Spatial transcriptomics

We offer pre-processing of data from 10x Genomics Visium spatial gene expression assays. We use spaceranger count to perform fiducial detection, map the reads to the reference genome and count the number of reads overlapping with each gene to produce a count matrix for each sample. After that, we perform a downstream analysis with the R package Seurat, resulting in quality control, transformation, dimensionality reduction and clustering.

  • Run summary metrics and charts in HTML format
  • HTML report of QC, filtering and normalization
  • HTML report of integration, dimensionality reduction, clustering and differential gene expression analysis
  • Interactive app for exploring your results (optional)
  • Filtered and/or unfiltered feature-barcode matrices in MEX format (optional)
  • Read alignment file in bam format and associated index (optional)
  • Loupe Cell Browser visualization and analysis file (optional)
  • Intermediate results for your own analysis (optional)

 

Note that we also offer more extensive downstream analyses in the form of collaborations. Please contact us for more details.
HTML reports from an example analysis can be downloaded below.

Downloads

spatial_RNAseq_integration-dimRed-clustering.html
(ignore the error message and click the download buttom on the top right)
spatial_RNAseq_qc-filtering-normalization.html