Paradigm4 has launched its Reveal: Single Cell app to offer biopharmaceutical developers the ability to break through the data wrangling and programming challenges associated with the analysis of large-scale, single-cell datasets.
Its built on top of Paradigm4’s Agile Science engine, SciDB, an analytics platform organized around vectors and multidimensional arrays that enables scientific data modelling, storage, and large-scale computation.
This storage and elastic computing platform is a massively parallel, transaction-safe, array-oriented, analytics solution.
The Reveal: Single Cell app enables scientists to make connections across large data sets and combines ‘omics modalities to test hypotheses. Users can select cells of interest across any or all studies using individual metadata tags to evaluate tissue distribution, variance in response to treatment, and for comparisons of normal to diseased cells. It features GUIs and R, Python, and REST connectors for data management and analysis.
The higher-level interface means that there is less programming required to access and analyse data. Users can organize datasets in their own data models, transforming ways of working with single cells.
Recently, in partnership with a pharmaceutical company, Paradigm4 used the app to analyse cells in the COVID Cell Atlas, a database of cells which stores information from patients infected with COVID-19.
Zachary Pitluk, Vice President of Life Sciences and Healthcare at Paradigm4, commented: “When Covid-19 hit earlier this year, we used our REVEAL: Single Cell app to identify tissues expressing the key SARS-CoV-2 entry associated genes in seconds. We found they were expressed in multiple tissue types, thus explaining the multi-organ involvement in infected patients observed worldwide during the ongoing pandemic.”
Marilyn Matz, co-founder and CEO of Paradigm4, commented: “Accelerating drug and biomarker discovery is a key driver for our customers. Our Agile Science engine, SciDB, with its REVEAL apps, transforms the way researchers integrate, share, and gain insights from multimodal scientific data.”
