R/allEndpoints.R
get_dataset_differential_expression_analyses.RdRetrieve annotations and surface level stats for a dataset's differential analyses
A numerical dataset identifier or a dataset short name
TRUE to receive results as-is from Gemma, or FALSE to enable
parsing. Raw results usually contain additional fields and flags that are
omitted in the parsed results.
Whether or not to save to cache for future calls with the
same inputs and use the result saved in cache if a result is already saved.
Doing options(gemma.memoised = TRUE) will ensure that the cache is always
used. Use forget_gemma_memoised to clear the cache.
The name of a file to save the results to, or NULL to not write
results to a file. If raw == TRUE, the output will be the raw endpoint from the
API, likely a JSON or a gzip file. Otherwise, it will be a RDS file.
Whether or not to overwrite if a file exists at the specified filename.
A data table with information about the differential expression
analysis of the queried dataset. Note that this funciton does not return
differential expression values themselves. Use get_differential_expression_values
to get differential expression values (see examples).
The fields of the output data.table are:
result.ID: Result set ID of the differential expression analysis.
May represent multiple factors in a single model.
contrast.ID: Id of the specific contrast factor. Together with the result.ID
they uniquely represent a given contrast.
experiment.ID: Id of the source experiment
factor.category: Category for the contrast
factor.category.URI: URI for the contrast category
factor.ID: ID of the factor
baseline.factors: Characteristics of the baseline. This field is a data.table
experimental.factors: Characteristics of the experimental group. This field is a data.table
isSubset: TRUE if the result set belong to a subset, FALSE if not. Subsets are created when performing differential expression to avoid unhelpful comparisons.
subsetFactor: Characteristics of the subset. This field is a data.table
probes.analyzed: Number of probesets represented in the contrast
genes.analyzed: Number of genes represented in the contrast
result <- get_dataset_differential_expression_analyses("GSE2872")
get_differential_expression_values(resultSet = result$result.ID[1])
#> $`570867`
#> Probe NCBIid GeneSymbol
#> <char> <char> <char>
#> 1: 1389528_s_at 24516 Jun
#> 2: 1374404_at 24516 Jun
#> 3: 1370315_a_at 79423 Stmn4
#> 4: 1369788_s_at 24516 Jun
#> 5: 1379606_at 308821 Rab30
#> ---
#> 15566: 1387552_at 116681 Dlgap2
#> 15567: 1367675_at 81823 Cib1
#> 15568: 1384589_at 498963 Spata2L
#> 15569: 1388175_at 79430 Clcnkb
#> 15570: 1398810_at 64527 Pdap1
#> GeneName pvalue
#> <char> <num>
#> 1: Jun proto-oncogene, AP-1 transcription factor subunit 2.836e-06
#> 2: Jun proto-oncogene, AP-1 transcription factor subunit 1.160e-05
#> 3: stathmin 4 1.903e-05
#> 4: Jun proto-oncogene, AP-1 transcription factor subunit 4.101e-05
#> 5: RAB30, member RAS oncogene family 1.000e-04
#> ---
#> 15566: DLG associated protein 2 9.999e-01
#> 15567: calcium and integrin binding 1 9.998e-01
#> 15568: spermatogenesis associated 2-like 1.000e+00
#> 15569: chloride voltage-gated channel Kb NA
#> 15570: PDGFA associated protein 1 NA
#> corrected_pvalue rank contrast_134441_coefficient
#> <num> <num> <num>
#> 1: 0.0441 6.436e-05 1.2514
#> 2: 0.1202 9.655e-05 0.9971
#> 3: 0.1478 1.000e-04 0.5632
#> 4: 0.2548 2.000e-04 1.2275
#> 5: 0.4532 2.000e-04 0.2237
#> ---
#> 15566: 1.0000 9.998e-01 0.1226
#> 15567: 1.0000 9.997e-01 0.1435
#> 15568: 1.0000 9.999e-01 0.1362
#> 15569: NA 1.000e+00 NA
#> 15570: NA 1.000e+00 NA
#> contrast_134441_log2fc contrast_134441_tstat contrast_134441_pvalue
#> <num> <num> <num>
#> 1: 1.2514 5.1513 0.0003
#> 2: 0.9971 4.3160 0.0012
#> 3: 0.5632 2.8673 0.0151
#> 4: 1.2275 3.8705 0.0025
#> 5: 0.2237 1.5604 0.1465
#> ---
#> 15566: 0.1226 1.0040 0.3366
#> 15567: 0.1435 1.2201 0.2475
#> 15568: 0.1362 0.6501 0.5288
#> 15569: NA NA NA
#> 15570: NA NA NA
#>