Workflows

Lymphoma type prediction based on microar... (7)

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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.

Created: 2010-05-11 | Last updated: 2010-05-11

Credits: Wei Tan Ravi Stian Soiland-Reyes

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

Calculating frequencies of gene expression... (1)

This workflow retrieves data from the MaxD microarray database and calculates the frequencies of gene expression levels using an R script

Created: 2010-03-15

Credits: Peter Li

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

Pathways and Gene annotations forQTL region (1)

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This workflow searches for genes found from a set of differentially expressed probestes, in Human, Homo sapiens. The workflow requires an input human affymetrix probeset identifiers. Data is then extracted from BioMart to annotate each of the genes found in this region. The Entrez and UniProt identifiers are then sent to KEGG to obtain KEGG gene identifiers. The KEGG gene identifiers are then used to searcg for pathways in the KEGG pathway database.

Created: 2011-03-24 | Last updated: 2011-03-24

Credits: Paul Fisher

Gene to Pubmed (4)

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This workflow takes in a list of gene names and searches the PubMed database for corresponding articles. Any matches to the genes are then retrieved (abstracts only). These abstracts are then returned to the user.

Created: 2011-02-08 | Last updated: 2011-02-10

Credits: Paul Fisher

Attributions: Cosine vector space Extract Scientific Terms Rank Phenotype Terms Cosine vector space Rank Phenotype Terms Pathway to Pubmed Extract Scientific Terms

KEGG pathways common to both QTL and micro... (1)

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This workflow takes in two lists of KEGG pathway ids. These are designed to come from pathways found from genes in a QTL (Quantitative Trait Loci) region, and from pathways found from genes differentially expressed in a microarray study. By identifying the intersecting pathways from both studies, a more informative picture is obtained of the candidate processes involved in the expression of a phenotype

Created: 2010-11-15 | Last updated: 2010-11-15

Credits: Paul Fisher

Pathways and Gene annotations for RefSeq ids (1)

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This workflow searches for genes which were found to be differentially expressed from a microarray study in the mouse, Mus musculus. The workflow requires an input of gene ref_seq identifiers. Data is then extracted from BioMart to annotate each of the genes found for each ref_seq id. The Entrez and UniProt identifiers are then sent to KEGG to obtain KEGG gene identifiers. The KEGG gene identifiers are then used to search for pathways in the KEGG pathway database.

Created: 2010-11-15 | Last updated: 2010-11-15

Credits: Paul Fisher

Principle Component Analysis (PCA) over mi... (1)

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Principle Component Analysis (PCA) over microarray data. Data is uploaded through caGrid transfer ultility.

Created: 2010-09-10 | Last updated: 2010-09-10

Credits: Wei Tan

A simple CQL query workflow in caGrid (1)

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1. CQL is a language to query data from caGrid/caBIG services. This workflow is tested with Taverna 2.1.2 and the caGrid Workflow Suite downloadable from http://www.mcs.anl.gov/~wtan/t2/. 2.More information regarding CQL can be found from http://wiki.cagrid.org/display/dataservices. 3. Sample input (95) is provided in the workflow. It is to query all the hybridization data within a microarray experiment whose id is 95.

Created: 2010-05-24 | Last updated: 2010-05-25

Credits: Wei Tan