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Updated: Jul 22, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

A universal tool for predicting differentially active features in single-cell and spatial genomics data.

Alexis Vandenbon^1,2, Diego Diez^3,4

¹Institute for Life and Medical Sciences, Kyoto University, 53 Shougoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan. alexisvdb@infront.kyoto-u.ac.jp.

Scientific Reports

|July 22, 2023

Summary

This summary is machine-generated.

The updated singleCellHaystack tool efficiently predicts active genes and features across diverse genomics data types. It now handles complex spatial and trajectory data, offering faster analysis for large datasets.

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A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Published on: March 1, 2017

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Single-cell and spatial genomics generate complex data requiring efficient exploratory analysis tools.
Predicting gene activity without cell clustering is crucial for unbiased analysis.

Purpose of the Study:

To present an updated singleCellHaystack method for universally predicting differentially active features.
To enhance the method's applicability to various genomics data types and coordinate systems.

Main Methods:

The updated singleCellHaystack accepts continuous features (RNA, protein, chromatin accessibility, module scores).
It accommodates 1D trajectories, 2-3D spatial coordinates, and higher-dimensional latent spaces.
The method is implemented in R and Python packages for broad accessibility.

Main Results:

singleCellHaystack now predicts differentially active features across single-cell, spatial, and bulk genomics data.
Computational time is reduced up to tenfold, enabling scalability to millions of cells.
The tool supports diverse input coordinate systems, including trajectories and spatial data.

Conclusions:

The enhanced singleCellHaystack is a versatile and efficient tool for exploratory data analysis in genomics.
Its improved performance and broad applicability make it suitable for large-scale atlas datasets.