ABSTRACT
scPipe is a flexible R/Bioconductor package originally developed to analyse platform-independent single-cell RNA-Seq data. To expand its preprocessing capability to accommodate new single-cell technologies, we further developed scPipe to handle single-cell ATAC-Seq and multi-modal (RNA-Seq and ATAC-Seq) data. After executing multiple data cleaning steps to remove duplicated reads, low abundance features and cells of poor quality, a SingleCellExperiment object is created that contains a sparse count matrix with features of interest in the rows and cells in the columns. Quality control information (e.g. counts per cell, features per cell, total number of fragments, fraction of fragments per peak) and any relevant feature annotations are stored as metadata. We demonstrate that scPipe can efficiently identify 'true' cells and provides flexibility for the user to fine-tune the quality control thresholds using various feature and cell-based metrics collected during data preprocessing. Researchers can then take advantage of various downstream single-cell tools available in Bioconductor for further analysis of scATAC-Seq data such as dimensionality reduction, clustering, motif enrichment, differential accessibility and cis-regulatory network analysis. The scPipe package enables a complete beginning-to-end pipeline for single-cell ATAC-Seq and RNA-Seq data analysis in R.
ABSTRACT
BACKGROUND: The assessment of pulmonary vascular resistance (PVR) plays an important role in the diagnosis and management of pulmonary arterial hypertension (PAH). The main objective of this study was to determine whether the noninvasive index of systolic pulmonary arterial pressure (SPAP) to heart rate (HR) times the right ventricular outflow tract time-velocity integral (TVI(RVOT)) (SPAP/[HR x TVI(RVOT)]) provides clinically useful estimations of PVR in PAH. METHODS: Doppler echocardiography and right-heart catheterization were performed in 51 consecutive patients with established PAH. The ratio of SPAP/(HR x TVI(RVOT)) was then correlated with invasive indexed PVR (PVRI) using regression and Bland-Altman analysis. Using receiver operating characteristic curve analysis, a cutoff value for the Doppler equation was generated to identify patients with PVRI > or = 15 Wood units (WU)/m2. RESULTS: The mean pulmonary arterial pressure was 52 +/- 15 mm Hg, the mean cardiac index was 2.2 +/- 0.6 L/min/m2, and the mean PVRI was 20.5 +/- 9.6 WU/m2. The ratio of SPAP/(HR x TVI(RVOT)) correlated very well with invasive PVRI measurements (r = 0.860; 95% confidence interval, 0.759-0.920). A cutoff value of 0.076 provided well-balanced sensitivity (86%) and specificity (82%) to determine PVRI > 15 WU/m2. A cutoff value of 0.057 increased sensitivity to 97% and decreased specificity to 65%. CONCLUSION: The novel index of SPAP/(HR x TVI(RVOT)) provides useful estimations of PVRI in patients with PAH.
