Welcome to the AutoRel (auto_relevant or autorrel) model.
To be run, it requires the following installations:
- R language
- DESeq2 R package
One can access "AutoRel/scripts/autorrel/run_autorrel.R" to introduce the data and run the model.
After running DESeq2, 4 files/variables that can be recovered from the DESeq2 output are needed:
-
norm_counts: These are the normalized counts.
- They can be obtained with the following line:
norm_counts = DESeq2::counts(object = dds, normalized = T) -
res: this is the results object of DESeq2, where the statistical results are stored.
- res can be obtained with the following line:
res <- results(dds) -
coldata: dataframe which you specified in DESeq2 to split between control and treatment For example, if your DESeq2 code contained the following line:
dds = DESeqDataSetFromMatrix(countData = cts, colData = coldata, design = ~ Group)
-
contrast_group: One last string character you need to specify This is the column name of your 'coldata' data.frame Using the prior example:
dds = DESeqDataSetFromMatrix(countData = cts, colData = coldata, design = ~ Group)
contrast_group = 'Group' -
output_path: Path where the output of the autorrel model will be saved
output_path = 'output/example_files/'