Compute differentially expressed genes (Affymetrix probes) (workflow) - Revision history

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;Workflow title
:Compute differentially expressed genes (Affymetrix probes)
;Provider
:[[GeneXplain GmbH]]
== Workflow overview ==
[[File:Compute-differentially-expressed-genes-Affymetrix-probes-workflow-overview.png|400px]]
== Description ==
This workflow is designed to identify upregulated, downregulated and non-changed genes for experimental data with three and more data points for each experiment and control.

As input, the normalized data with Affymetrix probeset IDs can be submitted.

Such normalized files are resulting from the output of the “Normalize data” procedure under “analyses/Methods/Data normalization/Normalize Affymetrix experiment and control”.

At the next step, p-value is calculated for up-and down-regulated probeset IDs. This workflow applies Student T-test for p-value calculation, and therefore the number of data points should be at least three for each experiment and control.

Simultaneously, log fold change is calculated for each probeset ID, and as the result of this step, a table is produced in which both LogFoldChange and p-value are assigned to each probeset ID.

Further, this table is filtered by several conditions in parallel, to identify upregulated, downregulated, and non-changed Affymetrix probeset IDs.

The filtering criteria are set as the following.

For upregulated probes: LogFoldChange>0.5 and -log_P_value_>3.

For downregulated probes: LogFoldChange<-0.5 and -log_P_value_<-3.

For non-changed probes: LogFoldChange<0.01 and LogFoldChange>-0.01

Resulting tables of the upregulated, downregulated, and non-changed Affymetrix probeset IDs are annotated with additional information, gene description, gene symbols, species.

Finally, these tables are converted into the tables of genes. Two tables are produced, with Ensembl Gene IDs and with Entrez IDs.

== Parameters ==
;Experiment normalized
;Control normalized
;Species
;Results folder

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 [[File:Compute-differentially-expressed-genes-Affymetrix-probes-workflow-overview.png|400px]]
 == Description ==
-This workflow is designed to identify up-regulated, down-regulated and non-changed genes for experimental data with three and more data points for each experiment and control.
+This workflow is designed to identify differentially expressed genes from an experiment data set compared to a control data set.  Normalized data with Affymetrix probeset IDs can be submitted as input. Such normalized files are the output of the workflow [http://test.genexplain.com/bioumlweb/#de=analyses/Methods/Data normalization/Normalize Affymetrix experiment and control Normalize Affymetrix experiment and control].
-As input, normalized data with Affymetrix probeset IDs can be submitted. Such normalized files are the output of the “Normalize data” procedure.
+In the first step, the up- and down-regulated probes are identified and log fold change values are calculated for all probes using the ''Up and Down Identification ''analysis. This analysis applies Student’s T-test and calculates p-values, thus the number of data points should be at least three for each experiment data set and control data set. A histogram with the log fold change distribution from the whole experiment is drawn and given output image file.
-In the next step, p-values for up- and down-regulated probes are calculated for all probes using the “Up and Down Identification”'' ''analysis. This analysis applies Student’s T-test for p-value calculation, thus the number of data points should be at least three for each experiment and control.
+In addition the results are filtered by different conditions in parallel applying the ''Filter table'' method, to identify up-regulated, down-regulated, and non-changed Affymetrix probeset IDs. The filtering criteria are set as follows:
-Simultaneously, the log fold change is calculated for each probeset ID, and as the result of this step, a table is produced in which both log fold change and p-value are assigned to each probeset ID. A histogram with log fold change distribution is calculated and generated as one of the output files.
+'''For up-regulated probes: LogFoldChange>0.5 and -log_P_value_>3.
-−
-In addition this table is filtered by several conditions in parallel applying the “Filter table” method, to identify up-regulated, down-regulated, and non-changed Affymetrix probeset IDs. The filtering criteria are set as follows:
-−
 For up-regulated probes: LogFoldChange>0.5 and -log_P_value_>3.
 For down- regulated probes: LogFoldChange<-0.5 and -log_P_value_<-3.
-For non-changed genes : LogFoldChange<0.002 and LogFoldChange>-0.002
+For non-changed genes : LogFoldChange<0.002 and LogFoldChange>-0.002'''
-The resulting tables of up-regulated, down-regulated, and non-changed Affymetrix probeset IDs are converted into a gene set via the “Convert table” method and annotated with additional information, gene descriptions, gene symbols, and species via “Annotate table”. Two tables are produced, one with Ensembl Gene IDs and one with Entrez IDs.
+The resulting tables of up-regulated, down-regulated, and non-changed Affymetrix probeset IDs are converted into a gene table with the ''Convert table'' method and annotated with additional information (gene descriptions, gene symbols, and species) via ''Annotate table'' method.
-A new folder is generated as output containing Ensemble and Entrez gene tables for up-regulated, down-regulated, up- and down-regulated combined, and non-changed genes. After completion of the workflow, a script generates a report which gives a summary of the workflow output files.
+A result folder is generated and automatically named corresponding to the experiment data set name. This resulting folder contains all tables, the histogramm and a summary HTML report.
 == Parameters ==

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 :Compute differentially expressed genes (Affymetrix probes)
 ;Provider
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 == Workflow overview ==
 [[File:Compute-differentially-expressed-genes-Affymetrix-probes-workflow-overview.png|400px]]