The miRNA Enrichment Analysis and Annotation Tool (miEAA) is a service provided by the Chair for Clinical Bioinformatics at Saarland University. Basically, miEAA is a multi-species microRNA enrichment analysis tool. For more information, see their website or published paper.
Before Enriching miRNA set, note that based on your input miRNA type (either all mature or precursor, not a mixture of both!) and the species, there will be different sets of supported enrichment categories.
Thus, it is recommended to retrieve a list of possible enrichment categories that you may use:
## A list of available enrichment categories for: ## mature human miRNA: rba_mieaa_cats(mirna_type = "mature", species = 9606) ## precursor human miRNA rba_mieaa_cats(mirna_type = "precursor", species = 9606) ## precursor zebrafish miRNA rba_mieaa_cats(mirna_type = "mature", species = "Danio rerio")
There are two approaches to do this, we will start with the simpler one.
Just fill the arguments of
rba_mieaa_enrich() according to the function’s manual; As you can see in the function’s arguments, you have a lot of controls over your enrichment request, but you need to provide
## 1 We create a variable with our miRNAs' mature IDs <- c("hsa-miR-20b-5p", "hsa-miR-144-5p", "hsa-miR-17-5p", "hsa-miR-20a-5p", mirs "hsa-miR-222-3p", "hsa-miR-106a-5p", "hsa-miR-93-5p", "hsa-miR-126-3p", "hsa-miR-363-3p", "hsa-miR-302c-3p", "hsa-miR-374b-5p", "hsa-miR-18a-5p", "hsa-miR-548d-3p", "hsa-miR-135a-3p", "hsa-miR-558", "hsa-miR-130b-5p", "hsa-miR-148a-3p") ## 2a We can enrich our miRNA set without limiting the enrichment to any categories <- rba_mieaa_enrich(test_set = mirs, mieaa_all mirna_type = "mature", test_type = "ORA", species = 9606) #> -- Step 1/3: Submitting Enrichment request: #> No categories were supplied, Requesting enrichment using all of the 28 available categories for species 'Homo sapiens'. #> Submitting ORA enrichment request for 17 miRNA IDs of species Homo sapiens to miEAA servers. #> #> -- Step 2/3: Checking for Submitted enrichment job's status every 5 seconds. #> Your submitted job ID is: 03a4dc71-5155-4de9-99f4-1a70f12d1cb4 #> .... #> #> -- Step 3/3: Retrieving the results of the finished enrichment job. #> Retrieving results of submitted enrichment request with ID: 03a4dc71-5155-4de9-99f4-1a70f12d1cb4 ## 2b Or, We can limit the enrichment to certain datasets (enrichment categories) <- rba_mieaa_enrich(test_set = mirs, mieaa_kegg mirna_type = "mature", test_type = "ORA", species = 9606, categories = c("miRWalk_Diseases_mature", "miRWalk_Organs_mature") )#> -- Step 1/3: Submitting Enrichment request: #> Submitting ORA enrichment request for 17 miRNA IDs of species Homo sapiens to miEAA servers. #> #> -- Step 2/3: Checking for Submitted enrichment job's status every 5 seconds. #> Your submitted job ID is: 234109d3-0fa6-4353-9316-46262c52440c #> . #> #> -- Step 3/3: Retrieving the results of the finished enrichment job. #> Retrieving results of submitted enrichment request with ID: 234109d3-0fa6-4353-9316-46262c52440c
As stated before,
rba_mieaa_enrich() is a wrapper function, meaning that it executes the following sequence of functions:
## 1 Submit enrichment request to miEAA <- rba_mieaa_enrich_submit(test_set = mirs, request mirna_type = "mature", test_type = "ORA", species = 9606, categories = c("miRWalk_Diseases_mature", "miRWalk_Organs_mature") )## 2 check for job's running status rba_mieaa_enrich_status(job_id = request$job_id) ## 3 If the job has completed, retrieve the results <- rba_mieaa_enrich_results(job_id = request$job_id)results
Please Note: Other services supported by rbioapi also provide Over-representation analysis tools. Please see the vignette article Do with rbioapi: Over-Representation (Enrichment) Analysis (link to the documentation site) for an in-depth review.
miEAA only recognizes miRBASE version 22 accessions. You can use
rba_mieaa_convert_version() to convert miRNA accession between different miRBASE versions. Also, as stated before, miEAA differentiate between precursor and mature miRNA accessions, to convert between these 2 accession types, use
To cite miEAA (Please see https://ccb-compute2.cs.uni-saarland.de/mieaa2/):
To cite rbioapi:
#> R version 4.1.2 (2021-11-01) #> Platform: x86_64-w64-mingw32/x64 (64-bit) #> Running under: Windows 10 x64 (build 19044) #> #> Matrix products: default #> #> locale: #>  LC_COLLATE=C #>  LC_CTYPE=English_United States.1252 #>  LC_MONETARY=English_United States.1252 #>  LC_NUMERIC=C #>  LC_TIME=English_United States.1252 #> system code page: 1256 #> #> attached base packages: #>  stats graphics grDevices utils datasets methods base #> #> other attached packages: #>  rbioapi_0.7.6 #> #> loaded via a namespace (and not attached): #>  digest_0.6.29 R6_2.5.1 jsonlite_1.8.0 magrittr_2.0.2 #>  evaluate_0.15 httr_1.4.2 stringi_1.7.6 rlang_1.0.2 #>  cli_3.2.0 curl_4.3.2 rstudioapi_0.13 jquerylib_0.1.4 #>  DT_0.21 bslib_0.3.1 rmarkdown_2.13 tools_4.1.2 #>  stringr_1.4.0 htmlwidgets_1.5.4 crosstalk_1.2.0 xfun_0.30 #>  yaml_2.3.5 fastmap_1.1.0 compiler_4.1.2 htmltools_0.5.2 #>  knitr_1.37 sass_0.4.0