Retrieve raw expression data of a dataset
A numerical dataset identifier or a dataset short name
Quantitation type id. These can be acquired
using get_dataset_quantitation_types function. This endpoint can
only return non-processed quantitation types.
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.
If raw is FALSE (default), a data table of the expression matrix for the queried dataset. If raw is TRUE, returns the binary file in raw form.
q_types <- get_dataset_quantitation_types("GSE59918")
get_dataset_raw_expression("GSE59918", q_types$id[q_types$name == "Counts"])
#> Probe GeneSymbol
#> <int> <char>
#> 1: 100034253 Gnl3l
#> 2: 100036765 Ccdc92
#> 3: 100049583 Trex1
#> 4: 100101439
#> 5: 100124593 Cxcr6
#> ---
#> 31212: 94338 Smpd3
#> 31213: 94339 Mmp23
#> 31214: 94340 Acsl5
#> 31215: 94341 Kcnj13
#> 31216: 94342 Bag6
#> GeneName NCBIid
#> <char> <int>
#> 1: G protein nucleolar 3 like 100034253
#> 2: coiled-coil domain containing 92 100036765
#> 3: three prime repair exonuclease 1 100049583
#> 4: NA
#> 5: C-X-C motif chemokine receptor 6 100124593
#> ---
#> 31212: sphingomyelin phosphodiesterase 3 94338
#> 31213: matrix metallopeptidase 23 94339
#> 31214: acyl-CoA synthetase long-chain family member 5 94340
#> 31215: potassium inwardly-rectifying channel, subfamily J, member 13 94341
#> 31216: BAG cochaperone 6 94342
#> rat hypothalamus Fru_rep1 rat hypothalamus Ctrl_rep4
#> <num> <num>
#> 1: 1191.0 729.0
#> 2: 4681.6 4629.4
#> 3: 420.0 373.0
#> 4: 0.0 0.0
#> 5: 4.0 6.0
#> ---
#> 31212: 1004.0 703.0
#> 31213: 133.0 130.0
#> 31214: 581.0 390.0
#> 31215: 85.0 282.0
#> 31216: 5406.0 4690.0
#> rat hypothalamus Fru_rep2 rat hypothalamus Fru_rep3
#> <num> <num>
#> 1: 1224.0 1187.0
#> 2: 4380.2 4158.3
#> 3: 356.0 416.0
#> 4: 0.0 0.0
#> 5: 3.0 2.0
#> ---
#> 31212: 926.0 913.0
#> 31213: 79.0 141.0
#> 31214: 524.0 459.0
#> 31215: 6.0 142.0
#> 31216: 5364.0 5576.0
#> rat hypothalamus Ctrl_rep1 rat hippocampus Fru_rep3
#> <num> <num>
#> 1: 1059.0 589.00
#> 2: 4147.9 782.76
#> 3: 422.0 60.00
#> 4: 0.0 0.00
#> 5: 4.0 1.00
#> ---
#> 31212: 880.0 1442.00
#> 31213: 135.0 35.00
#> 31214: 518.0 828.00
#> 31215: 237.0 281.00
#> 31216: 5472.0 1594.00
#> rat hippocampus Fru_rep1 rat hypothalamus Fru_rep4
#> <num> <num>
#> 1: 834.00 263.0
#> 2: 868.61 3229.1
#> 3: 66.00 449.0
#> 4: 0.00 0.0
#> 5: 1.00 0.0
#> ---
#> 31212: 1699.00 406.0
#> 31213: 17.00 85.0
#> 31214: 1215.00 310.0
#> 31215: 2100.00 73.0
#> 31216: 2016.00 3896.0
#> rat hypothalamus Ctrl_rep3 rat hippocampus Ctrl_rep3
#> <num> <num>
#> 1: 932.0 1126.0
#> 2: 3527.7 1273.7
#> 3: 345.0 72.0
#> 4: 1.0 0.0
#> 5: 7.0 0.0
#> ---
#> 31212: 883.0 2456.0
#> 31213: 146.0 25.0
#> 31214: 594.0 1412.0
#> 31215: 246.0 269.0
#> 31216: 4698.0 2807.0
#> rat hippocampus Ctrl_rep2 rat hippocampus Ctrl_rep4
#> <num> <num>
#> 1: 770.00 648.00
#> 2: 871.83 768.66
#> 3: 55.00 64.00
#> 4: 0.00 0.00
#> 5: 0.00 2.00
#> ---
#> 31212: 1620.00 1541.00
#> 31213: 16.00 51.00
#> 31214: 1177.00 1431.00
#> 31215: 641.00 1199.00
#> 31216: 1626.00 1978.00
#> rat hippocampus Ctrl_rep1 rat hippocampus Fru_rep4
#> <num> <num>
#> 1: 539.00 1090.00
#> 2: 774.63 684.74
#> 3: 59.00 57.00
#> 4: 0.00 0.00
#> 5: 2.00 1.00
#> ---
#> 31212: 1176.00 2361.00
#> 31213: 33.00 21.00
#> 31214: 845.00 1863.00
#> 31215: 1165.00 2345.00
#> 31216: 1661.00 2064.00
#> rat hippocampus Fru_rep2 rat hypothalamus Ctrl_rep2
#> <num> <num>
#> 1: 769.00 953.0
#> 2: 862.79 4084.7
#> 3: 96.00 388.0
#> 4: 0.00 0.0
#> 5: 9.00 0.0
#> ---
#> 31212: 1736.00 809.0
#> 31213: 83.00 127.0
#> 31214: 1254.00 484.0
#> 31215: 711.00 120.0
#> 31216: 1881.00 4465.0