scholarly journals FlowCal: A User-Friendly, Open Source Software Tool for Automatically Converting Flow Cytometry Data from Arbitrary to Calibrated Units

2016 ◽  
Vol 5 (7) ◽  
pp. 774-780 ◽  
Author(s):  
Sebastian M. Castillo-Hair ◽  
John T. Sexton ◽  
Brian P. Landry ◽  
Evan J. Olson ◽  
Oleg A. Igoshin ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Open Source ◽  
Open Source Software ◽  
Software Tool ◽  
Flow Cytometry Data ◽  
User Friendly

A New Method for Morphometric Analysis of Opal Phytoliths from Plants

2014 ◽  
Vol 20 (6) ◽  
pp. 1876-1887 ◽  
Author(s):  
Welmoed A. Out ◽  
José F. Pertusa Grau ◽  
Marco Madella
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Standard Method ◽  
Morphometric Analysis ◽  
Software Tool ◽  
New Method ◽  
Phytolith Analysis ◽  
Opal Phytoliths ◽  
User Friendly ◽  
Comparability Of Results

AbstractMicro-morphometry has substantially gained ground in the field of phytolith analysis, but the comparability of results is limited due to the use of different methods. This paper presents a new, user-friendly method based on open-source software (FIJI) that is proposed as a step towards the introduction of a standard method. After obtaining a mask of a phytolith by making a digital drawing, 27 commonly used variables of size and shape are measured automatically. This method is not only useful for phytolith analysis, but may also be used for other fields of morphometric research. Users can furthermore customize the software tool when additional variables are required.

scholarly journals Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Frédéric Pont ◽  
Marie Tosolini ◽  
Qing Gao ◽  
Marion Perrier ◽  
Miguel Madrid-Mencía ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Single Cell ◽  
Open Source ◽  
Open Source Software ◽  
Healthy Donor ◽  
Large Datasets ◽  
Integrated Analysis ◽  
Functional Maturation ◽  
User Friendly ◽  
Cell Data

Abstract The development of single-cell transcriptomic technologies yields large datasets comprising multimodal informations, such as transcriptomes and immunophenotypes. Despite the current explosion of methods for pre-processing and integrating multimodal single-cell data, there is currently no user-friendly software to display easily and simultaneously both immunophenotype and transcriptome-based UMAP/t-SNE plots from the pre-processed data. Here, we introduce Single-Cell Virtual Cytometer, an open-source software for flow cytometry-like visualization and exploration of pre-processed multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of transcriptomes and epitopes of functional maturation in human peripheral T lymphocytes. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.

scholarly journals Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets

2019 ◽  
Author(s):  
Frédéric Pont ◽  
Marie Tosolini ◽  
Qing Gao ◽  
Marion Perrier ◽  
Miguel Madrid-Mencía ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Single Cell ◽  
Open Source ◽  
Open Source Software ◽  
Healthy Donor ◽  
Large Datasets ◽  
Integrated Analysis ◽  
Functional Maturation ◽  
Healthy Donors ◽  
User Friendly

ABSTRACTThe development of single cell transcriptomic technologies yields large datasets comprising multimodal informations such as transcriptomes and immunophenotypes. Currently however, there is no software to easily and simultaneously analyze both types of data. Here, we introduce Single-Cell Virtual Cytometer, an open-source software for flow cytometry-like visualization and exploration of multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of transcriptomes and phenotypes of functional maturation in peripheral T lymphocytes from healthy donors. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.

scholarly journals ELIMU-MDx: a web-based, open-source platform for storage, management and analysis of diagnostic qPCR data

BioTechniques ◽  
2020 ◽  
Vol 68 (1) ◽  
pp. 22-27 ◽  
Author(s):  
Silvan Krähenbühl ◽  
Fabian Studer ◽  
Etienne Guirou ◽  
Anna Deal ◽  
Philipp Mächler ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Tool ◽  
Turnaround Time ◽  
Storage Management ◽  
Quantitative Real Time Pcr ◽  
Web Browser ◽  
Web Based ◽  
Data Standard ◽  
User Friendly

The Electronic Laboratory Information and Management Utensil for Molecular Diagnostics (ELIMU-MDx) is a user-friendly platform designed and built to accelerate the turnaround time of diagnostic qPCR assays. ELIMU-MDx is compliant with Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines and has extensive data-import capabilities for all major qPCR instruments by using the RDML data standard. This platform was designed as an open-source software tool and can be accessed through the web browser on all major operating systems.

scholarly journals Cantera: an open source software tool for integrating complex thermo-chemistry into device-level simulations

2020 ◽  
Author(s):  
Richard West ◽  
Robert Kee ◽  
Kyle Niemeyer ◽  
Steven C. DeCaluwe ◽  
C. Goldsmith ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Tool

scholarly journals An uncertainty-based protocol for the setup and measurement of soot/black carbon emissions from gas flares using sky-LOSA

2020 ◽  
Author(s):  
Bradley M. Conrad ◽  
Matthew R. Johnson
Keyword(s):  
Open Source ◽  
Black Carbon ◽  
Open Source Software ◽  
Carbon Emissions ◽  
Climate Models ◽  
Optical Measurement ◽  
Measurement Data ◽  
Software Tool ◽  
Measurement Protocol ◽  
Measurement Uncertainties

Abstract. Gas flaring is an important source of atmospheric soot/black carbon, especially in sensitive Arctic regions. However, emissions have traditionally been challenging to measure and remain poorly characterized, confounding international reporting requirements and adding uncertainty to climate models. The sky-LOSA optical measurement technique has emerged as a powerful means to quantify flare black carbon emissions in the field, but broader adoption has been hampered by the complexity of its deployment, where decisions during setup in the field can have profound, non-linear impacts on achievable measurement uncertainties. To address this challenge, this paper presents a prescriptive measurement protocol and associated open-source software tool that simplifies acquisition of sky-LOSA data in the field. Leveraging a comprehensive Monte Carlo-based General Uncertainty Analysis (GUA) to predict measurement uncertainties over the entire breadth of possible measurement conditions, general heuristics are identified to guide a sky-LOSA user toward optimal data collection. These are further extended in the open-source software utility, SetupSkyLOSA, which interprets the GUA results to provide detailed guidance for any specific combination of location, date/time, and flare, plume, and ambient conditions. Finally, a case study of a sky-LOSA measurement at an oil and gas facility in Mexico is used to demonstrate the utility of the software tool, where potentially small region(s) of optimal instrument setup are easily and quickly identified. It is hoped that this work will help increase the accessibility of the sky-LOSA technique and ultimately the availability of field measurement data for flare black carbon emissions.

Prospects of Open Source Software for Maximizing the User Expectations in Heterogeneous Network

2021 ◽  
pp. 257-271
Author(s):  
Pushpa Singh ◽  
Rajeev Agrawal
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Real Time ◽  
Open Source Software ◽  
Heterogeneous Networks ◽  
Heterogeneous Network ◽  
Research Work ◽  
Software Tool ◽  
Knn Classifier ◽  
User Expectations

This article focuses on the prospects of open source software and tools for maximizing the user expectations in heterogeneous networks. The open source software Python is used as a software tool in this research work for implementing machine learning technique for the categorization of the types of user in a heterogeneous network (HN). The KNN classifier available in Python defines the type of user category in real time to predict the available users in a particular category for maximizing profit for a business organization.

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