scholarly journals LungMAP Portal Ecosystem: Systems-Level Exploration of the Lung

2021 ◽  
Author(s):  
Nathan Gaddis ◽  
Joshua Fortriede ◽  
Minzhe Guo ◽  
Eric E. Bardes ◽  
Michal Kouril ◽  
...  

ABSTRACTAn improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a gateway portal. This portal connects a broad-spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease and drug treatment. These atlases are provided as independent and integrated queriable datasets, with an emphasis on dynamic visualization, figure generation and reference-based classification of user-provided datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, data portals and datasets from LungMAP and external research efforts.

2007 ◽  
Vol 306 (1) ◽  
pp. 354
Author(s):  
Kelley S. Harris ◽  
Michael McManus ◽  
Brian Harfe ◽  
Xin Sun

2015 ◽  
Vol 406 (2) ◽  
pp. 222-234 ◽  
Author(s):  
Arianna Caprioli ◽  
Alethia Villasenor ◽  
Lyndsay A Wylie ◽  
Caitlin Braitsch ◽  
Leilani Marty-Santos ◽  
...  

2021 ◽  
Vol 12 (2) ◽  
pp. 317-334
Author(s):  
Omar Alaqeeli ◽  
Li Xing ◽  
Xuekui Zhang

Classification tree is a widely used machine learning method. It has multiple implementations as R packages; rpart, ctree, evtree, tree and C5.0. The details of these implementations are not the same, and hence their performances differ from one application to another. We are interested in their performance in the classification of cells using the single-cell RNA-Sequencing data. In this paper, we conducted a benchmark study using 22 Single-Cell RNA-sequencing data sets. Using cross-validation, we compare packages’ prediction performances based on their Precision, Recall, F1-score, Area Under the Curve (AUC). We also compared the Complexity and Run-time of these R packages. Our study shows that rpart and evtree have the best Precision; evtree is the best in Recall, F1-score and AUC; C5.0 prefers more complex trees; tree is consistently much faster than others, although its complexity is often higher than others.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Maria Hurskainen ◽  
Ivana Mižíková ◽  
David P. Cook ◽  
Noora Andersson ◽  
Chanèle Cyr-Depauw ◽  
...  

AbstractDuring late lung development, alveolar and microvascular development is finalized to enable sufficient gas exchange. Impaired late lung development manifests as bronchopulmonary dysplasia (BPD) in preterm infants. Single-cell RNA sequencing (scRNA-seq) allows for assessment of complex cellular dynamics during biological processes, such as development. Here, we use MULTI-seq to generate scRNA-seq profiles of over 66,000 cells from 36 mice during normal or impaired lung development secondary to hyperoxia with validation of some of the findings in lungs from BPD patients. We observe dynamic populations of cells, including several rare cell types and putative progenitors. Hyperoxia exposure, which mimics the BPD phenotype, alters the composition of all cellular compartments, particularly alveolar epithelium, stromal fibroblasts, capillary endothelium and macrophage populations. Pathway analysis and predicted dynamic cellular crosstalk suggest inflammatory signaling as the main driver of hyperoxia-induced changes. Our data provides a single-cell view of cellular changes associated with late lung development in health and disease.


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