Introduction

DoReMiTra provides a curated resource of radiation transcriptomic datasets with harmonized metadata for cross-study comparison such as:

Radiation_type, either Xray, gamma ray, neutron
Dose, which is commonly measured in Gy
Time_point, normally indicating the time post radiation exposure
Sex of the donors/samples collected
Organism, which at the current state of things is Homo sapiens and Mus musculus
Exp_setting exvivo invivo
Tissue, which at the current state includes only blood

The package delivers data as SummarizedExperiment objects directly accessible via ExperimentHub, enabling easy subsetting, filtering, and comparative analyses.

This vignette guides you through:

Exploring available datasets
Loading and summarizing datasets
Filtering datasets
Comparing metadata across datasets

Getting started

To install this package, start R and enter:

if (!requireNamespace("BiocManager", quietly = TRUE)) {
  install.packages("BiocManager")
}

BiocManager::install("DoReMiTra")

Once installed, the package can be loaded and attached to your current workspace as follows:

library("DoReMiTra")

List All Available Datasets

datasets <- list_DoReMiTra_datasets()
knitr::kable(datasets)

Dataset	RadiationType	Organism	ExpSetting	Accession	Tissue	Author
SE_Amundson_2019_InVivo_GSE124612_GPL11202	gamma ray	Mus musculus	InVivo	GSE124612	Blood	Amundson
SE_Aryankalayil_2018_InVivo_GSE104121_GPL10787	gamma ray	Mus musculus	InVivo	GSE104121	Blood	Aryankalayil
SE_Aryankalayil_2018_InVivo_GSE104121_GPL21163	gamma ray	Mus musculus	InVivo	GSE104121	Blood	Aryankalayil
SE_Park_2017_ExVivo_GSE102971_GPL10332_MacacaMulatta	gamma ray	Macaca mulatta	ExVivo	GSE102971	Blood	Park
SE_Park_2017_ExVivo_GSE102971_GPL10332_HomoSapiens	gamma ray	Homo sapiens	ExVivo	GSE102971	Blood	Park
SE_Vasilyev_2017_ExVivo_GSE97000_GPL17077	gamma ray	Homo sapiens	ExVivo	GSE97000	Blood	Vasilyev
SE_Paul_2013_ExVivo_GSE44201_GPL6480	gamma ray	Homo sapiens	ExVivo	GSE44201	Blood	Paul
SE_Paul_2013_ExVivo_GSE44201_GPL6848	gamma ray	Homo sapiens	ExVivo	GSE44201	Blood	Paul
SE_Nosel_2013_ExVivo_GSE43151_GPL13497	gamma ray	Homo sapiens	ExVivo	GSE43151	Blood	Nosel
SE_Girardi_2012_ExVivo_GSE20173_GPL6480	gamma ray	Homo sapiens	ExVivo	GSE20173	Blood	Girardi
SE_Amundson_2011_ExVivo_GSE23515_GPL6480	gamma ray	Homo sapiens	ExVivo	GSE23515	Blood	Amundson
SE_Gruel_2008_ExVivo_GSE6978_GPL4803	gamma ray	Homo sapiens	ExVivo	GSE6978	Blood	Gruel
SE_Rouchka_2019_ExVivo_GSE63952_GPL15207	gamma ray	Homo sapiens	ExVivo	GSE63952	Blood	Rouchka
SE_Amundson_2008_ExVivo_GSE8917_GPL1708	gamma ray	Homo sapiens	ExVivo	GSE8917	Blood	Amundson
SE_Manikandan_2014_ExVivo_GSE36355_GPL6883	gamma ray	Homo sapiens	ExVivo	GSE36355	Blood	Manikandan
SE_Lee_2013_ExVivo_GSE44245_GPL570	gamma ray	Homo sapiens	ExVivo	GSE44245	Blood	Lee
SE_Rouchka_2015_ExVivo_GSE64375_GPL6244	gamma ray	Homo sapiens	ExVivo	GSE64375	Blood	Rouchka
SE_Ankermit_2015_ExVivo_GSE55953_GPL14550	gamma ray	Homo sapiens	ExVivo	GSE55953	Blood	Ankermit
SE_Broustas_2018_InVivo_GSE113509_GPL11202	Neutron; X-ray	Mus musculus	InVivo	GSE113509	Blood	Broustas
SE_Broustas_2017_InVivo_GSE85323_GPL10333	Neutron; X-ray	Mus musculus	InVivo	GSE85323	Blood	Broustas
SE_Broustas_2017_ExVivo_GSE90909_GPL13497	Neutron; X-ray	Homo sapiens	ExVivo	GSE90909	Blood	Broustas
SE_Paul_2010_InVivo_GSE23393_GPL6480	X-ray	Homo sapiens	InVivo	GSE23393	Blood	Paul
SE_Ghandhi_2015_ExVivo_GSE65292_GPL13497	X-ray	Homo sapiens	ExVivo	GSE65292	Blood	Ghandhi
SE_Flores_2009_ExVivo_GSE15341_GPL8332	X-ray	Homo sapiens	ExVivo	GSE15341	Blood	Flores
SE_Amundson_2011_InVivo_GSE20162_GPL6480	X-ray	Homo sapiens	InVivo	GSE20162	Blood	Amundson
SE_Broustas_2023_InVivo_GSE196400_GPL11202	X-ray	Mus musculus	InVivo	GSE196400	Blood	Broustas
SE_Broustas_2022_InVivo_GSE184361_GPL11202	X-ray	Mus musculus	InVivo	GSE184361	Blood	Broustas
SE_Broustas_2021_InVivo_GSE132559_GPL11202	X-ray	Mus musculus	InVivo	GSE132559	Blood	Broustas
SE_Yamaguchi_2020_InVivo_GSE137192_GPL1261	X-ray	Mus musculus	InVivo	GSE137192	Blood	Yamaguchi
SE_Mukherjee_2019_InVivo_GSE114142_GPL11202	X-ray	Mus musculus	InVivo	GSE114142	Blood	Mukherjee
SE_Amundson_2018_InVivo_GSE101402_GPL11202	X-ray	Mus musculus	InVivo	GSE101402	Blood	Amundson
SE_Amundson_2018_InVivo_GSE99176_GPL11202	X-ray	Mus musculus	InVivo	GSE99176	Blood	Amundson
SE_Paul_2015_InVivo_GSE62623_GPL10333	X-ray	Mus musculus	InVivo	GSE62623	Blood	Paul
SE_Ghandhi_2018_InVivo_GSE84898_GPL13497	X-ray	Macaca mulatta	InVivo	GSE84898	Blood	Ghandhi
SE_Broustas_2021_InVivo_GSE133451_GPL11202	X-ray	Mus musculus	InVivo	GSE133451	Blood	Broustas
SE_Salah_2025_ExVivo	X-ray	Homo sapiens	ExVivo	NA	Blood	Salah

Load All Datasets

You can use the function get_all_DoReMiTra_datasets() to download all available DoReMiTra datasets from ExperimentHub. In this example, we fetched all the DoReMiTra datasets which is outputted as a named list from which you can easily access any SE object like (Salah et al. 2025) dataset simply by subsetting.


all_SEs <- get_all_DoReMiTra_datasets()

# Now you can access any loaded dataset by its name, for example:
all_SEs[["SE_Salah_2025_ExVivo"]]

List medatada information

list_DoReMiTra_metadata_feilds() function displays the available metadata fields across all DoReMiTra datasets along with the unique values observed for each field.It facilitates intuitive dataset discovery and filtering.


list_DoReMiTra_metadata_fields()
#> Available metadata fields:
#> - RadiationType: gamma ray, Neutron; X-ray, X-ray
#> - Organism: Homo sapiens, Macaca mulatta, Mus musculus
#> - ExpSetting: ExVivo, InVivo
#> - Accession: GSE101402, GSE102971, GSE104121, GSE113509, GSE114142, GSE124612, GSE132559, GSE133451, GSE137192, GSE15341, GSE184361, GSE196400, GSE20162, GSE20173, GSE23393, GSE23515, GSE36355, GSE43151, GSE44201, GSE44245, GSE55953, GSE62623, GSE63952, GSE64375, GSE65292, GSE6978, GSE84898, GSE85323, GSE8917, GSE90909, GSE97000, GSE99176
#> - Tissue: Blood
#> - Author: Amundson, Ankermit, Aryankalayil, Broustas, Flores, Ghandhi, Girardi, Gruel, Lee, Manikandan, Mukherjee, Nosel, Park, Paul, Rouchka, Salah, Vasilyev, Yamaguchi

Search for Specific Datasets

With the search_DoReMiTra_datasets() function, you can filter datasets based on radiation type, organism, author name, and experimental setting.

For example, in the following chunk we search for datasets where human samples have been exposed to gamma ray in an ex vivo setting.

search_DoReMiTra_datasets(radiation_type = "gamma ray", 
                          organism = "Homo sapiens", 
                          exp_setting = "ExVivo")
#> Filtering for radiation type: gamma ray
#> Filtering for organism: Homo sapiens
#> Filtering for experimental setting: ExVivo
#> Author not provided - searching across all authors.
#> 
#> Matching datasets found: 14
#> To retrieve one or more of these datasets, you can use:
#> se_name1 <- get_DoReMiTra_data("SE_Park_2017_ExVivo_GSE102971_GPL10332_HomoSapiens")
#> se_name2 <- get_DoReMiTra_data("SE_Vasilyev_2017_ExVivo_GSE97000_GPL17077")
#> 
#> For more details, please refer to `?get_DoReMiTra_data`
#>  [1] "SE_Park_2017_ExVivo_GSE102971_GPL10332_HomoSapiens"
#>  [2] "SE_Vasilyev_2017_ExVivo_GSE97000_GPL17077"         
#>  [3] "SE_Paul_2013_ExVivo_GSE44201_GPL6480"              
#>  [4] "SE_Paul_2013_ExVivo_GSE44201_GPL6848"              
#>  [5] "SE_Nosel_2013_ExVivo_GSE43151_GPL13497"            
#>  [6] "SE_Girardi_2012_ExVivo_GSE20173_GPL6480"           
#>  [7] "SE_Amundson_2011_ExVivo_GSE23515_GPL6480"          
#>  [8] "SE_Gruel_2008_ExVivo_GSE6978_GPL4803"              
#>  [9] "SE_Rouchka_2019_ExVivo_GSE63952_GPL15207"          
#> [10] "SE_Amundson_2008_ExVivo_GSE8917_GPL1708"           
#> [11] "SE_Manikandan_2014_ExVivo_GSE36355_GPL6883"        
#> [12] "SE_Lee_2013_ExVivo_GSE44245_GPL570"                
#> [13] "SE_Rouchka_2015_ExVivo_GSE64375_GPL6244"           
#> [14] "SE_Ankermit_2015_ExVivo_GSE55953_GPL14550"

Load a Dataset

To access an individual dataset, use its exact name as provided by list_DoReMiTra_datasets(). This function contains “gene_symbol” argument that is set to FALSE by default, which assigns the gene symbol from the rowData to the rownames of the SE object. if a gene symbol was found to be duplicated, the gene symbol and its corresponding probe id will be appended and assigned to the rownames. if a gene symbol is messing- NA- the probe id will be used instead. otherwise, if the gene_symbol is set to FALSE, probe ids will be used as rownames

search_DoReMiTra_datasets(radiation_type = "X-ray", 
                          organism = "Homo sapiens", 
                          exp_setting = "ExVivo")
#> Filtering for radiation type: X-ray
#> Filtering for organism: Homo sapiens
#> Filtering for experimental setting: ExVivo
#> Author not provided - searching across all authors.
#> 
#> Matching datasets found: 4
#> To retrieve one or more of these datasets, you can use:
#> se_name1 <- get_DoReMiTra_data("SE_Broustas_2017_ExVivo_GSE90909_GPL13497")
#> se_name2 <- get_DoReMiTra_data("SE_Ghandhi_2015_ExVivo_GSE65292_GPL13497")
#> 
#> For more details, please refer to `?get_DoReMiTra_data`
#> [1] "SE_Broustas_2017_ExVivo_GSE90909_GPL13497"
#> [2] "SE_Ghandhi_2015_ExVivo_GSE65292_GPL13497" 
#> [3] "SE_Flores_2009_ExVivo_GSE15341_GPL8332"   
#> [4] "SE_Salah_2025_ExVivo"

dataset_name <- "SE_Broustas_2017_ExVivo_GSE90909_GPL13497"
se <- get_DoReMiTra_data(dataset_name, gene_symbol = TRUE)
#> see ?DoReMiTra and browseVignettes('DoReMiTra') for documentation
#> downloading 1 resources
#> retrieving 1 resource
#> loading from cache
se
#> class: SummarizedExperiment 
#> dim: 12289 92 
#> metadata(1): DoReMiTra
#> assays(1): exprs
#> rownames(12289): _(+)E1A_r60_1 _(+)E1A_r60_3 ... _ETG10_234183
#>   _GE_BrightCorner
#> rowData names(18): ID SPOT_ID ... SEQUENCE SYMBOL
#> colnames(92): GSM2417353 GSM2417354 ... GSM2417443 GSM2417444
#> colData names(45): title geo_accession ... Exp_setting Tissue

Exploring a Dataset

Each dataset is a SummarizedExperiment object with gene-level expression values, sample-level metadata (colData) and gene annotations (rowData):

assay(se)[1:5, 1:5] # expression matrix
#>                  GSM2417353 GSM2417354 GSM2417355 GSM2417356 GSM2417357
#> _(+)E1A_r60_1     18.115025  17.673410  17.577608  18.373386  17.952204
#> _(+)E1A_r60_3      3.947578   2.215706   2.473996   2.886919   2.374902
#> _(+)E1A_r60_a104   5.122130   4.716759   3.974693   3.266030   3.144284
#> _(+)E1A_r60_a107   4.961576   4.226226   4.386784   4.988791   4.612860
#> _(+)E1A_r60_a135   7.657646   7.323098   7.118343   7.914989   7.519629
head(rowData(se)) # gene info
#> DataFrame with 6 rows and 18 columns
#>                               ID         SPOT_ID CONTROL_TYPE      REFSEQ
#>                      <character>     <character>  <character> <character>
#> _(+)E1A_r60_1       (+)E1A_r60_1    (+)E1A_r60_1          pos            
#> _(+)E1A_r60_3       (+)E1A_r60_3    (+)E1A_r60_3          pos            
#> _(+)E1A_r60_a104 (+)E1A_r60_a104 (+)E1A_r60_a104          pos            
#> _(+)E1A_r60_a107 (+)E1A_r60_a107 (+)E1A_r60_a107          pos            
#> _(+)E1A_r60_a135 (+)E1A_r60_a135 (+)E1A_r60_a135          pos            
#> _(+)E1A_r60_a20   (+)E1A_r60_a20  (+)E1A_r60_a20          pos            
#>                       GB_ACC      GENE GENE_SYMBOL   GENE_NAME  UNIGENE_ID
#>                  <character> <integer> <character> <character> <character>
#> _(+)E1A_r60_1                       NA                                    
#> _(+)E1A_r60_3                       NA                                    
#> _(+)E1A_r60_a104                    NA                                    
#> _(+)E1A_r60_a107                    NA                                    
#> _(+)E1A_r60_a135                    NA                                    
#> _(+)E1A_r60_a20                     NA                                    
#>                   ENSEMBL_ID   TIGR_ID ACCESSION_STRING CHROMOSOMAL_LOCATION
#>                  <character> <logical>      <character>          <character>
#> _(+)E1A_r60_1                       NA                                      
#> _(+)E1A_r60_3                       NA                                      
#> _(+)E1A_r60_a104                    NA                                      
#> _(+)E1A_r60_a107                    NA                                      
#> _(+)E1A_r60_a135                    NA                                      
#> _(+)E1A_r60_a20                     NA                                      
#>                     CYTOBAND DESCRIPTION       GO_ID    SEQUENCE      SYMBOL
#>                  <character> <character> <character> <character> <character>
#> _(+)E1A_r60_1                                                               
#> _(+)E1A_r60_3                                                               
#> _(+)E1A_r60_a104                                                            
#> _(+)E1A_r60_a107                                                            
#> _(+)E1A_r60_a135                                                            
#> _(+)E1A_r60_a20
head(colData(se)) # sample info
#> DataFrame with 6 rows and 45 columns
#>                             title geo_accession                status
#>                       <character>   <character>           <character>
#> GSM2417353 blood 0.25Gy Neutron..    GSM2417353 Public on Feb 22 2017
#> GSM2417354 blood 0.5Gy Neutron ..    GSM2417354 Public on Feb 22 2017
#> GSM2417355 blood 1Gy Neutron rep1    GSM2417355 Public on Feb 22 2017
#> GSM2417356   blood 1Gy X-ray rep1    GSM2417356 Public on Feb 22 2017
#> GSM2417357   blood 2Gy X-ray rep1    GSM2417357 Public on Feb 22 2017
#> GSM2417358   blood 4Gy X-ray rep1    GSM2417358 Public on Feb 22 2017
#>            submission_date last_update_date        type channel_count
#>                <character>      <character> <character>   <character>
#> GSM2417353     Dec 05 2016      Feb 24 2017         RNA             1
#> GSM2417354     Dec 05 2016      Feb 24 2017         RNA             1
#> GSM2417355     Dec 05 2016      Feb 24 2017         RNA             1
#> GSM2417356     Dec 05 2016      Feb 24 2017         RNA             1
#> GSM2417357     Dec 05 2016      Feb 24 2017         RNA             1
#> GSM2417358     Dec 05 2016      Feb 24 2017         RNA             1
#>                 source_name_ch1 organism_ch1 characteristics_ch1
#>                     <character>  <character>         <character>
#> GSM2417353 blood 0.25Gy Neutron Homo sapiens      donor: Donor 1
#> GSM2417354  blood 0.5Gy Neutron Homo sapiens      donor: Donor 1
#> GSM2417355    blood 1Gy Neutron Homo sapiens      donor: Donor 1
#> GSM2417356      blood 1Gy X-ray Homo sapiens      donor: Donor 1
#> GSM2417357      blood 2Gy X-ray Homo sapiens      donor: Donor 1
#> GSM2417358      blood 4Gy X-ray Homo sapiens      donor: Donor 1
#>             characteristics_ch1.1 treatment_protocol_ch1    growth_protocol_ch1
#>                       <character>            <character>            <character>
#> GSM2417353 tissue: peripheral b.. Peripheral blood fro.. After irradiation, b..
#> GSM2417354 tissue: peripheral b.. Peripheral blood fro.. After irradiation, b..
#> GSM2417355 tissue: peripheral b.. Peripheral blood fro.. After irradiation, b..
#> GSM2417356 tissue: peripheral b.. Peripheral blood fro.. After irradiation, b..
#> GSM2417357 tissue: peripheral b.. Peripheral blood fro.. After irradiation, b..
#> GSM2417358 tissue: peripheral b.. Peripheral blood fro.. After irradiation, b..
#>            molecule_ch1   extract_protocol_ch1   label_ch1
#>             <character>            <character> <character>
#> GSM2417353    total RNA The RNA was prepared..         Cy3
#> GSM2417354    total RNA The RNA was prepared..         Cy3
#> GSM2417355    total RNA The RNA was prepared..         Cy3
#> GSM2417356    total RNA The RNA was prepared..         Cy3
#> GSM2417357    total RNA The RNA was prepared..         Cy3
#> GSM2417358    total RNA The RNA was prepared..         Cy3
#>                label_protocol_ch1   taxid_ch1           hyb_protocol
#>                       <character> <character>            <character>
#> GSM2417353 Cyanine-3 (Cy3) labe..        9606 1.65 ug of Cy3-label..
#> GSM2417354 Cyanine-3 (Cy3) labe..        9606 1.65 ug of Cy3-label..
#> GSM2417355 Cyanine-3 (Cy3) labe..        9606 1.65 ug of Cy3-label..
#> GSM2417356 Cyanine-3 (Cy3) labe..        9606 1.65 ug of Cy3-label..
#> GSM2417357 Cyanine-3 (Cy3) labe..        9606 1.65 ug of Cy3-label..
#> GSM2417358 Cyanine-3 (Cy3) labe..        9606 1.65 ug of Cy3-label..
#>                     scan_protocol        data_processing platform_id
#>                       <character>            <character> <character>
#> GSM2417353 Slides were scanned .. The scanned images w..    GPL13497
#> GSM2417354 Slides were scanned .. The scanned images w..    GPL13497
#> GSM2417355 Slides were scanned .. The scanned images w..    GPL13497
#> GSM2417356 Slides were scanned .. The scanned images w..    GPL13497
#> GSM2417357 Slides were scanned .. The scanned images w..    GPL13497
#> GSM2417358 Slides were scanned .. The scanned images w..    GPL13497
#>               contact_name          contact_email     contact_department
#>                <character>            <character>            <character>
#> GSM2417353 Sally,,Amundson [email protected].. Center for Radiologi..
#> GSM2417354 Sally,,Amundson [email protected].. Center for Radiologi..
#> GSM2417355 Sally,,Amundson [email protected].. Center for Radiologi..
#> GSM2417356 Sally,,Amundson [email protected].. Center for Radiologi..
#> GSM2417357 Sally,,Amundson [email protected].. Center for Radiologi..
#> GSM2417358 Sally,,Amundson [email protected].. Center for Radiologi..
#>              contact_institute contact_address contact_city contact_state
#>                    <character>     <character>  <character>   <character>
#> GSM2417353 Columbia University 630 W. 168th St     New York            NY
#> GSM2417354 Columbia University 630 W. 168th St     New York            NY
#> GSM2417355 Columbia University 630 W. 168th St     New York            NY
#> GSM2417356 Columbia University 630 W. 168th St     New York            NY
#> GSM2417357 Columbia University 630 W. 168th St     New York            NY
#> GSM2417358 Columbia University 630 W. 168th St     New York            NY
#>            contact_zip.postal_code contact_country     supplementary_file
#>                        <character>     <character>            <character>
#> GSM2417353                   10032             USA ftp://ftp.ncbi.nlm.n..
#> GSM2417354                   10032             USA ftp://ftp.ncbi.nlm.n..
#> GSM2417355                   10032             USA ftp://ftp.ncbi.nlm.n..
#> GSM2417356                   10032             USA ftp://ftp.ncbi.nlm.n..
#> GSM2417357                   10032             USA ftp://ftp.ncbi.nlm.n..
#> GSM2417358                   10032             USA ftp://ftp.ncbi.nlm.n..
#>            data_row_count   donor.ch1       tissue.ch1        Dose  Time_point
#>               <character> <character>      <character> <character> <character>
#> GSM2417353          12289     Donor 1 peripheral blood      0.25Gy         24h
#> GSM2417354          12289     Donor 1 peripheral blood       0.5Gy         24h
#> GSM2417355          12289     Donor 1 peripheral blood         1Gy         24h
#> GSM2417356          12289     Donor 1 peripheral blood         1Gy         24h
#> GSM2417357          12289     Donor 1 peripheral blood         2Gy         24h
#> GSM2417358          12289     Donor 1 peripheral blood         4Gy         24h
#>                    Sex Radiation_type   Sample_id     Organism    Platform
#>            <character>    <character> <character>  <character> <character>
#> GSM2417353          NA        Neutron  GSM2417353 Homo sapiens  Microarray
#> GSM2417354          NA        Neutron  GSM2417354 Homo sapiens  Microarray
#> GSM2417355          NA        Neutron  GSM2417355 Homo sapiens  Microarray
#> GSM2417356          NA          X-ray  GSM2417356 Homo sapiens  Microarray
#> GSM2417357          NA          X-ray  GSM2417357 Homo sapiens  Microarray
#> GSM2417358          NA          X-ray  GSM2417358 Homo sapiens  Microarray
#>             TaxonomyId Exp_setting      Tissue
#>            <character> <character> <character>
#> GSM2417353        9606      ExVivo       Blood
#> GSM2417354        9606      ExVivo       Blood
#> GSM2417355        9606      ExVivo       Blood
#> GSM2417356        9606      ExVivo       Blood
#> GSM2417357        9606      ExVivo       Blood
#> GSM2417358        9606      ExVivo       Blood

Summarize a Dataset

You can get a quick metadata summary of a dataset using summarize_DoReMiTra_se()which will output key information like the author of the study, number of the samples, organism, experiment setting, and radiation type and dose, and a link directing you to the the study

summarize_DoReMiTra_se(se)
#> This dataset is generated by: Broustas
#>     Platform: Microarray
#>     Organism(s): Homo sapiens
#>     Radiation Type: Neutron; X-ray
#>     Experiment Setting: ExVivo
#>     Number of Samples: 92
#>     Tissue: Blood
#>     Accession: GSE90909
#>     For more information about this study, please check: 
#> https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE90909

Compare Metadata Across Multiple Datasets

This is useful for checking compatibility before combined analysis - for example, we first searched for studies that involved gamma ray irradiation of homo sapiens samples. from the number of studies that are shown, we want to compare between (Park et al. 2017) and (Paul and Amundson 2008)

search_DoReMiTra_datasets(radiation_type = "gamma ray", 
                          organism = "Homo sapiens", 
                          exp_setting = "ExVivo")
#> Filtering for radiation type: gamma ray
#> Filtering for organism: Homo sapiens
#> Filtering for experimental setting: ExVivo
#> Author not provided - searching across all authors.
#> 
#> Matching datasets found: 14
#> To retrieve one or more of these datasets, you can use:
#> se_name1 <- get_DoReMiTra_data("SE_Park_2017_ExVivo_GSE102971_GPL10332_HomoSapiens")
#> se_name2 <- get_DoReMiTra_data("SE_Vasilyev_2017_ExVivo_GSE97000_GPL17077")
#> 
#> For more details, please refer to `?get_DoReMiTra_data`
#>  [1] "SE_Park_2017_ExVivo_GSE102971_GPL10332_HomoSapiens"
#>  [2] "SE_Vasilyev_2017_ExVivo_GSE97000_GPL17077"         
#>  [3] "SE_Paul_2013_ExVivo_GSE44201_GPL6480"              
#>  [4] "SE_Paul_2013_ExVivo_GSE44201_GPL6848"              
#>  [5] "SE_Nosel_2013_ExVivo_GSE43151_GPL13497"            
#>  [6] "SE_Girardi_2012_ExVivo_GSE20173_GPL6480"           
#>  [7] "SE_Amundson_2011_ExVivo_GSE23515_GPL6480"          
#>  [8] "SE_Gruel_2008_ExVivo_GSE6978_GPL4803"              
#>  [9] "SE_Rouchka_2019_ExVivo_GSE63952_GPL15207"          
#> [10] "SE_Amundson_2008_ExVivo_GSE8917_GPL1708"           
#> [11] "SE_Manikandan_2014_ExVivo_GSE36355_GPL6883"        
#> [12] "SE_Lee_2013_ExVivo_GSE44245_GPL570"                
#> [13] "SE_Rouchka_2015_ExVivo_GSE64375_GPL6244"           
#> [14] "SE_Ankermit_2015_ExVivo_GSE55953_GPL14550"

se1 <- get_DoReMiTra_data("SE_Park_2017_ExVivo_GSE102971_GPL10332_HomoSapiens")
#> see ?DoReMiTra and browseVignettes('DoReMiTra') for documentation
#> downloading 1 resources
#> retrieving 1 resource
#> loading from cache
se2 <- get_DoReMiTra_data("SE_Paul_2013_ExVivo_GSE44201_GPL6480")
#> see ?DoReMiTra and browseVignettes('DoReMiTra') for documentation
#> downloading 1 resources
#> retrieving 1 resource
#> loading from cache
se_list<- list(
  Park = se1, 
  Paul = se2
)
compare_DoReMiTra_datasets(se_list = se_list)
#>                                   Park                      Paul
#> Radiation_type               gamma ray                 gamma ray
#> Dose           0Gy, 2Gy, 5Gy, 6Gy, 7Gy 0.5Gy, 0Gy, 2Gy, 5Gy, 8Gy
#> Sex                       Female, Male              female, male
#> Time_point                         24h                      48hr
#> Organism                  Homo sapiens              Homo sapiens
#> Tissue                           Blood                     Blood
#> Sample_number                      100                        25

Troubleshooting and Tips

Always use exact dataset names from list_DoReMiTra_datasets() when calling get_DoReMiTra_data().
Use search_DoReMiTra_datasets() to dynamically find datasets of interest based on key metadata fields.
If you get a missing dataset error, check for typos or mismatched casing.

How to cite data included in DoReMiTra

To cite the datasets or studies, please refer to the original GEO accession IDs (e.g., GSE124612). More details are included in the metadata, which you can easily access via summarize_DoReMiTra_se().

Session Info

sessionInfo()
#> 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
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats4    stats     graphics  grDevices utils     datasets  methods  
#> [8] base     
#> 
#> other attached packages:
#>  [1] DoReMiTra_1.3.0             ExperimentHub_3.3.2        
#>  [3] AnnotationHub_4.3.2         BiocFileCache_3.3.0        
#>  [5] dbplyr_2.6.0                SummarizedExperiment_1.43.0
#>  [7] Biobase_2.73.2              GenomicRanges_1.65.4       
#>  [9] Seqinfo_1.3.2               IRanges_2.47.5             
#> [11] S4Vectors_0.51.10           BiocGenerics_0.59.12       
#> [13] generics_0.1.4              MatrixGenerics_1.25.0      
#> [15] matrixStats_1.5.0           BiocStyle_2.41.0           
#> 
#> loaded via a namespace (and not attached):
#>  [1] tidyselect_1.2.1            viridisLite_0.4.3          
#>  [3] vipor_0.4.7                 farver_2.1.2               
#>  [5] dplyr_1.2.1                 blob_1.3.0                 
#>  [7] viridis_0.6.5               S7_0.2.2                   
#>  [9] filelock_1.0.3              Biostrings_2.81.9          
#> [11] fastmap_1.2.0               SingleCellExperiment_1.35.2
#> [13] digest_0.6.39               rsvd_1.0.5                 
#> [15] lifecycle_1.0.5             KEGGREST_1.53.6            
#> [17] RSQLite_3.53.3              magrittr_2.0.5             
#> [19] compiler_4.6.1              rlang_1.3.0                
#> [21] sass_0.4.10                 tools_4.6.1                
#> [23] yaml_2.3.12                 knitr_1.52                 
#> [25] S4Arrays_1.13.2             bit_4.6.0                  
#> [27] curl_8.0.0                  DelayedArray_0.39.8        
#> [29] RColorBrewer_1.1-3          abind_1.4-8                
#> [31] BiocParallel_1.47.0         withr_3.0.3                
#> [33] purrr_1.2.2                 sys_3.4.3                  
#> [35] grid_4.6.1                  beachmat_2.29.3            
#> [37] ggplot2_4.0.3               scales_1.4.0               
#> [39] cli_3.6.6                   rmarkdown_2.32             
#> [41] crayon_1.5.3                otel_0.2.0                 
#> [43] httr_1.4.9                  BiocBaseUtils_1.15.1       
#> [45] DBI_1.3.0                   scuttle_1.23.2             
#> [47] ggbeeswarm_0.7.3            cachem_1.1.0               
#> [49] parallel_4.6.1              AnnotationDbi_1.75.2       
#> [51] BiocManager_1.30.27         XVector_0.53.0             
#> [53] vctrs_0.7.3                 Matrix_1.7-6               
#> [55] jsonlite_2.0.0              BiocSingular_1.29.2        
#> [57] BiocNeighbors_2.7.3         ggrepel_0.9.8              
#> [59] bit64_4.8.6                 beeswarm_0.4.0             
#> [61] irlba_2.4.1                 scater_1.41.2              
#> [63] maketools_1.3.2             jquerylib_0.1.4            
#> [65] glue_1.8.1                  codetools_0.2-20           
#> [67] gtable_0.3.6                BiocVersion_3.24.0         
#> [69] ScaledMatrix_1.21.0         tibble_3.3.1               
#> [71] pillar_1.11.1               rappdirs_0.3.4             
#> [73] htmltools_0.5.9             R6_2.6.1                   
#> [75] httr2_1.3.0                 evaluate_1.0.5             
#> [77] lattice_0.23-1              png_0.1-9                  
#> [79] memoise_2.0.1               bslib_0.12.0               
#> [81] Rcpp_1.1.2                  gridExtra_2.3.1            
#> [83] SparseArray_1.13.4          xfun_0.61                  
#> [85] buildtools_1.0.0            pkgconfig_2.0.3

References

Park, Jin G., Sunirmal Paul, Natalia Briones, et al. 2017. “Developing Human Radiation Biodosimetry Models: Testing Cross-Species Conversion Approaches Using an Ex Vivo Model System.” Radiation Research 187 (6): 708. https://doi.org/10.1667/rr14655.1.

Paul, Sunirmal, and Sally A. Amundson. 2008. “Development of Gene Expression Signatures for Practical Radiation Biodosimetry.” International Journal of Radiation Oncology*Biology*Physics 71 (4): 1236–1244.e76. https://doi.org/10.1016/j.ijrobp.2008.03.043.

Salah, Ahmed, Daniel Wollschläger, Maurizio Callari, Heinz Schmidberger, Federico Marini, and Sebastian Zahnreich. 2025. “Genome-Wide Transcriptomic Response of Whole Blood to Radiation.” Scientific Reports 15 (1). https://doi.org/10.1038/s41598-025-04898-1.