Accessible Workflow | Identify and Validate a Consensus Signature Using Gene Expression Data

Galaxy Workflow ' Identify and Validate a Consensus Signature Using Gene Expression Data'


StepAnnotation
Step 1: Input dataset
select at runtime
Add the list of differentially expressed genes from the acute myeloid leukemia (AML) dataset.
Step 2: Input dataset
select at runtime
Add the list of differentially expressed genes from the multiple myeloma (MM) dataset.
Step 3: Remove beginning
21
Output dataset 'output' from step 1
Remove unnecessary headers from the ODF file.
Step 4: Remove beginning
21
Output dataset 'output' from step 2
Remove unnecessary headers from the ODF file.
Step 5: Filter
Output dataset 'out_file1' from step 3
c13>=1.5
0
Remove features with log2 fold change < 1.5.
Step 6: Filter
Output dataset 'out_file1' from step 4
c13>=1.5
0
Remove features with log2 fold change < 1.5.
Step 7: Filter
Output dataset 'out_file1' from step 5
c8<0.05
0
Remove features with FDR >= 0.05.
Step 8: Filter
Output dataset 'out_file1' from step 6
c8<0.05
0
Remove features with FDR >= 0.05.
Step 9: Compare two Datasets
Output dataset 'out_file1' from step 7
2
Output dataset 'out_file1' from step 8
2
Matching rows of 1st dataset
Generate a consensus gene set by overlapping the AML and MM datasets.
Step 10: Cut
c2
Tab
Output dataset 'out_file1' from step 9
Extract the Gene Symbols from the consensus gene set.
Step 11: GenomeSpace Exporter
Output dataset 'out_file1' from step 10
Not available.

No value found for 'Choose Target Directory'.

consensus.genelist.txt
Save the output to GenomeSpace.