The AWAggregatorData package contains the data
associated with the AWAggregator R package. It includes two
pre-trained random forest models, one incorporating the average
coefficient of variation as a feature, and the other one not including
it. It also contains the PSMs in Benchmark Set 1~3 derived from the
psm.tsv output files generated by FragPipe, which are used
to train the random forest models.
Data available in the AWAggregatorData package:
regr: represent the pre-trained random forest model
that incorporates the average coefficient of variation (CV) as a
feature.
regr.no.CV: represent the pre-trained random forest
model that does not include the average CV as a feature.
benchmark.set.1, benchmark.set.2,
benchmark.set.3: represents PSMs in Benchmark Set 1~3
derived from the psm.tsv output files generated by
FragPipe, which are used to train the random forest model. Columns
unnecessary for the AWAggregator have been removed from the
sample data.
ExperimentHubData are stored via ExperimentHub package. The
information of available datasets can be retrieved by the
query function
## Loading required package: BiocGenerics## Loading required package: generics##
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## unsplit, which.max, which.min## Loading required package: AnnotationHub## Loading required package: BiocFileCache## Loading required package: dbplyr## ExperimentHub with 5 records
## # snapshotDate(): 2026-04-21
## # $dataprovider: University of British Columbia
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## # coordinate_1_based, maintainer, rdatadateadded, preparerclass, tags,
## # rdatapath, sourceurl, sourcetype
## # retrieve records with, e.g., 'object[["EH9637"]]'
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## title
## EH9637 | benchmark.set.1.rds
## EH9638 | benchmark.set.2.rds
## EH9639 | benchmark.set.3.rds
## EH9640 | regr.rds
## EH9641 | regr.no.CV.rdsThe datasets and pre-trained models can be downloaded by:
## see ?AWAggregatorData and browseVignettes('AWAggregatorData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## see ?AWAggregatorData and browseVignettes('AWAggregatorData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## see ?AWAggregatorData and browseVignettes('AWAggregatorData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache# Pre-trained model incorporating the average coefficient of variation (CV) as
# a feature
regr = eh[['EH9640']]## see ?AWAggregatorData and browseVignettes('AWAggregatorData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## see ?AWAggregatorData and browseVignettes('AWAggregatorData') for documentation## downloading 1 resources## retrieving 1 resource## loading from cache## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 26.04.1 LTS
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## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
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## other attached packages:
## [1] AWAggregatorData_1.2.0 ExperimentHub_3.2.2 AnnotationHub_4.2.2
## [4] BiocFileCache_3.2.0 dbplyr_2.6.0 BiocGenerics_0.58.1
## [7] generics_0.1.4 BiocStyle_2.40.0
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## loaded via a namespace (and not attached):
## [1] rappdirs_0.3.4 sass_0.4.10 BiocVersion_3.23.1
## [4] RSQLite_3.53.3 digest_0.6.39 magrittr_2.0.5
## [7] evaluate_1.0.5 fastmap_1.2.0 blob_1.3.0
## [10] jsonlite_2.0.0 AnnotationDbi_1.74.0 DBI_1.3.0
## [13] BiocManager_1.30.27 httr_1.4.9 purrr_1.2.2
## [16] Biostrings_2.80.2 httr2_1.3.0 jquerylib_0.1.4
## [19] cli_3.6.6 crayon_1.5.3 rlang_1.3.0
## [22] XVector_0.52.0 Biobase_2.72.0 bit64_4.8.6
## [25] withr_3.0.3 cachem_1.1.0 yaml_2.3.12
## [28] tools_4.6.1 memoise_2.0.1 dplyr_1.2.1
## [31] filelock_1.0.3 curl_8.0.0 png_0.1-9
## [34] buildtools_1.0.0 vctrs_0.7.3 R6_2.6.1
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## [40] KEGGREST_1.52.2 S4Vectors_0.50.3 IRanges_2.46.0
## [43] bit_4.6.0 pkgconfig_2.0.3 pillar_1.11.1
## [46] bslib_0.12.0 glue_1.8.1 xfun_0.61
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## [52] knitr_1.52 htmltools_0.5.9 rmarkdown_2.32
## [55] maketools_1.3.2 compiler_4.6.1