alona is a web-based bioinformatics service
designed to analyze single cell RNA sequencing (scRNA-seq)
data. This service performs processing, analysis and
visualization using some of the most popular scRNA-seq
algorithms. Cells are annotated into cell types using
marker genes from PanglaoDB. Instead of using the default
marker genes, the user can also provide such a
list. Processed data can be explored from an intuitive web
An example of scRNA-seq data from the mouse brain. See below for more examples.
The service is free and it is provided by the Integrated Cardio Metabolic Centre at the Karolinska Institutet .
alona is based on the
adobo Python package
The flowchart to the left illustrates the basic steps
in the analysis. The boxes in yellow illustrate steps
A gene expression from a scRNA-seq experiment is accepted as input. Data should have been mapped and reads counted using external software.
The uploaded data can come from any single cell protocol or platform.
The analysis usually completes within 10 to 15 minutes on a dataset consisting of 5000 cells. An e-mail can be sent as a reminder.
alona generates an archive of files in
tar.gz format, containing analysis results and plots.
Only a gene expression matrix is needed with genes as rows and cells as columns. Single cell gene expression matrices are often large because thousands of cells are usually sampled. The matrix is either a plain text file, having any arbitrary filename, and it must be compressed using zip, gzip, bzip2 or xz. The correct filename extension must be used for the corresponding compression (i.e. zip for zip, gz for gzip, bz2 for bzip2, and xz for xz).
Uploaded data must not be normalized; i.e., measurements should be raw read counts.
The file name must contain only latin characters.
alonaassumes that you have already performed basic data processing (alignments, read counting, etc). See here for our guide on how to preparing a dataset for analysis with alona.