scholarly journals A Multimodal and Integrated Approach to Interrogate Human Kidney Biopsies with Rigor and Reproducibility: Guidelines from the Kidney Precision Medicine Project

2020 ◽  
Author(s):  
Tarek M. El-Achkar ◽  
Michael T Eadon ◽  
Rajasree Menon ◽  
Blue B. Lake ◽  
Tara K. Sigdel ◽  
...  
Keyword(s):  
Quality Control ◽  
Precision Medicine ◽  
Single Cell ◽  
Human Kidney ◽  
Integrated Approach ◽  
Control Measures ◽  
Common Source ◽  
Data Generation ◽  
Cell Region ◽  
Imaging Technologies

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate 3-dimensional (3D) molecular atlases of healthy and diseased kidney biopsies using multiple state-of-the-art OMICS and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single cell level or in 3D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single cell/region 3D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation and harmonization across different OMICS and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis and sharing. We established benchmarks for quality control, rigor, reproducibility and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multi-OMICS and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

scholarly journals A Multimodal and Integrated Approach to Interrogate Human Kidney Biopsies with Rigor and Reproducibility: The Kidney Precision Medicine Project

2019 ◽  
Author(s):  
Tarek M. El-Achkar ◽  
Michael T. Eadon ◽  
Rajasree Menon ◽  
Blue B. Lake ◽  
Tara K. Sigdel ◽  
...  
Keyword(s):  
Quality Control ◽  
Precision Medicine ◽  
Single Cell ◽  
Human Kidney ◽  
Integrated Approach ◽  
Control Measures ◽  
Common Source ◽  
Data Generation ◽  
Cell Region ◽  
Imaging Technologies

AbstractComprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate 3-dimensional (3D) molecular atlases of healthy and diseased kidney biopsies using multiple state-of-the-art OMICS and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single cell level or in 3D space is a significant challenge that can be a futile exercise if not well controlled. We describe a “follow the tissue” pipeline for generating a reliable and authentic single cell/region 3D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation and harmonization across different OMICS and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis and sharing. We established benchmarks for quality control, rigor, reproducibility and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multi-OMICS and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

scholarly journals Built on sand: the shaky foundations of simulating single-cell RNA sequencing data

2021 ◽  
Author(s):  
Helena L Crowell ◽  
Sarah X Morillo Leonardo ◽  
Charlotte Soneson ◽  
Mark D Robinson
Keyword(s):  
Quality Control ◽  
Single Cell ◽  
Rna Sequencing ◽  
Simulated Data ◽  
Quality Standard ◽  
Data Generation ◽  
Clustering Methods ◽  
Sequencing Data ◽  
Study Results ◽  
Single Cell Rna Sequencing

With the emergence of hundreds of single-cell RNA-sequencing (scRNA-seq) datasets, the number of computational tools to analyse aspects of the generated data has grown rapidly. As a result, there is a recurring need to demonstrate whether newly developed methods are truly performant - on their own as well as in comparison to existing tools. Benchmark studies aim to consolidate the space of available methods for a given task, and often use simulated data that provide a ground truth for evaluations. Thus, demanding a high quality standard for synthetically generated data is critical to make simulation study results credible and transferable to real data. Here, we evaluated methods for synthetic scRNA-seq data generation in their ability to mimic experimental data. Besides comparing gene- and cell-level quality control summaries in both one- and two-dimensional settings, we further quantified these at the batch- and cluster-level. Secondly, we investigate the effect of simulators on clustering and batch correction method comparisons, and, thirdly, which and to what extent quality control summaries can capture reference-simulation similarity. Our results suggest that most simulators are unable to accommodate complex designs without introducing artificial effects; they yield over-optimistic performance of integration, and potentially unreliable ranking of clustering methods; and, it is generally unknown which summaries are important to ensure effective simulation-based method comparisons.

scholarly journals Towards Building a Smart Kidney Atlas: Network-based integration of multimodal transcriptomic, proteomic, metabolomic and imaging data in the Kidney Precision Medicine Project

2020 ◽  
Author(s):  
Jens Hansen ◽  
Rachel Sealfon ◽  
Rajasree Menon ◽  
Michael T. Eadon ◽  
Blue B. Lake ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Single Cell ◽  
Computational Models ◽  
Kidney Injury ◽  
Human Kidney ◽  
Cell Types ◽  
Data Sets ◽  
Imaging Data ◽  
Reference Tissue ◽  
Single Nucleus

AbstractThe Kidney Precision Medicine Project (KPMP) plans to construct a spatially specified tissue atlas of the human kidney at a cellular resolution with near comprehensive molecular details. The atlas will have maps of healthy, acute kidney injury and chronic kidney disease tissues. To construct such maps, we integrate different data sets that profile mRNAs, proteins and metabolites collected by five KPMP Tissue Interrogation Sites. Here, we describe a set of hierarchical analytical methods to process, combine, and harmonize single-cell, single-nucleus and subsegmental laser microdissection (LMD) transcriptomics with LMD and near single-cell proteomics, 3-D nondestructive and immunofluorescence-based Codex imaging and spatial metabolomics datasets. We use nephrectomy, healthy living donor and surveillance transplant biopsy tissues to create a harmonized reference tissue map. Our results demonstrate that different assays produce reliable and coherent identification of cell types and tissue subsegments. They further show that the molecular profiles and pathways are partially overlapping yet complementary for cell type-specific and subsegmental physiological processes. Focusing on the proximal tubules, we find that our integrated systems biologybased analyses identify different subtypes of tubular cells with potential for different levels of lipid oxidation and energy generation. Integration of our omics data with pathways from the literature, enables us to construct predictive computational models to develop a smart kidney atlas. These integrated models can describe physiological capabilities of the tissues based on the underlying cell types and pathways in health and disease.

Radar-aided CSO-control-criteria for an ecological approach

1997 ◽  
Vol 36 (8-9) ◽  
pp. 223-228
Author(s):  
A. Petruck ◽  
F. Sperling
Keyword(s):  
Critical Time ◽  
Integrated Approach ◽  
Control Measures ◽  
Real Time Control ◽  
Sewer System ◽  
Time Control ◽  
Physical Measurements ◽  
Combined Sewer ◽  
Receiving Stream ◽  
Control Criteria

The control strategy of a combined sewer system incorporating three stormwater storage tanks with overflows presented here attempts to consider all aspects of acute CSO effects. These are the hydraulic and the composition components as well as the time factor. The result is an integrated approach, which is not based on the classic emission view (i.e. reduction of volume), but on pollution criteria (i.e. possible harm to the biotic community). The aim is to reduce the exceeding of critical peak values of the CSO components at critical time intervals. Control decisions will be based on continuous measurements in the sewer system and in the receiving stream. Furthermore the measurements are carried out to determine the effects (both hydraulic and chemical) of particular CSO discharges in order to evolve the critical values for the project area. The chemical and physical measurements are accompanied by a biological monitoring programme. Macroinvertebrates are sampled upstream and downstream of outfalls and at a reference site. This allows the evaluation of the control measures on an ecological basis, and thus an assessment of the ecological potential of radar-aided real-time control of the combined sewer systems.

scholarly journals Quality control of direct cell–mineral adhesion measurements in air and liquid using inverse AFM imaging

RSC Advances ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 5384-5392
Author(s):  
Abd Alaziz Abu Quba ◽  
Gabriele E. Schaumann ◽  
Mariam Karagulyan ◽  
Doerte Diehl
Keyword(s):  
Quality Control ◽  
Single Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
C Cell ◽  
Afm Imaging ◽  
Direct Cell ◽  
Mineral Interaction

Setup for a reliable cell-mineral interaction at the single-cell level, (a) study of the mineral by a sharp tip, (b) study of the bacterial modified probe by a characterizer, (c) cell-mineral interaction, (d) subsequent check of the modified probe.

Single-Cell Sequencing in Precision Medicine

2019 ◽  
pp. 237-252 ◽  
Author(s):  
Julia E. Wiedmeier ◽  
Pawan Noel ◽  
Wei Lin ◽  
Daniel D. Von Hoff ◽  
Haiyong Han
Keyword(s):  
Precision Medicine ◽  
Single Cell ◽  
Single Cell Sequencing

scholarly journals Sparsely-connected autoencoder (SCA) for single cell RNAseq data mining

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Luca Alessandri ◽  
Francesca Cordero ◽  
Marco Beccuti ◽  
Nicola Licheri ◽  
Maddalena Arigoni ◽  
...  
Keyword(s):  
Quality Control ◽  
Single Cell ◽  
Medical Personnel ◽  
Cellular Heterogeneity ◽  
Biological Information ◽  
Cell Clusters ◽  
The Neural Network ◽  
Rnaseq Data ◽  
Functional Features ◽  
Cell Subpopulations

AbstractSingle-cell RNA sequencing (scRNAseq) is an essential tool to investigate cellular heterogeneity. Thus, it would be of great interest being able to disclose biological information belonging to cell subpopulations, which can be defined by clustering analysis of scRNAseq data. In this manuscript, we report a tool that we developed for the functional mining of single cell clusters based on Sparsely-Connected Autoencoder (SCA). This tool allows uncovering hidden features associated with scRNAseq data. We implemented two new metrics, QCC (Quality Control of Cluster) and QCM (Quality Control of Model), which allow quantifying the ability of SCA to reconstruct valuable cell clusters and to evaluate the quality of the neural network achievements, respectively. Our data indicate that SCA encoded space, derived by different experimentally validated data (TF targets, miRNA targets, Kinase targets, and cancer-related immune signatures), can be used to grasp single cell cluster-specific functional features. In our implementation, SCA efficacy comes from its ability to reconstruct only specific clusters, thus indicating only those clusters where the SCA encoding space is a key element for cells aggregation. SCA analysis is implemented as module in rCASC framework and it is supported by a GUI to simplify it usage for biologists and medical personnel.

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