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galaxyproject · Dec 18, 2023 · ab79c8a · ab79c8a
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diff --git a/topics/single-cell/tutorials/scrna-data-ingest/tutorial.md b/topics/single-cell/tutorials/scrna-data-ingest/tutorial.md
@@ -62,7 +62,7 @@ To start with, here are the most common formats and datatypes that you might com
 - **Tabular** - simply using TSV, CSV or TXT formats to store expression matrix as well as cell and gene metadata. 
 - **MTX** - it's just a sparse matrix format with genes on the rows and cells on the columns as output by Cell Ranger.
 - **HDF5** - Hierarchical Data Format - can store datasets and groups. A dataset is a  a multidimensional array of data elements, together with supporting metadata. A group is a structure for organizing objects in an HDF5 file. This format allows for storing both the count matrices and all metadata in a single file rather than having separate features, barcodes and matrix files. 
-- **AnnData objects** - [anndata](link https://anndata.readthedocs.io/en/latest/) is a Python package for handling annotated data matrices. In Galaxy, you'll see AnnData objects in **h5ad** format, which is based on the standard HDF5 (h5) format. There are lots of Python tools that work with this format, such as Scanpy, MUON, Cell Oracle, SquidPy, etc. 
+- **AnnData objects** - [anndata](https://anndata.readthedocs.io/en/latest/) is a Python package for handling annotated data matrices. In Galaxy, you'll see AnnData objects in **h5ad** format, which is based on the standard HDF5 (h5) format. There are lots of Python tools that work with this format, such as Scanpy, MUON, Cell Oracle, SquidPy, etc. 
 - **Loom** - it is simply an HDF5 file that contains specific groups containing the main matrix as well as row and column attributes and can be read by any language supporting HDF5. [Loompy](https://linnarssonlab.org/loompy/) has been released as a Python API to interact with loom files, and [loomR](https://github.com/mojaveazure/loomR) is its implementation in R. 
 - **Zarr** - a Python package providing an implementation of compressed, chunked, N-dimensional arrays, designed for use in parallel computing. The Zarr file format offers powerful compression options, supports multiple data store backends, and can read/write your NumPy arrays.
 - **Seurat objects** - a representation of single-cell expression data for R, in Galaxy you might see them in **rdata** format.