Comparative study of gene set enrichment methods

Abatangelo, Luca; Maglietta, Rosalia; Distaso, Angela; D’Addabbo, A.; Creanza, Teresa Maria; Mukherjee, Sayan; Ancona, Nicola

doi:10.1186/1471-2105-10-275

Cited by 103 publications

(102 citation statements)

References 25 publications

(50 reference statements)

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“…12 GSEA is widely used, generates detailed information on the results, and has shown very good performance in a comparison of methods that compute enrichment at the level of gene sets. 13 Further, GSEA has been used to identify pathways involved in liver toxicity in human hepatoblastoma cells. 8 GSEA is designed to identify predefined gene sets that are differentially expressed in a treatment and a control.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Genome-Wide Transcriptional Profiles of Primary Hepatocytes in Collagen Sandwich and Monolayer Cultures

Kim

Lasher

Milford

et al. 2010

Tissue Engineering Part C: Methods

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Two commonly used culture systems in hepatic tissue engineering are the collagen sandwich (CS) and monolayers of cells. In this study, genome-wide gene expression profiles of primary hepatocytes were measured over an 8-day period for each cell culture system using Affymetrix GeneChips and compared via gene set enrichment analysis to elicit biologically meaningful information at the level of gene sets. Our results demonstrate that gene expression in hepatocytes in CS cultures steadily and comprehensively diverges from that in monolayer cultures. Gene sets up-regulated in CS cultures include several associated with liver metabolic and synthesis functions, such as metabolism of lipids, amino acids, carbohydrates, and alcohol, and synthesis of bile acids. Monooxygenases such as Cytochrome-P450 enzymes do not show any change between the culture systems after 1 day, but exhibit significant up-regulation in CS cultures after 3 days in comparison to hepatocyte monolayers. These data provide insights into the up-and down-regulation of several liver-critical gene sets and their subsequent effects on liver-specific functions. These results provide a baseline for further explorations into the systems biology of engineered liver mimics.

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Section: Introductionmentioning

confidence: 99%

A Comparative Study of Genome-Wide Transcriptional Profiles of Primary Hepatocytes in Collagen Sandwich and Monolayer Cultures

Kim

Lasher

Milford

et al. 2010

Tissue Engineering Part C: Methods

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“…An up-to-date method for analyzing microarrays is gene set enrichment [4]. It has a higher consistency of prediction in contrast to other pathway methods such as Fishers exact test [18]. Using this method, the user has to decide for one database to search in for pathways.…”

Section: Introductionmentioning

confidence: 99%

Automatic network generation describes differential gene data in user friendly and expeditiously analyzable network views

Wolf¹,

Barbosa²,

Bucher³

2017

Biomed Genet Genomics

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Cancer is a group of diseases that involves abnormal cell growth, resulting from genetic perturbations in signaling mechanisms. High resolution RNAseq and microarray assays enable the evaluation of the transcriptional activity of high number of signaling molecules. Furthermore, many signaling pathways are described in publically available databases. Today's challenge lies in the connection of signaling pathways and signaling data to produce predictive models which have the power to validate and identify targets in disease treatment. Curating networks manually can be exhaustive handiwork. We designed an ensemble approach of gene set enrichment on seven pathway databases. It generates a basic gene set mapping of the complex input data on comprehensive pathways. Using two publically available protein-protein interaction databases, the novel algorithm automatically reconstructs a comprehensive biological system representation from these mappings. The reconstruction was based on a newly shortest path algorithm. Using a microarray data set from hepatocellular cancer cells as input, a network with well-known cancer signaling mechanisms was derived. Furthermore, nodes accounting for hormone signaling were found as being modified in liver cancer that can be used as future research targets. Two recent publically available networks were adequately inferred when testing the method to reconstruct manually curated signaling networks. Finally, our method shows that integration of raw data and publically available knowledge expeditiously generates convenient and analyzable network views.

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“…In addition, it has been demonstrated extensively that pathway analysis rather than single gene evaluation has many advantages. In a recent paper, Abatangelo et al [99] reviewed the main technical aspects of pathway analysis and provided practical advice to perform data analysis more efficiently. Therefore, it seems clear that, in future, researchers involved in pharmacogenomics studies should combine all available methods (associative, predictive) to obtain more reliable and reproducible results.…”

Section: Pharmacogenomics: a New Strategy To Study The Polygenic Inflmentioning

confidence: 99%

Pharmacogenomics: a new paradigm to personalize treatments in nephrology patients

Zaza

Granata

Sallustio

et al. 2009

Clinical and Experimental Immunology

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SummaryAlthough notable progress has been made in the therapeutic management of patients with chronic kidney disease in both conservative and renal replacement treatments (dialysis and transplantation), the occurrence of medication-related problems (lack of efficacy, adverse drug reactions) still represents a key clinical issue. Recent evidence suggests that adverse drug reactions are major causes of death and hospital admission in Europe and the United States. The reasons for these conditions are represented by environmental/non-genetic and genetic factors responsible for the great inter-patient variability in drugs metabolism, disposition and therapeutic targets. Over the years several genetic settings have been linked, using pharmacogenetic approaches, to the effects and toxicity of many agents used in clinical nephrology. However, these strategies, analysing single gene or candidate pathways, do not represent the gold standard, being the overall pharmacological effects of medications and not typically monogenic traits. Therefore, to identify multi-genetic influence on drug response, researchers and clinicians from different fields of medicine and pharmacology have started to perform pharmacogenomic studies employing innovative whole genomic high-throughput technologies. However, to date, only few pharmacogenomics reports have been published in nephrology underlying the need to enhance the number of projects and to increase the research budget for this important research field. In the future we would expect that, applying the knowledge about an individual's inherited response to drugs, nephrologists will be able to prescribe medications based on each person's genetic make-up, to monitor carefully the efficacy/toxicity of a given drug and to modify the dosage or number of medications to obtain predefined clinical outcomes.

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Comparative study of gene set enrichment methods

Cited by 103 publications

References 25 publications

A Comparative Study of Genome-Wide Transcriptional Profiles of Primary Hepatocytes in Collagen Sandwich and Monolayer Cultures

A Comparative Study of Genome-Wide Transcriptional Profiles of Primary Hepatocytes in Collagen Sandwich and Monolayer Cultures

Automatic network generation describes differential gene data in user friendly and expeditiously analyzable network views

Pharmacogenomics: a new paradigm to personalize treatments in nephrology patients

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