Gene expression profiling is a useful way to measure the activity of genes in molecular biology and, because of its effectiveness, researchers have released thousands of gene expression datasets publicly in online databases and repositories, such as Gene Expression Omnibus (GEO). To read and analyze gene expression data, the computational biology community has developed several tools and platforms, including Bioconductor, an R open-source platform of software packages that can be used to analyze these data. Despite the usefulness of Bioconductor and of its packages, it is still difficult to read gene expression data from GEO, and to assign gene symbols to the probesets of datasets. To alleviate this problem, we introduce here a new R software package, geneExpressionFromGEO, which provides to the users the possibility to easily download gene expression data from GEO and to easily associate gene symbols to probesets. In this short chapter, we describe the assets of our software package, and we report an example of its usage. We believe that geneExpressionFromGEO can be very useful for the R community of bioinformaticians working on gene expression data.

Chicco, D. (2022). geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO). In G. Agapito (a cura di), Microarray Data Analysis (pp. 187-194). Humana Press Inc. [10.1007/978-1-0716-1839-4_12].

geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO)

Chicco, D
2022

Abstract

Gene expression profiling is a useful way to measure the activity of genes in molecular biology and, because of its effectiveness, researchers have released thousands of gene expression datasets publicly in online databases and repositories, such as Gene Expression Omnibus (GEO). To read and analyze gene expression data, the computational biology community has developed several tools and platforms, including Bioconductor, an R open-source platform of software packages that can be used to analyze these data. Despite the usefulness of Bioconductor and of its packages, it is still difficult to read gene expression data from GEO, and to assign gene symbols to the probesets of datasets. To alleviate this problem, we introduce here a new R software package, geneExpressionFromGEO, which provides to the users the possibility to easily download gene expression data from GEO and to easily associate gene symbols to probesets. In this short chapter, we describe the assets of our software package, and we report an example of its usage. We believe that geneExpressionFromGEO can be very useful for the R community of bioinformaticians working on gene expression data.
Capitolo o saggio
Bioconductor; Gene expression; Gene Expression Omnibus; Microarray; R programming language
English
Microarray Data Analysis
Agapito, G
14-dic-2021
2022
9781071618387
2401
Humana Press Inc.
187
194
Chicco, D. (2022). geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO). In G. Agapito (a cura di), Microarray Data Analysis (pp. 187-194). Humana Press Inc. [10.1007/978-1-0716-1839-4_12].
reserved
File in questo prodotto:
File Dimensione Formato  
Chicco-2022-Microarray Data Analysis-VoR.pdf

Solo gestori archivio

Descrizione: Contributo in libro
Tipologia di allegato: Publisher’s Version (Version of Record, VoR)
Licenza: Tutti i diritti riservati
Dimensione 176.76 kB
Formato Adobe PDF
176.76 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

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/10281/430860
Citazioni
  • Scopus 12
  • ???jsp.display-item.citation.isi??? ND
Social impact