Compositional Data Analysis is necessary for simulating and analyzing RNA-Seq data, bioRxiv, 2019-03-02

Seq techniques (e.g. RNA-Seq) generate compositional datasets, i.e. the number of fragments sequenced is not proportional to the total RNA present. Thus, datasets carry only relative information, even though absolute RNA copy numbers are often of interest. Current normalization methods assume most features are not changing, which can lead to misleading conclusions when there are large shifts. However, there are few real datasets and no simulation protocols currently available that can directly benchmark methods when such large shifts occur.We present absSimSeq, an R package that simulates compositional data in the form of RNA-Seq reads. We tested several tools used for RNA-Seq differential analysis sleuth, DESeq2, edgeR, limma, sleuth and ALDEx2 (which explicitly takes a compositional approach). For these tools, we compared their standard normalization to either “compositional normalization”, which uses log-ratios to anchor the data on a set of negative control features, or RUVSeq, another tool that directly uses negative control features.We show that common normalizations result in reduced performance with current methods when there is a large change in the total RNA per cell. Performance improves when spike-ins are included and used by a compositional approach, even if the spike-ins have substantial variation. In contrast, RUVSeq, which normalizes count data rather than compositional data, has poor performance. Further, we show that previous criticisms of spike-ins did not take into account the compositional nature of the data. We conclude that absSimSeq can generate more representative datasets for testing performance, and that spike-ins should be more broadly used in a compositional manner to minimize misleading conclusions from differential analyses.

biorxiv bioinformatics 0-100-users 2019

Genetic inhibition of PCSK9, atherogenic lipoprotein concentrations, and calcific aortic valve stenosis, bioRxiv, 2019-03-02

Background Proprotein convertase subtilisinkexin type 9 (PCSK9) inhibition reduces plasma concentrations of low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (apoB) and lipoprotein(a) [Lp(a)]. Atherogenic lipoprotein levels have been linked with calcific aortic valve stenosis (CAVS). Our objectives were to determine the association between variants in PCSK9 and lipoprotein-lipid levels, coronary artery disease (CAD) and CAVS, and to evaluate if PCSK9 could be implicated in aortic valve interstitial cells (VICs) calcification.Methods We built a genetic risk score weight for LDL-C levels (wGRS) using 10 independent PCSK9 single nucleotide polymorphisms and determined its association with lipoprotein-lipid levels in 9692 participants of the EPIC-Norfolk study. We investigated the association between the wGRS and CAD and CAVS in the UK Biobank, as well as the association between the PCSK9 R46L variant and CAVS in a meta-analysis of published prospective, population-based studies (Copenhagen studies, 1463 cases101,620 controls) and unpublished studies (UK Biobank, 1350 cases349,043 controls, Malmo Diet and Cancer study, 682 cases5963 controls and EPIC-Norfolk study, 508 cases20,421 controls). We evaluated PCSK9 expression and localization in explanted aortic valves by capillary Western blot and immunohistochemistry in patients with and without CAVS. Von Kossa staining was used to visualize aortic leaflet calcium deposits. PCSK9 expression under oxidative stress conditions in VICs was assessed.Results The wGRS was significantly associated with lower LDL-C and apoB (p<0.001), but not with Lp(a). In the UK Biobank, the association of PCSK9 variants with CAD were positively correlated with their effects on apoB levels. CAVS was less prevalent in carriers of the PCSK9 R46L variant [odds ratio=0.71 (95% confidence interval, 0.57-0.88), p<0.001]. PCSK9 expression was elevated in the aortic valves of patients with aortic sclerosis and CAVS compared to controls. In calcified leaflets, PCSK9 co-localized with calcium deposits. PCSK9 expression was induced by oxidative stress in VICs. Conclusion Genetic inhibition of PCSK9 is associated with lifelong reductions in the levels of non-Lp(a) apoB-containing lipoproteins as well as lower odds of CAD and CAVS. PCSK9 is abundant in fibrotic and calcified aortic leaflets. Oxidative stress increases PCSK9 expression in VICs. These results provide a rationale for performing randomized clinical trials of PCSK9 inhibition in CAVS.

biorxiv genetics 0-100-users 2019

 

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