/hdst

Primary LanguageJupyter Notebook

HDST

This is a public repository for all code connected to HDST (High-definition spatial transcriptomics).

Please cite: Vickovic S et al. High-definition spatial transcriptomics for in situ tissue profiling. Nat Methods 2019: doi: https://doi.org/10.1038/s41592-019-0548-y

Tech workflow

github-small

File Structure Overview

All processed files are available at: https://portals.broadinstitute.org/single_cell/study/SCP420

github-small

We recommed using the Bulk Download function and to consult the Metadata file.

*red_ut*files: Sorted counts tsv files with:

bc barcode (XxY) coordinate
spot_px_x representing (x) pixel coordinate in the HE image and Xin bc
spot_px_y representing (y) pixel coordinate in the HE image and Yin bc
gene representing the gene name
count representing UMI filtered expressed counts per corresponding gene

(Note: spatial resolution is marked as HDST, 5x or segmentsin all file names)

*barcodes_under_tissue_annot*files: files conenction (x,y) coordinates to annotation regions in HDST with:

bc barcode (XxY) coordinate
spot_px_x representing (x) pixel coordinate in the HE image and Xin bc
spot_px_y representing (y) pixel coordinate in the HE image and Yin bc annotation_region` as region names to each (x,y) coordinate

*HE.png files are HE images used in the study

*HE_Probabilities_mask.tiff files are coordinates of segmented nuclei based on corresponding HE images

Files needed to run the ST pipeline:

*.fastq raw seq data with encoded barcode information
*barcode_ids.tsv ids files needed for demultiplexing

Alignment

This is code for aligning HE images to (x,y) barcode coordiantes as given by ST Pipeline (v.1.5.1).

Segmentation

This is code for segmenting HE nuclei. HE image segmentation was performed by combining Ilastik and CellProfiler. The labeled segmentation mask was used to assign the individual spots to the corresponding Cell ID. The output CSV file includes Cell IDs, X and Y position of the cells (centroid) and the corresponding spots.

Cell typing

This is code for imputing cell types onto (x,y) spatial positions based on scRNA-seq data.

Differential expression (DE) analysis

This is code for DE analysis between annotated regions.