# Stereo-CITE FF This tutorial will teach you how to run SAW count pipeline on the Stereo-seq chip derived from a fresh frozen (FF) mouse spleen in Stereo-CITE Proteo-Transcriptomics Solution. ## Prerequisites To run `SAW count` pipeline smoothly, you should: * Be acquainted with the Linux system. * Be familiar with running command line tools. * Ensure access to a system that meets the [minimum system requirements](https://stereotoolss-organization.gitbook.io/saw-user-manual-v8.1/download-center#system-requirements). {% hint style="info" %} **Adequate storage** and **sufficient permissions** should be paid more attention to, before running pipelines. {% endhint %} ## Overview of SAW count pipeline Stereo-seq sequencing data from FF tissues is analyzed with `SAW count`. The pipeline usually begins with: * a chip mask file (recording CIDs of the Stereo-seq chip), * gene expression and ADT FASTQ files (from Stereo-seq sequencing), * a reference library (chosen by the organism information), including the protein panel and transcriptome reference. You can refer to [#reference-libraries-1](https://stereotoolss-organization.gitbook.io/saw-user-manual-v8.1/preparation-of-reference#reference-libraries-1 "mention") and build the reference library in CSV format. * one or more microscope images (TIFF or image `.tar.gz` from **StereoMap**). {% hint style="info" %} The compressed image `.tar.gz` file, from StereoMap, saves the original microscope images and the QC information. {% endhint %}

Output results mainly include: * BAMs of alignment and annotation, * processed images, * gene and protein expression matrices at different dimensions, * transcriptomics clustering and differential expression analysis, * proteomics clustering, * an integrated `visualization.tar.gz` for **StereoMap**. ## Demo data Demo data of the mouse spleen from Stereo-seq Chip T is provided in this tutorial. Key features of demo - C04776D6: * Chip size: 1cm \* 1cm (S1) * Bin1: 500nm \* 500nm * Tissue section of 10μm thickness * DAPI-stained image acquired using Motic [The dataset page](http://116.6.21.110:8090/share/21bb9df9-e6c5-47c5-9aa8-29f2d23a6df4) allows you to download the chip mask file, the raw sequencing files in FASTQ format, a TIFF image or an image `tar.gz`, a transcriptome reference, and a protein panel. For better organization, creating new folders for corresponding data is a wise choice. ```sh $ cd /saw # Create sub-folders of different datasets $ mkdir -p datasets/STOmics-RNA-fastqs datasets/STOmics-ADT-fastqs datasets/mask datasets/image datasets/reference ``` ## Command lines {% hint style="info" %} Please create the reference library `ref_libraries.csv` before submitting the task. You can refer to [#reference-libraries-1](https://stereotoolss-organization.gitbook.io/saw-user-manual-v8.1/preparation-of-reference#reference-libraries-1 "mention") and build the reference library. {% endhint %} Set up `SAW count` analysis command in your working directory. ```sh saw count \ --id= \ --sn= \ --omics=transcriptomics,proteomics \ --kit-version="Stereo-CITE T FF V1.1" \ --sequencing-type="PE75_50+100" \ --chip-mask=/path/to/chip/mask \ --organism= \ --tissue= \ --fastqs=/saw/datasets/STOmics-RNA-fastqs \ --adt-fastqs=/saw/datasets/STOmics-ADT-fastqs \ --ref-libraries=/saw/datasets/reference/ref_libraries.csv \ --image-tar=/path/to/image/tar ``` Brief descriptions of the mentioned parameters in command lines:

Parameter	Description
`--id`	(Optional, default to None) A unique task id ([a-zA-Z0-9_-]+) which will be displayed as the output folder name and the title of HTML report. If the parameter is absent, `--sn` will play the same role.
`--sn <SN>`	(Required, default to None) SN (serial number) of the Stereo-seq chip.
`--omics <OMICS>`	(Required, default to "transcriptomics") Omics information. "transcriptomics,proteomics" for Stereo-CITE analysis.
`--kit-version <TEXT>`	(Required, default to None) The version of the product kit. More in count pipeline introduction.
`--sequencing-type <TEXT>`	(Required, default to None) Sequencing type of FASTQs which is recorded in the sequencing report.
`--chip-mask <MASK>`	(Required, default to None) Stereo-seq chip mask file.
`--organism <TEXT>`	(Optional, default to None) Organism type of sample, usually referring to species.
`--tissue <TEXT>`	(Optional, default to None) Physiological tissue of sample.
`--ref-libraries <CSV>`	(Optional, default to None) Path to a `ref_libraries.csv` which declares the Transcriptome reference index built by `SAW makeRef --mode=STAR` , and the protein panel. Not compatible with `--reference`.
`--fastqs <PATH>`	(Required, default to None) Path(s) to folder(s), containing all needed gene expression FASTQs. If FASTQs are stored in multiple directories, use it as: `--fastqs=/path/to/directory1,/path/to/directory2,...`. Notice that all FASTQ files under these directories will be loaded for analysis.
`--adt-fastqs <PATH>`	(Optional, default to None) Path(s) to folder(s), containing all needed ADT FASTQs. If FASTQs are stored in multiple directories, use it as: `--adt-fastqs=/path/to/directory1,/path/to/directory2,...`. Notice that all FASTQ files under these directories will be loaded for analysis.
`--image <TIFF>`	(Optional, default to None) TIFF image for QC (quality control), combined with expression matrix for analysis. Name rule for input TIFF : a. `<SN>_<stain_type>.tif` b. `<SN>_<stain_type>.tiff` c. `<SN>_<stain_type>.TIF` d. `<SN>_<stain_type>.TIFF` <stainType> includes: a. ssDNA b. DAPI c. HE (referring to H&E) d. <_IF_name1>_IF, <IF_name2>_IF, ...
`--image-tar <TAR>`	(Optional, default to None) The compressed image `.tar.gz` file from StereoMap has been through prepositive QC (quality control).

## Run SAW count Set up `SAW count` analysis command in your working directory. ```sh cd /saw/runs saw count \ --id=Demo_Mouse_Spleen \ --sn=C04776D6 \ --omics=transcriptomics,proteomics \ --kit-version="Stereo-CITE T FF V1.1" \ --sequencing-type="PE75_50+100" \ --chip-mask=/saw/datasets/mask/C04776D6.barcodeToPos.h5 \ --organism=mouse \ --tissue=spleen \ --fastqs=/saw/datasets/STOmics-RNA-fastqs \ --adt-fastqs=/saw/datasets/STOmics-ADT-fastqs \ --ref-libraries=/saw/datasets/reference/ref_libraries.csv \ --image-tar=/saw/datasets/image/C04776D6_SC_20250306_110538_4.1.1.tar.gz ``` {% hint style="info" %} Content of ref\_libraries.csv : ``` Reference,Type /saw/datasets/reference/reference-data-mouse_SAW_v8,STAR /saw/datasets/reference/ProteinPanel_128_mouse_V2.list,ProteinMap ``` {% endhint %} {% hint style="info" %} If you input a or certain images in TIFF, the prefixes of the file names should be: **\\_\\_\*.tif** e.g.: * C04144D5\_ssDNA.tif * SS200000135TL\_D1\_DAPI.tif {% endhint %} ## Explore the output structure After pipeline analysis is completed, a new folder named `Demo_Mouse_Spleen` (which is provided by `--id`, or by `--sn` in the absence of `--id`) will appear in your working directory. All the metadata and outputs generated from `SAW count` are listed below: ``` Demo_Mouse_Thymus ├── pipeline-logs ├── STEREO_ANALYSIS_WORKFLOW_PROCESSING └── outs ├── analysis ├── bam ├── feature_expression ├── image ├── .report.html └── visualization.tar.gz ```

If you want to dig deeper into the results, * Jump to the [`report.html`](https://stereotoolss-organization.gitbook.io/saw-user-manual-v8.1/analysis/outputs/html-report) inside `.report.tar.gz`. * Explore the [`visualization.tar.gz`](https://stereotoolss-organization.gitbook.io/saw-user-manual-v8.1/analysis/outputs/count-outputs#visualization.tar.gz) in **StereoMap**. * Learn more about the individual files on the [Outputs](https://stereotoolss-organization.gitbook.io/saw-user-manual-v8.1/analysis/outputs) page.