Standard Operating Protocols for RNA-seq data analysis

MERINO, GABRIELA; FERNÁNDEZ, ELMER

Montevideo

Otro; Genómica en Cancer; 2013

RNA_seq technology is emerging as a promising tool for transcriptomics analysis. In general it implies the identification of gene and evaluates some experimental condition in terms of expression, using millions of reads produced by a high-throughput sequencing machine. The huge output is processed in several steps and requires taking in consideration many aspects. Although the technique is revolutionary, it is not stable yet. Therefore many variation sources including technical and random effects should be properly accounted in order to reduce bias from the results [1]. In addition, when you plan to do functional analysis it is compulsory to use the most appropriate gene identifier which depends on the functional platform. In this context, gene symbols are unsteady. Hence, a combination of data bases is necessary to retrieve the appropriate gene annotations. Here we propose a standard operating procedure for RNA_seq analysis, to detect and remove some bias sources from the data. The procedure is based on well-known microarray technology methodologies [2]. The analysis is also enriched by the integration of different data bases for gene symbol conversion to perform functional analysis.