $ remove_outliers     : logical\r\n#>   $ n_comp              : numeric\r\n#>   $ data_directory      : character\r\n#>   $ pc_sum              : data.frame\r\n#>   $ nacho               : data.frame\r\n#>   $ outliers_thresholds : list\r\n#>   $ raw_counts          : data.frame\r\n#>   $ normalised_counts   : data.frame\r\n\r\nunlink(paste0(tempdir(), \"/GSE70970\"), recursive = TRUE)\r\n\r\nmy_housekeeping <- GSE70970_sum[[\"housekeeping_genes\"]][-c(1, 2)]\r\n\r\nGSE70970_norm <- normalise(\r\n  nacho_object = GSE70970_sum,\r\n  housekeeping_genes = my_housekeeping,\r\n  housekeeping_norm = TRUE,\r\n  normalisation_method = \"GEO\", \r\n  remove_outliers = TRUE\r\n)\r\n#> [NACHO] Normalising \"GSE70970_sum\" with new value for parameters:\r\n#>   - housekeeping_genes = TRUE\r\n#>   - remove_outliers = TRUE\r\n#> [NACHO] Searching for the best housekeeping genes.\r\n#> [NACHO] Computing normalisation factors using \"GEO\" method for housekeeping genes prediction.\r\n#> [NACHO] The following predicted housekeeping genes will be used for normalisation:\r\n#>   - hsa-let-7e\r\n#>   - hsa-miR-1260\r\n#>   - hsa-miR-1274b\r\n#>   - hsa-miR-103\r\n#>   - hsa-miR-16\r\n#> [NACHO] Computing normalisation factors using \"GEO\" method.\r\n#> [NACHO] Missing values have been replaced with zeros for PCA.\r\n#> [NACHO] Returning a list.\r\n#>   $ access              : character\r\n#>   $ housekeeping_genes  : character\r\n#>   $ housekeeping_predict: logical\r\n#>   $ housekeeping_norm   : logical\r\n#>   $ normalisation_method: character\r\n#>   $ remove_outliers     : logical\r\n#>   $ n_comp              : numeric\r\n#>   $ data_directory      : character\r\n#>   $ pc_sum              : data.frame\r\n#>   $ nacho               : data.frame\r\n#>   $ outliers_thresholds : list\r\n#>   $ raw_counts          : data.frame\r\n#>   $ normalised_counts   : data.frame\r\n\r\n\r\nGSE70970_sum[[\"housekeeping_genes\"]]\r\n#> [1] \"hsa-miR-103\"                \"hsa-let-7e\"                \r\n#> [3] \"hsa-miR-1260\"               \"hsa-miR-500+hsa-miR-501-5p\"\r\n#> [5] \"hsa-miR-1274b\"\r\nmy_housekeeping\r\n#> [1] \"hsa-miR-1260\"               \"hsa-miR-500+hsa-miR-501-5p\"\r\n#> [3] \"hsa-miR-1274b\"\r\nGSE70970_norm[[\"housekeeping_genes\"]]\r\n#> [1] \"hsa-let-7e\"    \"hsa-miR-1260\"  \"hsa-miR-1274b\" \"hsa-miR-103\"  \r\n#> [5] \"hsa-miR-16\"\r\n```"}}
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