A critical comparison of topology-based pathway analysis
methods

J 2018

A critical comparison of topology-based pathway analysis methods

IHNATOVÁ, Ivana, Vlad POPOVICI and Eva BUDINSKÁ

Basic information

Original name

A critical comparison of topology-based pathway analysis methods

Authors

IHNATOVÁ, Ivana (703 Slovakia, belonging to the institution), Vlad POPOVICI (642 Romania, belonging to the institution) and Eva BUDINSKÁ (703 Slovakia, guarantor, belonging to the institution)

Edition

Plos one, San Francisco, Public Library Science, 2018, 1932-6203

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10700 1.7 Other natural sciences

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 2.776

RIV identification code

RIV/00216224:14310/18:00102453

Organization unit

Faculty of Science

DOI

http://dx.doi.org/10.1371/journal.pone.0191154

UT WoS

000423416600042

Keywords in English

topology-based pathway analysis; gene-set enrichment analysis; pathway analysis; microarrays; RNA-seq

Abstract

V originále

One of the aims of high-throughput gene/protein profiling experiments is the identification of biological processes altered between two or more conditions. Pathway analysis is an umbrella term for a multitude of computational approaches used for this purpose. While in the beginning pathway analysis relied on enrichment-based approaches, a newer generation of methods is now available, exploiting pathway topologies in addition to gene/protein expression levels. However, little effort has been invested in their critical assessment with respect to their performance in different experimental setups. Here, we assessed the performance of seven representative methods identifying differentially expressed pathways between two groups of interest based on gene expression data with prior knowledge of pathway topologies: SPIA, PRS, CePa, TAPPA, TopologyGSA, Clipper and DEGraph. We performed a number of controlled experiments that investigated their sensitivity to sample and pathway size, threshold-based filtering of differentially expressed genes, ability to detect target pathways, ability to exploit the topological information and the sensitivity to different preprocessing strategies. We also verified type I error rates and described the influence of overexpression of single genes, gene sets and topological motifs of various sizes on the detection of a pathway as differentially expressed. The results of our experiments demonstrate a wide variability of the tested methods. We provide a set of recommendations for an informed selection of the proper method for a given data analysis task.

Links

EF15_003/0000469, research and development project

Name: Cetocoen Plus

LM2015085, research and development project

Name: CERIT Scientific Cloud (Acronym: CERIT-SC)

Investor: Ministry of Education, Youth and Sports of the CR, CERIT Scientific Cloud

602901, interní kód MU

Name: MErCuRIC - A Phase Ib/II study of MEK1/2 inhibitor PD-‐0325901 with cMET inhibitor PF-‐02341066 in KRASMT and KRASWT (with aberrant c-‐MET) Colorectal Cancer Patients (Acronym: MErCuRIC)

Investor: European Union, Cooperation

Citovat

IHNATOVÁ, Ivana, Vlad POPOVICI and Eva BUDINSKÁ. A critical comparison of topology-based pathway analysis methods. Plos one. San Francisco: Public Library Science, 2018, vol. 13, No 1, p. 1-24. ISSN 1932-6203. Available from: https://dx.doi.org/10.1371/journal.pone.0191154.

@article{1412163,
   author = {Ihnatová, Ivana and Popovici, Vlad and Budinská, Eva},
   article_location = {San Francisco},
   article_number = {1},
   doi = {http://dx.doi.org/10.1371/journal.pone.0191154},
   keywords = {topology-based pathway analysis; gene-set enrichment analysis; pathway analysis; microarrays; RNA-seq},
   language = {eng},
   issn = {1932-6203},
   journal = {Plos one},
   title = {A critical comparison of topology-based pathway analysis methods},
   url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0191154},
   volume = {13},
   year = {2018}
}

TY  - JOUR
ID  - 1412163
AU  - Ihnatová, Ivana - Popovici, Vlad - Budinská, Eva
PY  - 2018
TI  - A critical comparison of topology-based pathway analysis methods
JF  - Plos one
VL  - 13
IS  - 1
SP  - 1-24
EP  - 1-24
PB  - Public Library Science
SN  - 19326203
KW  - topology-based pathway analysis
KW  - gene-set enrichment analysis
KW  - pathway analysis
KW  - microarrays
KW  - RNA-seq
UR  - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0191154
L2  - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0191154
N2  - One of the aims of high-throughput gene/protein profiling experiments is the identification of biological processes altered between two or more conditions. Pathway analysis is an umbrella term for a multitude of computational approaches used for this purpose. While in the beginning pathway analysis relied on enrichment-based approaches, a newer generation of methods is now available, exploiting pathway topologies in addition to gene/protein expression levels. However, little effort has been invested in their critical assessment with respect to their performance in different experimental setups. Here, we assessed the performance of seven representative methods identifying differentially expressed pathways between two groups of interest based on gene expression data with prior knowledge of pathway topologies: SPIA, PRS, CePa, TAPPA, TopologyGSA, Clipper and DEGraph. We performed a number of controlled experiments that investigated their sensitivity to sample and pathway size, threshold-based filtering of differentially expressed genes, ability to detect target pathways, ability to exploit the topological information and the sensitivity to different preprocessing strategies. We also verified type I error rates and described the influence of overexpression of single genes, gene sets and topological motifs of various sizes on the detection of a pathway as differentially expressed. The results of our experiments demonstrate a wide variability of the tested methods. We provide a set of recommendations for an informed selection of the proper method for a given data analysis task.
ER  -

IHNATOVÁ, Ivana, Vlad POPOVICI and Eva BUDINSKÁ. A critical comparison of topology-based pathway analysis methods. \textit{Plos one}. San Francisco: Public Library Science, 2018, vol.~13, No~1, p.~1-24. ISSN~1932-6203. Available from: https://dx.doi.org/10.1371/journal.pone.0191154.

Detailed Information on Publication Record