Proceedings Article10.1109/BIBM47256.2019.8982944
Pathway Analysis for SNP microarray data
Giuseppe Agapito,Pietro Hiram Guzzi,Mario Cannataro +2 more
- 01 Nov 2019
- pp 2244-2250
1
TL;DR: SNPs Microarray Pathway Analysis (MPA), a software tool able to discriminate relevant genes from SNP microarrays to use in PA analysis, and provides to the user the list of enriched pathways from the identified SNPs.
read more
Abstract: Pathway Analysis (PA) is a powerful method for data analysis in genomics, most often applied to gene expression analysis, but little used to analyze variants such as Single Nucleotide Polymorphisms (SNPs). PA could allow the interpretation of variants concerning the biological processes in which the affected genes and proteins are involved. Currently, the available PA software tools are not able to automatically perform pathway analysis using SNPs data. PA software tools cannot deal natively with SNPs data, hence several software tools have to be used to put SNPs data in the proper format for the analysis. To overcome these limitations, we present SNP Microarray Pathway Analysis (MPA), a software tool able to discriminate relevant genes from SNP microarrays to use in PA analysis. MPA automatically identifies relevant SNPs using the well known Fisher's test, with which to perform PA. Pathway analysis in MPA is obtained employing the Hypergeometric function. As a result, MPA provides to the user the list of enriched pathways from the identified SNPs. MPA software tool along with the user guide and datasets, are available for download at https://gitlab.com/giuseppeagapito/mpa under the GPL v3.0 license.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Microarray Data Analysis Protocol.
Giuseppe Agapito,Mariamena Arbitrio +1 more
TL;DR: This paper presents a general protocol for microarray data analysis, focusing on selecting the best software tool to efficiently identify genomic/pharmacogenomic biomarkers, providing a simple and accurate approach to omic investigation in biology and medicine.
References
KEGG: Kyoto Encyclopedia of Genes and Genomes
Minoru Kanehisa,Susumu Goto +1 more
TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Glynn Dennis,Brad T. Sherman,Douglas A. Hosack,Jun Jun Yang,Wei Gao,H. Clifford Lane,Richard A. Lempicki +6 more
TL;DR: DAMID is a web-accessible program that integrates functional genomic annotations with intuitive graphical summaries that assists in the interpretation of genome-scale datasets by facilitating the transition from data collection to biological meaning.
The Reactome Pathway Knowledgebase.
Antonio Fabregat,Konstantinos Sidiropoulos,Phani V. Garapati,Marc Gillespie,Marc Gillespie,Kerstin Hausmann,Robin Haw,Bijay Jassal,S Jupe,Florian Korninger,Sheldon J. McKay,Lisa Matthews,Bruce May,Marija Milacic,Karen Rothfels,Veronica Shamovsky,Marissa Webber,Joel Weiser,Mark Williams,Guanming Wu,Lincoln Stein,Lincoln Stein,Lincoln Stein,Henning Hermjakob,Henning Hermjakob,Peter D'Eustachio +25 more
TL;DR: The Reactome Knowledgebase provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations—an extended version of a classic metabolic map, in a single consistent data model.
KEGG for integration and interpretation of large-scale molecular data sets
TL;DR: KEGG Mapper, a collection of tools for KEGG PATHWAY, BRITE and MODULE mapping, enabling integration and interpretation of large-scale data sets and recent enhancements to the K EGG content, especially the incorporation of disease and drug information used in practice and in society, to support translational bioinformatics.
The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases
Ron Caspi,Richard Billington,Luciana Ferrer,Hartmut Foerster,Carol A. Fulcher,Ingrid M. Keseler,Anamika Kothari,Markus Krummenacker,Mario Latendresse,Lukas A. Mueller,Quang Ong,Suzanne M. Paley,Pallavi Subhraveti,Daniel Weaver,Peter D. Karp +14 more
TL;DR: The BioCyc PGDBs generated by SRI are offered for adoption by any interested party for the ongoing integration of metabolic and genome-related information about an organism.