Lymphoma type prediction based on microarray data

Created: 2010-05-11 19:04:30 Last updated: 2010-05-11 19:04:32

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Scientific value

Using gene-expression patterns associated with DLBCL and FL to predict the lymphoma type of an unknown sample.
Using SVM (Support Vector Machine) to classify data, and predicting the tumor types of unknown examples.

Steps

Querying training data from experiments stored in caArray.
Preprocessing, or normalize the microarray data.
Adding training and testing data into SVM service to get classification result.

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Titles (1)

Descriptions (1)

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Inputs (0)

Processors (57)

Name	Type	Description
Beanshell_3	beanshell	Script import java.io.File; import java.util.ArrayList; import java.util.List; import java.io.IOException; import java.io.StringReader; import java.io.StringWriter; import javax.xml.parsers.DocumentBuilder; import javax.xml.parsers.DocumentBuilderFactory; import javax.xml.parsers.ParserConfigurationException; import javax.xml.transform.Transformer; import javax.xml.transform.TransformerException; import javax.xml.transform.TransformerFactory; import javax.xml.transform.dom.DOMSource; import javax.xml.transform.stream.StreamResult; import javax.xml.xpath.XPath; import javax.xml.xpath.XPathConstants; import javax.xml.xpath.XPathExpressionException; import javax.xml.xpath.XPathFactory; import org.w3c.dom.Document; import org.w3c.dom.Element; import org.w3c.dom.Node; import org.w3c.dom.NodeList; import org.xml.sax.InputSource; import org.xml.sax.SAXException; try{ DocumentBuilderFactory docBuilderFactory = DocumentBuilderFactory.newInstance(); docBuilderFactory.setNamespaceAware(true); DocumentBuilder docBuilder; docBuilder = docBuilderFactory.newDocumentBuilder(); Document doc2 = docBuilder.parse( new InputSource(new StringReader(i))); Element el = doc2.getDocumentElement(); XPath xpath = XPathFactory.newInstance().newXPath(); String findDataSet = "//*[local-name()='DataSet' and namespace-uri()='gme://caArray.caBIG/2.1/gov.nih.nci.caarray.domain.data']/@id"; //String DataSetId = (String) xpath.evaluate(findDataSet, el, XPathConstants.STRING); //String DataSetId = (String) xpath.evaluate(findDataSet, el, XPathConstants.STRING); //o = ""; NodeList nodes = (NodeList) xpath.evaluate(findDataSet, el, XPathConstants.NODESET); StringBuffer cql = new StringBuffer(""); //String DataSetId = (String) xpath.evaluate(findDataSet, el, XPathConstants.STRING); NodeList DataSetIdNodes = (NodeList) xpath.evaluate(findDataSet, el, XPathConstants.NODESET); for (int i=0;i"); } cql.append(""); o = cql.toString(); } catch (ParserConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (SAXException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (XPathExpressionException e) { // TODO Auto-generated catch block e.printStackTrace(); }
Beanshell_2	beanshell	Script import java.io.File; import java.util.ArrayList; import java.util.List; import java.io.IOException; import java.io.StringReader; import java.io.StringWriter; import javax.xml.parsers.DocumentBuilder; import javax.xml.parsers.DocumentBuilderFactory; import javax.xml.parsers.ParserConfigurationException; import javax.xml.transform.Transformer; import javax.xml.transform.TransformerException; import javax.xml.transform.TransformerFactory; import javax.xml.transform.dom.DOMSource; import javax.xml.transform.stream.StreamResult; import javax.xml.xpath.XPath; import javax.xml.xpath.XPathConstants; import javax.xml.xpath.XPathExpressionException; import javax.xml.xpath.XPathFactory; import org.w3c.dom.Document; import org.w3c.dom.Element; import org.w3c.dom.Node; import org.w3c.dom.NodeList; import org.xml.sax.InputSource; import org.xml.sax.SAXException; try{ DocumentBuilderFactory docBuilderFactory = DocumentBuilderFactory.newInstance(); docBuilderFactory.setNamespaceAware(true); DocumentBuilder docBuilder; docBuilder = docBuilderFactory.newDocumentBuilder(); Document doc2 = docBuilder.parse( new InputSource(new StringReader(i))); Element el = doc2.getDocumentElement(); XPath xpath = XPathFactory.newInstance().newXPath(); String findDerivedArrayData = "//[local-name()='DerivedArrayData' and namespace-uri()='gme://caArray.caBIG/2.1/gov.nih.nci.caarray.domain.data'][contains(@name,'.CHP')]/@id"; String findClass = "//[local-name()='FactorValue' and namespace-uri()='gme://caArray.caBIG/2.1/gov.nih.nci.caarray.domain.project']/@value"; //String DerivedArrayDataId = (String) xpath.evaluate(findDerivedArrayData, el, XPathConstants.STRING); //String DerivedClass = (String) xpath.evaluate(findClass, el, XPathConstants.STRING); NodeList DerivedArrayDataIdNodes = (NodeList) xpath.evaluate(findDerivedArrayData, el, XPathConstants.NODESET); NodeList DerivedClassNodes = (NodeList) xpath.evaluate(findClass, el, XPathConstants.NODESET); System.out.println(DerivedArrayDataIdNodes.getLength()); System.out.println(DerivedClassNodes.getLength()); StringBuffer cql = new StringBuffer(""); //o = ""; for (int i=0;i"); } cql.append(""); //type = DerivedClass; o = cql.toString(); } catch (ParserConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (SAXException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (XPathExpressionException e) { // TODO Auto-generated catch block e.printStackTrace(); }
Beanshell	beanshell	Script import java.io.File; import java.util.ArrayList; import java.util.List; import java.io.IOException; import java.io.StringReader; import java.io.StringWriter; import javax.xml.parsers.DocumentBuilder; import javax.xml.parsers.DocumentBuilderFactory; import javax.xml.parsers.ParserConfigurationException; import javax.xml.transform.Transformer; import javax.xml.transform.TransformerException; import javax.xml.transform.TransformerFactory; import javax.xml.transform.dom.DOMSource; import javax.xml.transform.stream.StreamResult; import javax.xml.xpath.XPath; import javax.xml.xpath.XPathConstants; import javax.xml.xpath.XPathExpressionException; import javax.xml.xpath.XPathFactory; import org.w3c.dom.Document; import org.w3c.dom.Element; import org.w3c.dom.Node; import org.w3c.dom.NodeList; import org.xml.sax.InputSource; import org.xml.sax.SAXException; try{ DocumentBuilderFactory docBuilderFactory = DocumentBuilderFactory.newInstance(); docBuilderFactory.setNamespaceAware(true); DocumentBuilder docBuilder; docBuilder = docBuilderFactory.newDocumentBuilder(); Document doc2 = docBuilder.parse( new InputSource(new StringReader(i))); Element el = doc2.getDocumentElement(); XPath xpath = XPathFactory.newInstance().newXPath(); String findHybridizationExpression = "//*[local-name()='Hybridization' and namespace-uri()='gme://caArray.caBIG/2.1/gov.nih.nci.caarray.domain.hybridization']/@id"; NodeList nodes = (NodeList) xpath.evaluate(findHybridizationExpression, el, XPathConstants.NODESET); System.out.println(nodes.getLength()); //ArrayList o2 = new ArrayList(); //o = new ArrayList(); StringBuffer cql = new StringBuffer(""); for (int i=0;i"); //if(i<17){ //o.add(n.getTextContent()); //} } cql.append(""); o = cql.toString(); } catch (ParserConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (SAXException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (XPathExpressionException e) { // TODO Auto-generated catch block e.printStackTrace(); }
dataXML	xmlsplitter
PreprocessDatasetParameterSetXML1	xmlsplitter
dataXML1	xmlsplitter
parametersXML4	xmlsplitter
cqlQueryXML2	xmlsplitter
parametersXML10	xmlsplitter
trainingDataXML	xmlsplitter
Beanshell_4	beanshell	Script import java.io.File; import java.util.ArrayList; import java.util.List; import java.io.IOException; import java.io.StringReader; import java.io.StringWriter; import javax.xml.parsers.DocumentBuilder; import javax.xml.parsers.DocumentBuilderFactory; import javax.xml.parsers.ParserConfigurationException; import javax.xml.transform.Transformer; import javax.xml.transform.TransformerException; import javax.xml.transform.TransformerFactory; import javax.xml.transform.dom.DOMSource; import javax.xml.transform.stream.StreamResult; import javax.xml.xpath.XPath; import javax.xml.xpath.XPathConstants; import javax.xml.xpath.XPathExpressionException; import javax.xml.xpath.XPathFactory; import org.w3c.dom.Document; import org.w3c.dom.Element; import org.w3c.dom.Node; import org.w3c.dom.NodeList; import org.xml.sax.InputSource; import org.xml.sax.SAXException; try{ DocumentBuilderFactory docBuilderFactory = DocumentBuilderFactory.newInstance(); docBuilderFactory.setNamespaceAware(true); DocumentBuilder docBuilder; docBuilder = docBuilderFactory.newDocumentBuilder(); Document doc2 = docBuilder.parse( new InputSource(new StringReader(i))); Element el = doc2.getDocumentElement(); XPath xpath = XPathFactory.newInstance().newXPath(); String findHybridizationData = "//*[local-name()='HybridizationData' and namespace-uri()='gme://caArray.caBIG/2.1/gov.nih.nci.caarray.domain.data']/@id"; //String HybridizationDataId = (String) xpath.evaluate(findHybridizationData, el, XPathConstants.STRING); StringBuffer cql = new StringBuffer(""); NodeList HybridizationDataIdNodes = (NodeList) xpath.evaluate(findHybridizationData, el, XPathConstants.NODESET); for (int i=0;i"); } cql.append(""); o = cql.toString(); //o = ""; } catch (ParserConfigurationException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (SAXException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } catch (XPathExpressionException e) { // TODO Auto-generated catch block e.printStackTrace(); }
preprocessDatasetParameterSetXML2	xmlsplitter
cqlQueryXML1	xmlsplitter
PreprocessDatasetParameterSetXML3	xmlsplitter
parametersXML13	xmlsplitter
cqlQueryXML4	xmlsplitter
parametersXML6	xmlsplitter
Beanshell_6	beanshell	Script import java.io.; import java.util.ArrayList; import java.util.List; import java.util.zip.GZIPInputStream; import javax.xml.parsers.DocumentBuilder; import javax.xml.parsers.DocumentBuilderFactory; import javax.xml.parsers.ParserConfigurationException; import javax.xml.transform.Transformer; import javax.xml.transform.TransformerException; import javax.xml.transform.TransformerFactory; import javax.xml.transform.dom.DOMSource; import javax.xml.transform.stream.StreamResult; import javax.xml.xpath.XPath; import javax.xml.xpath.XPathConstants; import javax.xml.xpath.XPathExpressionException; import javax.xml.xpath.XPathFactory; import org.w3c.dom.Document; import org.w3c.dom.Element; import org.w3c.dom.Node; import org.w3c.dom.NodeList; import org.xml.sax.InputSource; import org.xml.sax.SAXException; import java.util.zip.GZIPInputStream; public int getRowSize(String gctLineString){ int columnSize = 0; for(int i=0;i"); trainingClassMembershipXMLString.append("DLBCLFL"); trainingClassMembershipXMLString.append(""+trainingType.length+""); for(int i=0;i"+trainingType[i]+""); } for(int i=0;itrainingSample_"+i+""); } trainingClassMembershipXMLString.append(""); //System.out.println(trainingClassMembershipXMLString); //test StringBuffer testClassMembershipXMLString = new StringBuffer (""); testClassMembershipXMLString.append("DLBCLFL"); testClassMembershipXMLString.append(""+testType.length+""); for(int i=0;i"+testType[i]+""); } for(int i=0;itestSample_"+i+""); } testClassMembershipXMLString.append(""); //System.out.println(testClassMembershipXMLString); //construct Data elements //training data----------------------------------------------------------------- StringBuffer trainingDataXMLString = new StringBuffer (""); // contains four : // 1 add the base64value trainingDataXMLString.append("data" +trainingMicroArrayData.length+","+trainingMicroArrayData[0].length+ "datadouble"+ trainingMicroArrayBase64String+ ""); //2 add markerNames trainingDataXMLString.append("markerNames"); for(int i=0;imarkerNamesstringGene_"+i+""); } trainingDataXMLString.append(""); //3 add markerDescriptions trainingDataXMLString.append("markerDescriptions"); for(int i=0;imarkerDescriptionsstringGene_"+i+""); } trainingDataXMLString.append(""); //4 add sampleNames trainingDataXMLString.append("sampleNames"); for(int i=0;isampleNamesstringtrainingSample_"+i+""); } trainingDataXMLString.append(""); trainingDataXMLString.append(""); //test data----------------------------------------------------------------- StringBuffer testDataXMLString = new StringBuffer (""); // contains four : // 1 add the base64value testDataXMLString.append("data" +testMicroArrayData.length+","+testMicroArrayData[0].length+ "datadouble"+ testMicroArrayBase64String+ ""); //2 add markerNames testDataXMLString.append("markerNames"); for(int i=0;imarkerNamesstringGene_"+i+""); } testDataXMLString.append(""); //3 add markerDescriptions testDataXMLString.append("markerDescriptions"); for(int i=0;imarkerDescriptionsstringGene_"); testDataXMLString.append(i); testDataXMLString.append(""); } testDataXMLString.append(""); //4 add sampleNames testDataXMLString.append("sampleNames"); for(int i=0;isampleNamesstringtestSample_"+i+""); } testDataXMLString.append(""); testDataXMLString.append(""); //System.out.println(testDataXMLString); trainingClass = trainingClassMembershipXMLString.toString(); testClass = testClassMembershipXMLString.toString(); trainingDataString = trainingDataXMLString.toString(); testDataString = testDataXMLString.toString(); / //write the string to some files for testing purpose File trainingClassMembershipFile = new File(dir+"trainingClassMembership.xml"); File testClassMembershipFile = new File(dir+"testClassMembership.xml"); File trainingDataFile = new File(dir+"trainingData.xml"); try { //use buffering Writer trainingClassMembershipFileOutput = new BufferedWriter(new FileWriter(trainingClassMembershipFile)); Writer testClassMembershipFileOutput = new BufferedWriter(new FileWriter(testClassMembershipFile)); Writer trainingDataFileOutput = new BufferedWriter(new FileWriter(trainingDataFile)); OutputStream os = new FileOutputStream(dir+"testData.xml"); try { //FileWriter always assumes default encoding is OK! trainingClassMembershipFileOutput.write(new String(trainingClassMembershipXMLString)); testClassMembershipFileOutput.write(new String(testClassMembershipXMLString)); trainingDataFileOutput.write(new String(trainingDataXMLString)); //testDataFileOutput.write(testDataXMLString.toString()); byte [] bytes = testDataXMLString.toString().getBytes(); os.write(bytes); os.close(); System.out.println("Finished file writing."); } finally { trainingClassMembershipFileOutput.close(); testClassMembershipFileOutput.close(); trainingDataFileOutput.close(); } } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } */
cqlQueryXML	xmlsplitter
testClassXML	xmlsplitter
parametersXML9	xmlsplitter
getExperiment	wsdl	Wsdl http://array.nci.nih.gov/wsrf/services/cagrid/CaArraySvc?wsdl Wsdl Operation query
performAnalysis	wsdl	Wsdl http://node255.broad.mit.edu:6060/wsrf/services/cagrid/SVM?wsdl Wsdl Operation performAnalysis
parametersXML5	xmlsplitter
testDataXML	xmlsplitter
preProcessTrainingData	wsdl	Wsdl http://node255.broad.mit.edu:6060/wsrf/services/cagrid/PreprocessDatasetSTATMLService?wsdl Wsdl Operation performAnalysis
parametersXML1	xmlsplitter
preProcessTestData	wsdl	Wsdl http://node255.broad.mit.edu:6060/wsrf/services/cagrid/PreprocessDatasetSTATMLService?wsdl Wsdl Operation performAnalysis
CQLQueryResultCollectionXML	xmlsplitter
parametersXML12	xmlsplitter
parametersXML	xmlsplitter
parametersXML8	xmlsplitter
parametersXML11	xmlsplitter
parametersXML2	xmlsplitter
preprocessDatasetParameterSetXML	xmlsplitter
trainingClassXML	xmlsplitter
parametersXML3	xmlsplitter
parametersXML14	xmlsplitter
getHybridizationData	wsdl	Wsdl http://array.nci.nih.gov/wsrf/services/cagrid/CaArraySvc?wsdl Wsdl Operation query
getDerivedArrayData	wsdl	Wsdl http://array.nci.nih.gov/wsrf/services/cagrid/CaArraySvc?wsdl Wsdl Operation query
getHybridization	wsdl	Wsdl http://array.nci.nih.gov:80/wsrf/services/cagrid/CaArraySvc?wsdl Wsdl Operation query
parametersXML7	xmlsplitter
getDataSet	wsdl	Wsdl http://array.nci.nih.gov/wsrf/services/cagrid/CaArraySvc?wsdl Wsdl Operation query
cqlQueryXML3	xmlsplitter
ceiling	stringconstant	Value 2.1
columnThreshold	stringconstant	Value 0.0
filterFlag	stringconstant	Value false
logBaseTwo	stringconstant	Value false
maxSigmaBinning	stringconstant	Value 1
minChange	stringconstant	Value 3.0
minDelta	stringconstant	Value 100.0
numberOfColumnsAboveThreshold	stringconstant	Value 1
numExclude	stringconstant	Value 0
preprocessingFlag	stringconstant	Value no-disc-or-norm
probabilityThreshold	stringconstant	Value 1.0
threshold	stringconstant	Value 20.0
CQLQuery	stringconstant	Value

Beanshells (5)

Name	Inputs	Outputs
Beanshell_3	i	o
Beanshell_2	i	o type
Beanshell	i	o
Beanshell_4	i	o
Beanshell_6	i hybridizationString	trainingClass testClass trainingDataString testDataString

Outputs (1)

Name	Description
classification

Datalinks (73)

Source	Sink
parametersXML5:CQLQueryResultCollection	Beanshell_3:i
parametersXML3:CQLQueryResultCollection	Beanshell_2:i
CQLQueryResultCollectionXML:ObjectResult	Beanshell:i
Beanshell_6:testDataString	dataXML:Data
threshold:value	PreprocessDatasetParameterSetXML1:threshold
numExclude:value	PreprocessDatasetParameterSetXML1:numExclude
preprocessingFlag:value	PreprocessDatasetParameterSetXML1:preprocessingFlag
logBaseTwo:value	PreprocessDatasetParameterSetXML1:logBaseTwo
filterFlag:value	PreprocessDatasetParameterSetXML1:filterFlag
minDelta:value	PreprocessDatasetParameterSetXML1:minDelta
ceiling:value	PreprocessDatasetParameterSetXML1:ceiling
minChange:value	PreprocessDatasetParameterSetXML1:minChange
columnThreshold:value	PreprocessDatasetParameterSetXML1:columnThreshold
maxSigmaBinning:value	PreprocessDatasetParameterSetXML1:maxSigmaBinning
probabilityThreshold:value	PreprocessDatasetParameterSetXML1:probabilityThreshold
numberOfColumnsAboveThreshold:value	PreprocessDatasetParameterSetXML1:numberOfColumnsAboveThreshold
Beanshell_6:trainingDataString	dataXML1:Data
cqlQueryXML2:output	parametersXML4:cqlQuery
Beanshell_2:o	cqlQueryXML2:CQLQuery
trainingDataXML:output	parametersXML10:trainingData
testDataXML:output	parametersXML10:testData
trainingClassXML:output	parametersXML10:trainingClass
testClassXML:output	parametersXML10:testClass
parametersXML14:Data	trainingDataXML:Data
parametersXML7:CQLQueryResultCollection	Beanshell_4:i
PreprocessDatasetParameterSetXML3:output	preprocessDatasetParameterSetXML2:PreprocessDatasetParameterSet
Beanshell:o	cqlQueryXML1:CQLQuery
preprocessingFlag:value	PreprocessDatasetParameterSetXML3:preprocessingFlag
probabilityThreshold:value	PreprocessDatasetParameterSetXML3:probabilityThreshold
logBaseTwo:value	PreprocessDatasetParameterSetXML3:logBaseTwo
numberOfColumnsAboveThreshold:value	PreprocessDatasetParameterSetXML3:numberOfColumnsAboveThreshold
threshold:value	PreprocessDatasetParameterSetXML3:threshold
numExclude:value	PreprocessDatasetParameterSetXML3:numExclude
maxSigmaBinning:value	PreprocessDatasetParameterSetXML3:maxSigmaBinning
minChange:value	PreprocessDatasetParameterSetXML3:minChange
minDelta:value	PreprocessDatasetParameterSetXML3:minDelta
ceiling:value	PreprocessDatasetParameterSetXML3:ceiling
filterFlag:value	PreprocessDatasetParameterSetXML3:filterFlag
columnThreshold:value	PreprocessDatasetParameterSetXML3:columnThreshold
dataXML1:output	parametersXML13:data
preprocessDatasetParameterSetXML2:output	parametersXML13:preprocessDatasetParameterSet
Beanshell_4:o	cqlQueryXML4:CQLQuery
cqlQueryXML3:output	parametersXML6:cqlQuery
parametersXML9:CQLQueryResultCollection	Beanshell_6:i
parametersXML3:CQLQueryResultCollection	Beanshell_6:hybridizationString
CQLQuery:value	cqlQueryXML:CQLQuery
Beanshell_6:testClass	testClassXML:ClassMembership
getHybridizationData:parameters	parametersXML9:input
parametersXML:output	getExperiment:parameters
parametersXML10:output	performAnalysis:parameters
getDerivedArrayData:parameters	parametersXML5:input
parametersXML12:Data	testDataXML:Data
parametersXML13:output	preProcessTrainingData:parameters
getExperiment:parameters	parametersXML1:input
parametersXML11:output	preProcessTestData:parameters
parametersXML1:CQLQueryResultCollection	CQLQueryResultCollectionXML:input
preProcessTestData:parameters	parametersXML12:input
cqlQueryXML:output	parametersXML:cqlQuery
cqlQueryXML4:output	parametersXML8:cqlQuery
dataXML:output	parametersXML11:data
preprocessDatasetParameterSetXML:output	parametersXML11:preprocessDatasetParameterSet
cqlQueryXML1:output	parametersXML2:cqlQuery
PreprocessDatasetParameterSetXML1:output	preprocessDatasetParameterSetXML:PreprocessDatasetParameterSet
Beanshell_6:trainingClass	trainingClassXML:ClassMembership
getHybridization:parameters	parametersXML3:input
preProcessTrainingData:parameters	parametersXML14:input
parametersXML8:output	getHybridizationData:parameters
parametersXML4:output	getDerivedArrayData:parameters
parametersXML2:output	getHybridization:parameters
getDataSet:parameters	parametersXML7:input
parametersXML6:output	getDataSet:parameters
Beanshell_3:o	cqlQueryXML3:CQLQuery
performAnalysis:parameters	classification

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Information Workflow Type

Taverna 2

Information Uploader

Wei Tan

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9932 viewings

3888 downloads

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Citations (3)

1. Wei Tan, Ravi Madduri, Alexandra Nenadic, Stian Soiland-Reyes, Dinanath Sulakhe, Ian Foster, Carole A. Goble, caGrid Workflow Toolkit: A Taverna based workflow tool for cancer Grid, BMC Bioinformatics, 02 November 2010, http://www.biomedcentral.com/1471-2105/11/542, Accessed at: 03 September 2011

2. caArray, Experiment data: Diffuse large B-cell lymphoma outcome prediction , 23 April 2009, https://array.nci.nih.gov/caarray/project/golub-00095, Accessed at: 23 April 2009

3. MA Shipp et al, Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning, NATURE MEDICINE, 23 January 2002, http://www.broad.mit.edu/mpr/publications/projects/Lymphoma/Shipp_et_al_2002.pdf, Accessed at: 23 April 2009

Version History

In chronological order:

Lymphoma type prediction based on microarray data

Created by Wei Tan on Thursday 23 April 2009 17:10:37 (UTC)

Last edited by Wei Tan on Thursday 23 April 2009 17:15:00 (UTC)
Lymphoma type prediction based on microarray data

Created by Wei Tan on Friday 15 May 2009 18:13:17 (UTC)

Revision comment:

We added another classification service, KNN into the previous version.
Lymphoma type prediction based on microarray data

Created by Wei Tan on Tuesday 09 June 2009 22:10:13 (UTC)

Revision comment:

The workflow is now organized into three nested workflows.

With more explanations and instructions on input.

Output is more readible as a CSV string.
Lymphoma type prediction based on microarray data

Created by Wei Tan on Tuesday 28 July 2009 17:17:03 (UTC)

Revision comment:

Added the version presented at caBIG annual meeting 09.
Lymphoma type prediction based on microarray data

Created by Wei Tan on Monday 16 November 2009 06:16:23 (UTC)

Revision comment:

updated with the upgrade of caArray service v 2.3.
Lymphoma type prediction based on microarray data

Created by Wei Tan on Monday 16 November 2009 06:21:17 (UTC)

Revision comment:

update the workflow to work with caArray 2.3
Lymphoma type prediction based on microarray data

Created by Wei Tan on Tuesday 11 May 2010 19:04:30 (UTC)

Revision comment:

the genepattern grid services moved to broadinstitute.org

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Other workflows that use similar services (4)

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Taverna 2

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Wei Tan

caArray data retrieving (1)

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Query all the gene expression data in a caArray experiment. Returns a evenly divided gene expression data set with corresponding class information. They ca be later used as training and test data set in many classification algorithms.Query all the gene expression data in a caArray experiment. Returns a evenly divided gene expression data set with corresponding class information. They can be later used as training and test data set in many classification algorithms.

Created: 2009-11-23

Credits: Wei Tan

Taverna 2

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Wei Tan

genePattern data preprocessing (2)

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preprocess data set using genePattern preProces service, the input should be in genePattern STATML format. Configuration parameters can be adjusted by changing the default preprocess data set using genePattern preProces service, the input should be in genePattern STATML format.preprocess data set using genePattern preProces service, the input should be in genePattern STATML format. Configuration parameters can be adjusted by changing the string constants.

Created: 2010-05-24 | Last updated: 2010-05-24

Credits: Wei Tan

Lymphoma type prediction based on microarray data

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