A critical comparison of topology-based pathway analysis methods

Logo poskytovatele
Logo poskytovatele

Varování

Publikace nespadá pod Fakultu sportovních studií, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
Autoři

IHNATOVÁ Ivana POPOVICI Vlad BUDINSKÁ Eva

Rok publikování 2018
Druh Článek v odborném periodiku
Časopis / Zdroj Plos one
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0191154
Doi http://dx.doi.org/10.1371/journal.pone.0191154
Klíčová slova topology-based pathway analysis; gene-set enrichment analysis; pathway analysis; microarrays; RNA-seq
Popis 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.
Související projekty:

Používáte starou verzi internetového prohlížeče. Doporučujeme aktualizovat Váš prohlížeč na nejnovější verzi.

Další info