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Identification of differential genes using t-tests by R

Workflow Entry: Identification of differential genes using t-tests by R

Created at: 15/04/08 @ 15:37:42 Last updated: 01/07/08 @ 17:21:18

Version 2 (latest) (of 2)

Version created on: 15/04/08 @ 15:37:42 by: Peter Li | Revision comments Expand

Last edited on: 01/07/08 @ 17:21:18 by: Peter Li

Title: Identification of differential genes using t-tests by R

Type: Taverna 1

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Description

This workflow starts by retrieving the names of microarray datasets from the Maxd database. The user has to select sets of control and test data for analysis using t-tests by R. A list of significant differentially expressed genes is then analysed using the Go Term Finder tool which generates a list of GO terms associated with the genes. A CSV file containing the list of significant genes is also generated.

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Workflow Components

Inputs (0)

Processors (20)

Name	Type	Description
Ttest_pvalue	stringconstant
GoTermFinder_pvalue	stringconstant
getNamesUsingXPath	local	Parses the measurement names of microarray datasets from the XML output from maxdBrowse
flatten	local	Removes a layer of lists
performT_tests	rshell	This R script performs a series of t-tests for each gene expression level between its 2 input data sets.
mergeOutput1	beanshell	Merges the selected input data sets into a single data set
createFinalCSV	beanshell	Creates a text file in CSV format contain a list of the all the differentially expressed genes identified by the R script.
cleanCSV	beanshell	Removes unneccesary prefix text in the affy identifiers from the CSV file output generated by the R script
createGeneList	beanshell	Create a list of genes for analysis by the GOTermFinder service. Spurious genes are removed including those which have been annotated as questioable and hypothetical and therefore will not have a GO term asscoiated with them.
selectTestData	beanshell	Uses Java Swing classes to enable the user to select data sets for t-test analysis
getAffyIds	beanshell	Parses the affy identifiers from the CSV file
mergeOutput2	beanshell	Combines the selected data sets into a single data set
selectControlData	beanshell	Uses Java Swing classes to enable the user to select data sets for t-test analysis
getMeasurementNames	arbitrarywsdl	Querys the maxdload database using maxdBrowse to obtain a list of measurement names from the big experiment data stored there
queryMaxd1	arbitrarywsdl	Will take a list of Gene names, a list of Measurement names and a list of Column Types and produce a table. All values are coloured in relation to the a reference. In the list of Measurement names, the first Measurement listed is taken to be the reference. Formatted as text.
getGeneName	arbitrarywsdl	Gets the gene name for a given yeast open reading frame number See the Service entry for this web service.
analyseGenesPDFOutput	arbitrarywsdl	Analyses a list of genenames using the GOTermFinder service See the Service entry for this web service.
getTargetDescription	arbitrarywsdl	Gets a description of a given affy identifer using the YeastAffymapper service See the Service entry for this web service.
getTranscriptId	arbitrarywsdl	Gets the open reading frame number for a given affy identifier See the Service entry for this web service.
queryMaxd2	arbitrarywsdl	Will take a list of Gene names, a list of Measurement names and a list of Column Types and produce a table. All values are coloured in relation to the a reference. In the list of Measurement names, the first Measurement listed is taken to be the reference. Formatted as text.

Beanshells (8)

Name	Description	Inputs	Outputs
mergeOutput1	Merges the selected input data sets into a single data set	in	out
createFinalCSV	Creates a text file in CSV format contain a list of the all the differentially expressed genes identified by the R script.	affyIds orfs genenames descriptions	csv
cleanCSV	Removes unneccesary prefix text in the affy identifiers from the CSV file output generated by the R script	in	out
createGeneList	Create a list of genes for analysis by the GOTermFinder service. Spurious genes are removed including those which have been annotated as questioable and hypothetical and therefore will not have a GO term asscoiated with them.	listOfOrfs listOfGenenames listOfDescriptions	orfs spurious_genes
selectTestData	Uses Java Swing classes to enable the user to select data sets for t-test analysis	input	output
getAffyIds	Parses the affy identifiers from the CSV file	inList	outList
mergeOutput2	Combines the selected data sets into a single data set	in	out
selectControlData	Uses Java Swing classes to enable the user to select data sets for t-test analysis	input	output

Outputs (3)

Name	Description
pdf	A PDF document generated by the GoTermFinder service
csv	A text file in CSV format showing a list of differentially expressed genes and their annotations
spurious_genes	A text file in CSV format shoing a list of genes annotated as hypothetical, questionable, genomic sequences, etc. These genes do not have a GO term associated with them and so are removed from the list sent to the GoTermFinder service.

Links (28)

Source	Sink
GoTermFinder_pvalue:value	analyseGenesPDFOutput:pvalue
Ttest_pvalue:value	performT_tests:pvalue
cleanCSV:out	flatten:inputlist
createGeneList:orfs	analyseGenesPDFOutput:genes
createGeneList:spurious_genes	spurious_genes
flatten:outputlist	createFinalCSV:affyIds
flatten:outputlist	getAffyIds:inList
getAffyIds:outList	getGeneName:affyId
getAffyIds:outList	getTargetDescription:affyId
getAffyIds:outList	getTranscriptId:affyId
getGeneName:getGeneSymbolReturn	createFinalCSV:genenames
getGeneName:getGeneSymbolReturn	createGeneList:listOfGenenames
getMeasurementNames:return	getNamesUsingXPath:xml-text
getNamesUsingXPath:nodelist	selectControlData:input
getNamesUsingXPath:nodelist	selectTestData:input
getTargetDescription:getTargetDescriptionReturn	createFinalCSV:descriptions
getTargetDescription:getTargetDescriptionReturn	createGeneList:listOfDescriptions
getTranscriptId:getTranscriptIdReturn	createFinalCSV:orfs
getTranscriptId:getTranscriptIdReturn	createGeneList:listOfOrfs
mergeOutput1:out	performT_tests:control_csv
mergeOutput2:out	performT_tests:test_csv
performT_tests:file	cleanCSV:in
queryMaxd1:return	mergeOutput1:in
queryMaxd2:return	mergeOutput2:in
selectControlData:output	queryMaxd1:MeasurementNames
selectTestData:output	queryMaxd2:MeasurementNames
analyseGenesPDFOutput:analyseGenesPDFOutputReturn	pdf
createFinalCSV:csv	csv

Coordinations (1)

Controller	Target
mergeOutput1	selectTestData

Information Workflow Type

Taverna 1

Information Original Uploader

Peter Li

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Peter Li

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Information Statistics

1632 viewings

1475 downloads

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Citations (1)

1. Li, P., Castrillo, J. I., Velarde, G., Wassink, I., Soiland-Reyes, S., Owen, S., Withers, D., Oinn, T., Pocock, M. R., Goble, C. A., Oliver, S. G. & Kell, D. B., Performing statistical analyses on quantitative data in Taverna workflows: an example using R and maxdBrowse to identify differentially expressed genes from microarray data, BMC Bioinformatics 2008, 9:334, 07 August 2008, http://www.biomedcentral.com/1471-2105/9/334

Version History

Earliest Version:
[1] - Identification of differentially-expressed genes using R

Created on: Tuesday 15 April 2008 @ 15:37:42 (GMT)

Created by: Peter Li

Last edited on: Tuesday 15 April 2008 @ 15:41:25 (GMT)

Last edited by: Peter Li

Revision comments:

None

Latest Version:
[2] - Identification of differential genes using t-tests by R

Created on: Tuesday 15 April 2008 @ 15:37:42 (GMT)

Created by: Peter Li

Last edited on: Tuesday 01 July 2008 @ 17:21:18 (GMT)

Last edited by: Peter Li

Revision comments:

Replaced the cleanGenenames processor with a new Beanshell script called createGeneNames. This new processor generates a list of genes using their yeast gene name or open reading frame number if it does not have a standard yeast name.

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Other workflows that use similar services (3)

Only the first 2 workflows that use similar services are shown. View all workflows that use these services.

Taverna 1

Original Uploader

Peter Li

Identification of differential genes using the LIMMA Bioconductor package within R (v1)

Created: 02/07/08 @ 11:24:12 | Last updated: 02/07/08 @ 11:28:21

Credits: Peter Li

License: Creative Commons Attribution-Share Alike 3.0 Unported License

This workflow starts by retrieving the names of microarray datasets from the Maxd database. The user has to select sets of control and test data which are then analysed by the LIMMA Bioconductor package in an R script. This produces a list of significant differentially expressed genes which is then analysed using the Go Term Finder tool to generate a PDF report of the common GO terms associated with the genes. A CSV file containing the list of sign...

Rating: 0.0 / 5 (0 ratings) | Versions: 1 | Reviews: 0 | Comments: 0 | Citations: 0

Viewed: 584 times | Downloaded: 224 times

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