iPathwayGuide Pathway Analysis

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iPathwayGuide

Get the most out of your RNA seq and Omics data!

iPathwayGuide, an advanced AI platform, uses the most advanced pathway analysis approach that considers the role, positioning, and relationships of a given gene within a pathway, resulting in a significant reduction in false positives associated with pathway analysis. Simple, easy, web-based application that provides you with publication-ready results in minutes.

What is Pathway Analysis?

High-throughput technologies (e.g. RNA sequencing, microarray, etc) currently enable us to measure gene expression levels of tens of thousands of genes in the scope of a single experiment. Many such experiments involve the comparison of two phenotypes, such as disease vs. control, treated vs. not treated, drug A vs. drug B, etc. Various statistical approaches are subsequently used to identify the genes which are differentially expressed (DE) between these phenotypes, such as t test, Z-score, and ANOVA. Although such lists of DE genes (100’s to 1000’s) provide valuable information regarding the changes across phenotypes, and play important roles in the downstream analysis, they alone cannot explain the complex mechanisms that are involved in the given condition.

The goal of pathway analysis is to translate the list of genes that are differentially expressed across the given phenotypes (e.g. disease vs healthy, treated vs non-treated, disease subtype A vs disease subtype B, etc.) into meaningful biological phenomena.

By using a novel system biology approach called Impact Analysis, iPathwayGuide considers the role, position and relationships of each gene within a pathway, which results in a significant reduction in false positives and identify the truly impacted pathways and putative mechanisms that can explain all measured gene expression changes.

Feature Highlights

Pathway Analysis

Pathway Impact Analysis (enrichment & perturbation)

AdvaitaBio’s proprietary Impact Analysis quickly identifies the significantly impacted pathways based on two forms of evidences: Over Representation Analysis, and Perturbation Analysis. All other pathway analysis approaches consider the pathways as simply sets of genes ignoring the biological processes that the pathways are meant to describe. iPathwayGuide is the only pathway analysis tool that uses a system biology approach and includes in the analysis the type, function and interactions between the genes on all pathways.

Gene Analysis

DE Genes Analysis

Access up-to-date gene annotations including miRNAs, biological processes, cellular components, pathways, SNPs, drugs, diseases, etc. iPathwayGuide provides a user-friendly interface to investigate the genes of your interests, saving valuable time and effort. Our gene annotations come from many public data sources, as well as literature mining. Our knowledge base includes many recent papers that are not yet available from NCBI.

Gene Ontology (GO) Analysis

GO analysis for Biological Processes, Molecular Functions, and Cellular Components with advanced correction

Choose from a variety of correction factors including high-specificity pruning inspired by Elim and Weight pruning methods that take hierarchical relationships into consideration. Identify and explore annotated genes, and view hierarchy plots of the various GO terms.

Predicted miRNA Analysis

Predicted miRNA analysis based on gene expression signatures

iPathwayGuide provides a novel predicted micro RNA (miRNA) analysis based on your gene-expression or protein-expression data.

This analysis allows you to identify miRNAs that may be active in your conditions, identify targets, and generate new hypotheses.

Disease Analysis

Disease Analysis based on enrichment

iPathwayGuide analysis includes finds enriched diseases under the ICD-10 classification.

Quickly zoom in on groups of diseases and see significantly expressed genes from your data that are annotated to each disease. Choose from a variety of correction factors including FDR. Identify and explore annotated genes, references, and more.

Meta Analysis

Meta-analysis to quickly identify common/unique traits across different experiments

iPathwayGuide is the only platform that allows for a meta-analysis across multiple conditions. Quickly identify genes, pathways, microRNAs, GO terms, or diseases that may be in common or unique across your data. You can even build custom meta-analyses based on other data sets you may already have.

How iPathwayGuide differs from competitors?

Best-in-class Impact Analysis for Pathway Analysis

The iPathwayGuide’s impact analysis uses a systems biology approach that takes into consideration the direction and type of every edge on every pathway, the location of every gene, etc. This has been shown to both eliminate many of the false positives produced by the other approaches, as well as correctly identify true positives that are otherwise missed.

A comprehensive benchmarking and comparison of 13 widely-used pathway analysis methods across more than 1,000 analyses shows that the topology-based method used in iPathwayGuide ranked the best with highest median value of AUC.

The comparison is described in the following publication:

Nguyen TM, Shafi A, Nguyen T, Draghici S. Identifying significantly impacted pathways: a comprehensive review and assessment. Genome Biol. 2019 Oct 9;20(1):203. doi: 10.1186/s13059-019-1790-4. Erratum in: Genome Biol. 2019 Nov 12;20(1):234. PMID: 31597578; PMCID: PMC6784345.

iPathwayGuide vs Ingenuity Pathway Analysis IPA
network vs true biological meaning

We help you understand, not just visualize

There are many tools that can be used for network visualization, but iPathway Guide helps you to understand the biological meaning and allow easy interpretation.
For example, when creating a network diagram, it is difficult to obtain a complicated entanglement interpretation as shown in the left figure, but the iPathway Guide (right figure) can help you to visually understand the phenomenon.

Automatically-generated PDF reports and Unlimited result sharing

iPathwayGuide automatically generates PDF of each analysis with outstanding executive summary. The results of the iPathway Guide can also be shared with unlicensed users (without the nonsense of “having another seat” that the competitor software is requiring!).
iPathwayGuide Printable Report
pathway analysis anywhere

Log in and analyze your data from anywhere, any time

iPathwayGuide is a web-based software and it is not locked to a specific computer. You could access iPathwayGuide from any computers with internet connection!

App Highlights

Pathway Analysis with proprietary Impact Analysis

iPathway Guide is the only pathway analysis tool that includes the types, functions, and interactions between genes on all pathways in the analysis. iPathwayGuide’s proprietary Impact Analysis quickly identifies the significantly impacted pathways based on two forms of evidences: Over Representation Analysis, and Perturbation Analysis.

All other pathway analysis approaches (e.g. Ingenuity Pathway Analysis or IPA) consider the pathways as simply sets of genes ignoring the biological processes that the pathways are meant to describe. iPathwayGuide is the only pathway analysis tool that uses a system biology approach and includes in the analysis the type, function and interactions between the genes on all pathways.

Impact Analysis is described in the following publication:

Sorin Draghici, Purvesh Khatri, Adi Laurentiu Tarca, Kashayp Amin, Arina Done, Calin Voichita, Constantin Georgescu, and Roberto Romero. A systems biology approach for pathway level analysis. Genome Research, 17(10):1537–1545, 2007.

Gene Expression Analysis

Access the latest gene annotations including gene analysis, predicted miRNAs, Gene Ontology categories, pathways, SNPs, drugs, diseases and more. Gene annotations are obtained from various public data sources and literatures.

Gene Ontology Analysis

iPathway Guide analysis includes GO analysis for the three domains:

  • biological processes;
  • molecular functions, and;
  • cellular components.

miRNA Predictive Analytics

iPathwayGuide provides predictive microRNA (miRNA) analysis based on gene expression or protein expression data. You can identify miRNAs that may be active in your condition and make new hypotheses.

Disease analysis

Disease Analysis based on enrichment when researchers could identify the significantly expressed genes from the data annotated for each disease. You can identify and search for annotated genes, references, and more.

Testimony

CUSTOMER STORIES

See how researchers have used iPathwayGuide for their biodiscovery

iPathwayGuide helps us identify the actual process, and it helps us develop hypotheses we could not otherwise develop… iPathwayGuide’s pathway analysis works differently and better than other available systems of which I’m aware.

Richard Friedman

Richard FriedmanResearch Scientist - Herbert Irving Comprehensive Cancer Center at Columbia University

We were very excited to see the very positive clinical results provided by methylprednisolone in the Henry Ford Health System. We have seen a dramatic reduction in the number of deaths after we started treating patients with this drug. We are looking forward to exploring the clinical efficacy of the other repurposed drugs identified by Advaita’s drug repurposing platform.

Dr. Mayur S. Ramesh

Dr. Mayur S. RameshPublished on peer-reviewed journal - Henry Ford Health System (HFHS)

What’s really nice about it [iPathwayGuide] still is… we can run an analysis and send it to a collaborator and they can play all day. And there is none of this nonsense about ‘having another seat’ that the competition is requiring. I mean, that’s the biggest thing. I would definitely recommend Advaita to other organizations. No product is perfect, but Advaita iPathwayGuide serves our needs very well, allows for flexibility and does not cost a huge amount of money. This is an excellent choice for a department like ours.

Dr. Melinda Duncan

Dr. Melinda DuncanProfessor, Biological Sciences - University of Delaware’s Biological Sciences Department

“iPathway[Guide] is very good at doing things quickly. It’s very intuitive to upload your dataset. It’s very intuitive at the gene set breakdown. Especially with how you change the cutoff and the types of statistical benchmarks you can use. For instance, it’s very easy to choose several different cutoffs when it comes to criteria and stringency for the types of statistics you’re doing. If you want to make things more stringent or you want to do a p-value correction, it’s easy to adjust for that.”

Dr Douglas Dluzen

Dr Douglas DluzenAssistant Professor - Morgan State University

iPathwayGuide Free Demo Account

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iPathwayGuide Demo

Contact Team MBIO for an obligation-free walkthrough of the main features and a free demo account of iPathwayGuide!

Publications

Draghici, S., Khatri, P., Tarca, A. L., Amin, K., Done, A., Voichita, C., … Romero, R. (2007). A systems biology approach for pathway level analysis. Genome Research, 17(10), 1537–1545. doi:10.1101/gr.6202607. Full paper here.

Tarca, A. L., Draghici, S., Khatri, P., Hassan, S. S., Mittal, P., Kim, J., … Romero, R. (2008). A novel signaling pathway impact analysis. Bioinformatics, 25(1), 75–82. doi:10.1093/bioinformatics/btn577. Full paper here.

Ahsan, S., & Drăghici, S. (2017). Identifying Significantly Impacted Pathways and Putative Mechanisms with iPathwayGuide. Current Protocols in Bioinformatics, 7.15.1–7.15.30. doi:10.1002/cpbi.24. Full paper here.

Nguyen, T.-M., Shafi, A., Nguyen, T., & Draghici, S. (2019). Identifying significantly impacted pathways: a comprehensive review and assessment. Genome Biology, 20(1). doi:10.1186/s13059-019-1790-4. Full paper here.

About Advaita Bio

About Advaita Bioinformatics

Advaita provides its industry-leading bioinformatics platforms to over 17,000 registered users worldwide: iPathwayGuide, for functional interpretation of genes and proteins; iVariantGuide, for genetic variant analysis; and iBioGuide, a search engine revealing connections between genes, pathways, SNPs, drugs, and more. Currently, 9 of the top 10 pharma companies rely on Advaita’s state-of-the-art algorithms to solve complex problems.
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Webinars

Title: Using bioinformatics to shorten your path to discovery and improve patient care

Date/Time: 30th June 2021 (WED), 900AM – 1030AM

Organized by: Department of Pathology, Faculty of Medicine and Health Sciences, UPM and Mbioscience Solutions Sdn Bhd

Invited Speaker: Professor Sorin Draghici, Computer Science and Obstetrics and Gynecology, Wayne State University (USA)

Host: Professor Dr. Johnson Stanslas, Researcher in Translational Pharmacology and Therapeutics, Department of Medicine, UPM

For more information, please visit here

Back in May 2021, we hosted a webinar demonstrating how iPathwayGuide identified the key processes and mechanisms in severe cased of COVID-19.

We heard from world expert immunologist Dr. Gil Mor about the key mechanisms identified in this disease, and showed how iPathwayGuide used those mechanisms to predict an existing drug with clinical efficacy against COVID-19.

We also presented results from an independent clinical study, which showed in a cohort of over 200 patients, that a short course of methylprednisolone was able to significantly reduce transfers to ICU, requirements for ventilation, as well as reduce mortality by 44%.

What could iPathwayGuide help you see in your data? Watch the webinar to get some ideas about what more you can mine from your experiments.

Please fill in a simple form to view the recording here.