ArticleScientific reports2016
RNA-seq analysis for detecting quantitative trait-associated genes.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- Differential gene expression analysis based on linear mixed model corrects false positive inflation for studying quantitative traits.Scientific reports · 2023Article
- Gene expression of the endocannabinoid system in endometrium through menstrual cycle.Scientific reports · 2022Article
- Identification and annotation of milk associated genes from milk somatic cells using expression and RNA-seq data.Bioinformation · 2022Article
- The micro-RNA content of unsorted cryopreserved bovine sperm and its relation to the fertility of sperm after sex-sorting.BMC genomics · 2021Article
- Comparative Signatures of Selection Analyses Identify Loci Under Positive Selection in the Murrah Buffalo of India.Frontiers in genetics · 2021Article
- Associating gene expressions with curcuminoid biosynthesis in turmeric.Journal, genetic engineering & biotechnology · 2020Article
- Sequence analysis of the coding regions of the apolipoprotein C2 (APOC2) gene in Miniature Schnauzers with idiopathic hypertriglyceridemia.Veterinary journal (London, England : 1997) · 2020Article
- Circulating MicroRNA Profiling in Non-ST Elevated Coronary Artery Syndrome Highlights Genomic Associations with Serial Platelet Reactivity Measurements.Scientific reports · 2020Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many recent RNA-seq studies were focused mainly on detecting the differentially expressed genes (DEGs) between two or more conditions. In contrast, only a few attempts have been made to detect genes associated with quantitative traits, such as obesity index and milk yield, on RNA-seq experiment with large number of biological replicates. This study illustrates the linear model application on trait associated genes (TAGs) detection in two real RNA-seq datasets: 89 replicated human obesity related data and 21 replicated Holsteins' milk production related RNA-seq data. Based on these two datasets, the performance between suggesting methods, such as ordinary regression and robust regression, and existing methods: DESeq2 and Voom, were compared. The results indicate that suggesting methods have much lower false discoveries compared to the precedent two group comparisons based approaches in our simulation study and qRT-PCR experiment. In particular, the robust regression outperforms existing DEG finding method as well as ordinary regression in terms of precision. Given the current trend in RNA-seq pricing, we expect our methods to be successfully applied in various RNA-seq studies with numerous biological replicates that handle continuous response traits.
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