AssessORFData is an accompaniment to the AssessORF package, providing access to mapping and results objects generated by AssessORF as well as the genome sequences for the strains corresponding to those objects. Briefly, a mapping object stores the mapping of proteomics evidence and evolutionary conservation evidence to a particular strain’s genome, and a results object stores how much evidence there is supporting or against each gene in a set of predicted genes for a particular strain’s genome. Detailed descriptions of the structure and content of those two types of objects can be found in the documentation for the AssessORF package.
AssessORFData has data for 20 strains and their IDs (within the package) are listed below:
## [1] "ATCC11842" "ATCC13032" "ATCC17978" "ATCC700084" "CCMP1375"
## [6] "CECT5344" "CNRZ327" "COH1" "D_UW_3_CX" "EGD_e"
## [11] "H37Rv" "Houston_1" "Il1403" "K_12_MG1655" "LAL14_1"
## [16] "MGAS5005" "PAO1" "SL1344" "Strain168" "TCH1516"
## [21] "AP1" "BW25113" "HG001" "MG1363" "NCIB_3610"
## [26] "Strain10403S"For each strain, there are 5 objects: 1 mapping object and 4 results objects. The 4 results objects per strain differ in that for each one, the set of predicted genes came from a different program or database. The same 4 gene sources were used for all 20 strains, and their IDs (within the package) are listed below:
## [1] "Prodigal" "GeneMarkS2" "GenBank" "Glimmer"While the data function can be used to pull the desired
object from the package into the user’s workspace, using the the
data function may be inconvenient for some users because
there are 100 mapping and results objects, each of which has a long
name. For this reason, AssessORFData has alternative functions,
GetDataMapObj and GetResultsObj, to accomplish
a similar task. These functions allow the user to get the object of
interest and then save it in their workspace under a different name.
Examples on how to use the two functions are described below:
## Loading required package: RSQLite## Can replace the character string specifying the strain ID (first
## parameter) with any of the other 19 strain IDs listed above
mapObj <- GetDataMapObj("MGAS5005")
resObj1 <- GetResultsObj("MGAS5005", "Prodigal")
resObj2 <- GetResultsObj("MGAS5005", "GenBank")
resObj3 <- GetResultsObj("MGAS5005", "GeneMarkS2")
resObj4 <- GetResultsObj("MGAS5005", "Glimmer")The SaveGenomeToPath function allows the user to save
the genome for a strain of their choosing to a file path on their local
machine in situations where the user wants to run their own analyses on
their strain’s genome, e.g. predict genes for the genome using a
different gene finding program. An example of how to use the function is
provided below:
library(AssessORFData)
## A path to a temporary file is used in this example.
tmpFile <- paste0(tempfile(), ".fasta")
## Replace the second parameter below with a character string specifying
## the desired file path, making sure the file is of type FASTA.
SaveGenomeToPath("MGAS5005", tmpFile)
unlink(tmpFile)All of the output in this vignette was produced under the following conditions:
## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 26.04.1 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.32.so; LAPACK version 3.12.0
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] AssessORFData_1.30.0 RSQLite_3.53.3 BiocStyle_2.40.0
##
## loaded via a namespace (and not attached):
## [1] vctrs_0.7.3 crayon_1.5.3 cli_3.6.6
## [4] knitr_1.52 rlang_1.3.0 xfun_0.61
## [7] DBI_1.3.0 generics_0.1.4 jsonlite_2.0.0
## [10] bit_4.6.0 S4Vectors_0.50.3 buildtools_1.0.0
## [13] Biostrings_2.80.2 htmltools_0.5.9 maketools_1.3.2
## [16] sys_3.4.3 sass_0.4.10 stats4_4.6.1
## [19] rmarkdown_2.32 Seqinfo_1.2.0 evaluate_1.0.5
## [22] jquerylib_0.1.4 DECIPHER_3.8.1 fastmap_1.2.0
## [25] IRanges_2.46.0 yaml_2.3.12 lifecycle_1.0.5
## [28] memoise_2.0.1 BiocManager_1.30.27 compiler_4.6.1
## [31] blob_1.3.0 XVector_0.52.0 digest_0.6.39
## [34] R6_2.6.1 bslib_0.12.0 bit64_4.8.6
## [37] tools_4.6.1 BiocGenerics_0.58.1 cachem_1.1.0