Galaxy | Tool Preview

Seurat Read10x (version 4.0.4+galaxy0)
10X MTX or tabular
Raw expression quantification as a sparse matrix in Matrix Market format, where each column is a gene and each row is a barcode/cell.
Matrix market column file for genes
Matrix market row file for genes
File with metdata for the cells, first column should be cell identifiers as used in the cells 10x file.
Include features detected in at least this many cells. Will subset the counts matrix as well. To reintroduce excluded features, create a new object with a lower cutoff.
Include cells where at least this many features are detected.
Seurat, Single Cell Experiment, AnnData or Loom

What it does

Seurat is a toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. It is developed and maintained by the Satija Lab at NYGC. Seurat aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

Read expression data from a tabular file or a 10x-Genomics-formatted mtx directory (`read_10x_mtx`)

For mtx, the directory should contain:

  1. Raw expression quantification as a sparse matrix in Matrix Market format, where the each column is a gene and each row is a barcode/cell.
  2. A gene table of at least two columns where the first column gives the gene IDs.
  3. A barcode/cell table of at least one column giving the barcode/cell IDs.

The above-mentioned files can be obtained by running EBI SCXA Data Retrieval with a dataset accession. Otherwise, they need to be provided as separate Galaxy datasets.

Inputs
  • A tabular file of expression data OR
    • Raw expression quantification as a sparse matrix in Matrix Market format, where the each column is a gene and each row is a barcode/cell.
    • A gene table of at least two columns where the first column gives the gene IDs.
    • A barcode/cell table of at least one column giving the barcode/cell IDs.
  • Optionally, a file with cell metadata.
Outputs
  • R object for Seurat

Version history 4.0.0: Moves to Seurat 4.0.0, introducing a number of methods for merging datasets, plus the whole suite of Seurat plots. Pablo Moreno with funding from AstraZeneca.

3.2.3+galaxy0: Moves to Seurat 3.2.3 and introduce convert method, improving format interconversion support.

3.1.2_0.0.8: Update metadata parsing

3.1.1_0.0.7: Exposes perplexity and enables tab input.

3.1.1_0.0.6+galaxy0: Moved to Seurat 3.

Find clusters: removed dims-use, k-param, prune-snn.

2.3.1+galaxy0: Improved documentation and further exposition of all script's options. Pablo Moreno, Jonathan Manning and Ni Huang, Expression Atlas team https://www.ebi.ac.uk/gxa/home at EMBL-EBI https://www.ebi.ac.uk/. Parts obtained from wrappers from Christophe Antoniewski (GitHub drosofff) and Lea Bellenger (GitHub bellenger-l).

0.0.1: Initial contribution. Maria Doyle (GitHub mblue9).