Workflows

Pathways and Gene annotations for QTL region (7)

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This workflow searches for genes which reside in a QTL (Quantitative Trait Loci) region in the mouse, Mus musculus. The workflow requires an input of: a chromosome name or number; a QTL start base pair position; QTL end base pair position. 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 path...

Created: 2009-11-19 | Last updated: 2012-09-07

Credits: Paul Fisher

Mouse Microarray Analysis (3)

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This workflow takes in probesets from and AffyMetrix micorarray experiment and returns: the genes ; gene start and end positions; chromosome where genes reside; ensembl trasncripts; SwissProt ids; affy probeset identifiers for chips Mouse430_2 and Mouse430a_2. Example ids from the Mouse430_2 affymetrix array are as follows (newline separated): 1447227_at 1440624_at 1436240_at 1454904_at 1435665_at 1418148_at 1429831_at

Created: 2007-10-03 | Last updated: 2009-12-03

Extract Scientific Terms (1)

This workflow takes in a document containg text and removes any non-ascii characters. The cleaned text is then sent to a service in Dresden, to extract all scientific terms. These terms represent a concept profile for the input concpet. Any null values are also removed.

Created: 2009-08-10 | Last updated: 2009-08-10

Credits: Paul Fisher

Rank Phenotype Terms (1)

This workflow counts the number of articles in the pubmed database in which each term occurs, and identifies the total number of articles in the entire PubMed database. It also identified the total number of articles within pubmed so that a term enrichment score may be calculated. The workflow also takes in a document containing abstracts that are related to a particular phenotype. Scientiifc terms are then extracted from this text and given a weighting according to the number of terms that ...

Created: 2009-08-10

Credits: Paul Fisher

Cosine vector space (1)

This workflow calculates the cosine vector space between two sets of corpora. The workflow then removes any null values from the output. The result is a cosine vector score between 0 and 1, showing the significance of any links between one concept (e.g. pathway) to another (e.g. phenotype). A score of 0 means there is no or an undetermined correlation between the two concepts. A score approaching 1 represents positive correlation.

Created: 2009-08-10 | Last updated: 2009-08-10

Credits: Paul Fisher

GWAS to biomedical concept (3)

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Genome-Wide Association studies (GWAS) with metabolomic phenotypes yield several statistically significant SNP-metabolite associations. To understand the biological basis of the association, scientists typically dwell on identifying genes in the vicinity of the SNP and the possible pathways that the gene participates in. The information needed to arrive at an understanding of the mechanistic basis of the association requires integration of disparate data sources. The purpose of this workflow ...

Created: 2013-04-15 | Last updated: 2014-07-14

Credits: Kristina Hettne Harish Dharuri Marco Roos Reinout van Schouwen

SNPs to Concept Set through Concept Profil... (6)

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Purpose: Currently, this workflow takes one SNP and a concept set as input, calculates the matching score between these, finds co-occuring documents between the query concept and the match concept, finds the concept that contributes the most to the match, and the documents that support this finding. Author comments: The workflow is in Beta stage. It runs, but needs more testing with different parameter settings. This workflow can be used together with other workflows in this pack: http://www...

Created: 2012-06-26 | Last updated: 2013-02-05

Credits: Kristina Hettne Eleni Harish Dharuri Reinout van Schouwen Marco Roos Martijn Schuemie BioSemantics

Attributions: Find Supporting Documents SNP_ID2EntrezGene_ID DatabaseID to ConceptID Match gene lists based on information in literature Match concept profiles Explain concept scores

get human and mouse phenotypes for a gene (2)

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This workflow gets phenotype annotations associated with human genes and the mouse orthologs from human (GWAS Central) and mouse (EuroPhenome and MGI) databases.

Created: 2011-05-20 | Last updated: 2012-03-29

Credits: Tim Beck

Get similar phenotypes for a disease and a... (1)

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This workflow retrieves the similar phenotypes between a disease and a gene based on the Monarch services at http://monarchinitiative.org/page/services. Phenotype similarity is calculated based on OwlSim, see http://owlsim.org.

Created: 2016-02-22

Credits: Kristina Hettne

Get differentially expressed genes for Arr... (1)

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****IMPORTANT****:if libraries: library(ArrayExpress), library(hgu133b.db), library(limma) are not installed in the local R installation, then they need to be installed before running this workflow. Original data come from Hodges et. al 2006 "Regional and cellular gene expression changes in human Huntington’s disease brain" This workflow loads the two necessary files (gene expression data & phenotype data), and creates the expression set object to be used by the R package limma, to test for ...

Created: 2013-11-04

Credits: Eleni