Predicts clinical outcomes using single cell data such as flow cytometry data or RNA single cell sequencing data. CytoDx doesn’t require cell gating or clustering to process. It first estimates the association between each single cell and clinical outcome. It then averages cell level associations within samples to obtain predictors for clinical outcome. This software can also predict clinical features even in the presence of batch effects.
A Bayesian hierarchical framework based on a beta-binomial mixture model for testing for differential biomarker expression using single-cell assays. MIMOSA allows the inference to be subject specific, as is typically required when assessing vaccine responses, while borrowing strength across subjects through common prior distributions. We propose two approaches for parameter estimation: an empirical-Bayes approach using an Expectation–Maximization algorithm and a fully Bayesian one based on a Markov chain Monte Carlo algorithm. Cell counts are modeled by a binomial (or multinomial in the multivariate case) distribution and information is shared across subjects through a prior distribution on the unknown proportion(s) of the binomial (or multinomial) likelihood. In order to discriminate between responders and non-responders, the prior is written as a mixture of two beta (or Dirichlet) distributions where the hyper-parameters for each mixture component are shared across subjects.
Criticizes the recent FlowCAP IV challenge. The FloReMi approach consists of four steps: (1) the data is preprocessed, (2) many features are extracted (i.e., properties pertaining to certain cell types), (3) after which a selection of these features is made, and (4) the selected features are used in a regression model to predict the time until the detection of AIDS for the patients.
Studies extracellular vesicle (EV) proteins from human samples. BEAD exploits biotinylated EVs captured on streptavidin-coated polystyrene (PS) beads. It can: (1) improve EV capture efficiency due to the high affinity biotin-streptavidin interaction; (2) offer a simplified assay measured using conventional flow cytometers; (3) enhance detection sensitivity due to EV (and biomarker) concentration on polystyrene (PS) beads.
Retrieves cell populations or states associated with an outcome variable in high-dimensional cytometry data. diffcyt employs high-resolution unsupervised clustering together with supervised statistical analyses. It applies empirical Bayes moderated tests for differential discovery analyses in high-dimensional cytometry data. This tool can account for complex experimental designs, including batch effects, paired designs, and continuous covariates.
Serves for explorative analysis of index-sorted, single-cell transcriptomic data. indeXplorer allows users to explore their own datasets and is designed to use index-sorted datasets. This software supports ordinary single-cell transcriptomic data and can display raw and pre-processed data that are stored in a central data folder. It generates a file of raw read counts with single cells and genes for each transcriptomic data set.
Supplies a platform for designing flow cytometry. FluoroFinder is a cloud-based application with the aim of facilitating the modeling of experimental mechanisms. The application allows users to construct panel by selecting facility’s cytometers and markers based on various settings including target, hosts, or antigens. Lastly, users can pick reagents which are most fitted to their experiments.
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