What alona is

alona is a cloud-based bioinformatics service designed to analyze single cell RNA sequencing (scRNA-seq) data. alona performs advanced visualization, processing and cell type prediction of scRNA-seq using machine learning models to achieve accurate inference of biological cell types. alona currently works with data from mouse and human. (If data are human then genes will be mapped to mouse orthologs.)

alona is a free service developed and provided by the Integrated Cardio Metabolic Centre at the Karolinska Institutet to the scientific community.

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How alona works

The flowchart to the left illustrates the basic steps in the analysis. The boxes in yellow illustrate steps performed by alona.

alona takes as input a gene expression matrix from a single cell RNA sequencing experiment. Data should have been mapped and reads counted using external software.

The uploaded data can come from any single cell protocol and platform; if the data are from full-length mRNA-seq, then alona performs RPKM/FPKM calculation on the fly as part of the process.

If there are no errors, the analysis usually completes within 10 to 15 minutes on a dataset consisting of 5000 cells. An e-mail will automatically be sent when the report is available for download.

alona generates a document in PDF format, which contains analysis results and plots. Raw latex source for the document can also be downloaded.

How to prepare your data

alona only needs a gene expression matrix. A matrix with genes as rows and cells as columns is needed for input into alona. 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 extension, and it can be compressed using zip, gzip or bzip2. alona also understands single cell data in R's RDS object format.

alona prefers the raw read count matrix as input; however, you can also upload gene expression data that have been normalized (in that case this is specified when uploading the data)

The file name must contain only latin characters.

Supported data formats

  • A plain text gene expression matrix (supported but not recommended)
  • A compressed plain text gene expression matrix in one of the following formats:
    • gzip
    • bzip2
    • zip
  • Matrix object stored in R's RDS format

Detailed description on data preparation

alona assumes that you have already performed basic data processing (alignments, read counting, etc). See here for general guidance how to prepare scRNA-seq data. Also see here for our own tutorial on how to preparing a dataset for analysis.

Example datasets

Can be used for testing.

GEO Accession Species Tissue Normalization
GSE112008 Mus musculus Hematopoietic stem cells Scaled + log2
GSE95315 Mus musculus Brain Read counts
GSE111136 Mus musculus Dermal fibroblasts Read counts
GSE108020 Mus musculus Neurons FPKM
GSM2858342 Mus musculus Alveolar type II cells Scaled + log2

Privacy notice

All uploaded datasets are kept strictly confidential: your data are only seen by you. alona deletes your data and analysis results immediately whenever requested.

Current system status

Queued datasets: 0