Brief. Bioinformatics - A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis.

Tópicos

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Resumo

During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data.

Resumo Limpo

last year number approach normal rna sequenc data emerg literatur differ type bias adjust statist strategi adopt howev data continu accumul clear consensus appropri normal method use impact chosen method downstream analysi work focus comprehens comparison seven recent propos normal method differenti analysi rnaseq data emphasi use vari real simul dataset involv differ speci experiment design repres data characterist common observ practic base comparison studi propos practic recommend appropri normal method use impact differenti analysi rnaseq data

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