Biology subjects

PONT, F.

Publications and source records attributed to PONT, F..

3 recordsLinked to original sources

bioRxiv2022

Single-cell Spatial Explorer: Easy exploration of spatial and multimodal transcriptomics

The development of single cell technologies yields large datasets of informations as diverse and multimodal as transcriptomes, immunophenotypes, and spatial position from tissue sections in the so-called spatial transcriptomics. Currently however, user-friendly, powerful, and free algorithmic tools for straightforward analysis of spatial transcriptomic datasets are scarce. Here, we introduce Single-Cell Spatial Explorer, an open-source software for multimodal exploration of spatial transcriptomics, examplified with 6 human and murine tissues datasets.

bioinformatics↗

bioRxiv2019

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

The 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.

bioinformatics↗

bioRxiv2019

Single-Cell Signature Explorer for comprehensive visualization of single cell signatures across scRNA-seq data sets

The momentum of scRNA-seq data sets prompts for simple and powerful tools exploring their meaningful signatures. Here we present Single-Cell_Signature_Explorer (https://sites.google.com/site/fredsoftwares/products/single-cell-signature-explorer), the first method for high throughput scoring at single cell level of any gene set-based signature and visualization across t-SNE. By scanning data sets for single or combined signatures, it quantitatively and qualitatively maps any multi-gene feature, exemplified here with signatures of cell lineages, biological hallmarks and metabolic pathways in large scRNAseq datasets of human PBMC, lung cancer and adult testis.

bioinformatics↗