We discuss the challenge of comparing three gene prioritization methods: network propagation, integer linear programming rank aggregation (RA), and statistical RA. These methods are based on different biological categories and estimate disease?gene association. Previously proposed comparison schemes are based on three measures of performance: receiver operating curve, area under the curve, and median rank ratio. Although they may capture important aspects of gene prioritization performance, they may fail to capture important differences in the rankings of individual genes. We suggest that comparison schemes could be improved by also considering recently proposed measures of similarity between gene rankings. We tested this suggestion on comparison schemes for prioritizations of genes associated with autism that were obtained using brain- and tissue-specific data. Our results show the effectiveness of our measures of similarity in clustering brain regions based on their relevance to autism.

Rank-Similarity Measures for Comparing Gene Prioritizations: A Case Study in Autism / Ferraro Petrillo, Umberto; Guerra, Concettina; Joshi, Sarang; Lu, Yinquan; Palini, Francesco; Rossignac, Jarek. - In: JOURNAL OF COMPUTATIONAL BIOLOGY. - ISSN 1066-5277. - 28:(2020). [10.1089/cmb.2020.0244]

Rank-Similarity Measures for Comparing Gene Prioritizations: A Case Study in Autism

Ferraro Petrillo, Umberto;Palini, Francesco;
2020

Abstract

We discuss the challenge of comparing three gene prioritization methods: network propagation, integer linear programming rank aggregation (RA), and statistical RA. These methods are based on different biological categories and estimate disease?gene association. Previously proposed comparison schemes are based on three measures of performance: receiver operating curve, area under the curve, and median rank ratio. Although they may capture important aspects of gene prioritization performance, they may fail to capture important differences in the rankings of individual genes. We suggest that comparison schemes could be improved by also considering recently proposed measures of similarity between gene rankings. We tested this suggestion on comparison schemes for prioritizations of genes associated with autism that were obtained using brain- and tissue-specific data. Our results show the effectiveness of our measures of similarity in clustering brain regions based on their relevance to autism.
2020
rank-similarity; autism; gene prioritization
01 Pubblicazione su rivista::01a Articolo in rivista
Rank-Similarity Measures for Comparing Gene Prioritizations: A Case Study in Autism / Ferraro Petrillo, Umberto; Guerra, Concettina; Joshi, Sarang; Lu, Yinquan; Palini, Francesco; Rossignac, Jarek. - In: JOURNAL OF COMPUTATIONAL BIOLOGY. - ISSN 1066-5277. - 28:(2020). [10.1089/cmb.2020.0244]
File allegati a questo prodotto
File Dimensione Formato  
Guerra_Rank-Similarity-measures_2020

Open Access dal 07/11/2021

Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 390.45 kB
Formato Unknown
390.45 kB Unknown

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1451111
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact