Description Usage Arguments Value Examples
View source: R/function_DESeq2.R
Run DESeq2 gene Differential Expression Analysis (DEA).
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name |
A character string indicating the desired values to be used in next analysis. For instance, "HIF3A" in the legacy gene expression matrix, "mir-1307" in the miRNA quantification matrix, or "HER2" in the protein quantification matrix. |
core_number |
A numeric value indicating how many CPU cores should be used in the analysis. The default value is 2. |
test |
A character string indicating which test should be used:
|
group_gen |
A character string of the groups generation function:
|
clinical_pair |
A character string containing one of the group pairs
selected after statistical analysis runned in |
fc_cutoff |
Numerical value indicating the maximum value for Fold
Change '(FC). The default is |
work_dir |
A character string specifying the path to work directory. |
tumor |
A character string contaning one of the 33 tumors available in
the TCGA project. For instance, the |
fdr_cutoff |
Numerical value indicating the maximum value for FDR
values. The default is |
width |
Graphical parameters. See par for more
details. As default |
height |
Graphical parameters. See par for more
details. As default |
res |
Graphical parameters. See par for more
details. As default |
unit |
Graphical parameters. See par for more
details. As default |
image_format |
A character string indicating which image_format will be used. It could be "png" or "svg". The only unit available in "svg" is inches ('in'). The default is "png". |
env |
A character string containing the environment name that should be used. If none has been set yet, the function will create one in global environment following the standard criteria:
|
cooks_cutoff |
Cooks distance remove outliers from the analysis; More
details in DESeq2 results page. The default is |
A matrix with DE genes in row and statistical values in columns.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | library(DOAGDC)
# data already downloaded using the 'download_gdc' function
concatenate_expression("gene",
name = "HIF3A",
data_base = "legacy",
tumor = "CHOL",
work_dir = "~/Desktop"
)
# separating gene HIF3A expression data patients in two groups
groups_identification_mclust("gene", 2,
name = "HIF3A",
modelName = "E",
env = CHOL_LEGACY_gene_tumor_data,
tumor = "CHOL"
)
# load not normalized data
concatenate_expression("gene",
normalization = FALSE,
name = "HIF3A",
data_base = "legacy",
tumor = "CHOL",
env = CHOL_LEGACY_gene_tumor_data,
work_dir = "~/Desktop"
)
# start DE analysis
dea_deseq2(
name = "HIF3A",
test = "LRT",
env = CHOL_LEGACY_gene_tumor_data,
group_gen = "mclust"
)
|
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