SeekSoul Online

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### Download SeekSoul Tools v2.0.0 using wget

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/2_Download.html

This command downloads the SeekSoul Tools v2.0.0 archive using wget. It specifies the output filename and the download URL. Ensure wget is installed on your system.

```shell
wget -c -O seeksoultools.2.0.0.tar.gz "https://seekgene-public.oss-cn-beijing.aliyuncs.com/software/seeksoultools/seeksoultools.2.0.0.tar.gz"
```

--------------------------------

### Install Necessary Packages and Create Directories (R)

Source: https://seeksoul.online/cloudplatform-doc/zh/document/General/Notebooks.src/scatac-seq-gene-activity-analysis-tutorial.html

This R code snippet includes comments for adding necessary packages and checking/creating directories for saving output. It's a common setup step for data analysis and visualization workflows.

```R
# 添加必要的包
# 检查并创建保存目录
```

--------------------------------

### Install SeekSoul Tools v2.0.0 and set environment variables

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/2_Download.html

This script first extracts the downloaded SeekSoul Tools archive, then changes the directory. It sets the PATH environment variable to include the current directory and appends this to the ~/.bashrc file for persistence. Finally, it verifies the installation by running the --version command.

```shell
# 解压
tar zxf seeksoultools.2.0.0.tar.gz
cd seeksoultools.2.0.0

# 设置环境变量
export PATH=`pwd`:$PATH
echo "export PATH=$(pwd):$PATH" >> ~/.bashrc

# 初始化和安装验证，初次执行所需时间稍长
`pwd`/seeksoultools --version
```

--------------------------------

### Run RNA Analysis with Specific STAR Version

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/3_Use_guide/1_rna/2_Analysis.html

This example shows how to run SeekSoul Tools while specifying a particular STAR aligner executable path. This is useful for ensuring compatibility between the STAR version and the pre-built genome index.

```shell
seeksoultools rna run \
--fq1 /path/to/demo_dd/demo_dd_S39_L001_R1_001.fastq.gz \
--fq2 /path/to/demo_dd/demo_dd_S39_L001_R2_001.fastq.gz \
--samplename demo_dd \
--genomeDir /path/to/GRCh38/star \
--gtf /path/to/GRCh38/genes/genes.gtf \
--chemistry DDV2 \
--core 4 \
--include-introns \
--star_path /path/to/cellranger-5.0.0/lib/bin/STAR
```

--------------------------------

### SeekSoul Tools RNA Analysis - Basic Usage

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/3_Use_guide/1_rna/2_Analysis.html

This example demonstrates the basic command to run SeekSoul Tools for RNA analysis. It includes essential parameters like FASTQ file paths, sample name, genome directory, GTF file, chemistry type, and CPU core count.

```APIDOC
## POST /seeksoultools/rna

### Description
Runs SeekSoul Tools for RNA analysis with essential configuration parameters.

### Method
POST

### Endpoint
/seeksoultools/rna

### Parameters
#### Query Parameters
- **fq1** (PATH) - Required - Path to the Read1 FASTQ file. Can be specified multiple times.
- **fq2** (PATH) - Required - Path to the Read2 FASTQ file. Can be specified multiple times and must correspond to `--fq1`.
- **samplename** (TEXT) - Required - Name of the sample.
- **genomeDir** (PATH) - Required - Path to the directory containing the genome index. Must be compatible with the STAR version.
- **gtf** (PATH) - Required - Path to the GTF file.
- **chemistry** (TEXT) - Optional - Reagent type used in the experiment. Options: DDV2, DD5V1, MM, MM-D.
- **core** (INTEGER) - Optional - Maximum number of CPU cores to use for the analysis. Default: 4.
- **include-introns** - Optional - Whether to include intronic regions in the analysis.

### Request Example
```json
{
  "fq1": "/path/to/demo_dd/demo_dd_S39_L001_R1_001.fastq.gz",
  "fq2": "/path/to/demo_dd/demo_dd_S39_L001_R2_001.fastq.gz",
  "samplename": "demo_dd",
  "genomeDir": "/path/to/GRCh38/star",
  "gtf": "/path/to/GRCh38/genes/genes.gtf",
  "chemistry": "DDV2",
  "core": 4,
  "include-introns": true
}
```

### Response
#### Success Response (200)
- **status** (TEXT) - Indicates the success of the operation.
- **message** (TEXT) - Provides details about the result of the analysis.

#### Response Example
```json
{
  "status": "success",
  "message": "RNA analysis completed successfully."
}
```
```

--------------------------------

### SeekSoul Tools RNA Analysis - Multiple FASTQ Files per Sample

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/3_Use_guide/1_rna/2_Analysis.html

This example demonstrates how to handle samples with multiple FASTQ data sets by providing paths for all relevant FASTQ files.

```APIDOC
## POST /seeksoultools/rna

### Description
Runs SeekSoul Tools for RNA analysis when a sample has multiple FASTQ files.

### Method
POST

### Endpoint
/seeksoultools/rna

### Parameters
#### Query Parameters
- **fq1** (PATH) - Required - Path to the Read1 FASTQ file. Can be specified multiple times for multiple FASTQ sets.
- **fq2** (PATH) - Required - Path to the Read2 FASTQ file. Can be specified multiple times for multiple FASTQ sets and must correspond to `--fq1`.
- **samplename** (TEXT) - Required - Name of the sample.
- **genomeDir** (PATH) - Required - Path to the directory containing the genome index. Must be compatible with the STAR version.
- **gtf** (PATH) - Required - Path to the GTF file.
- **chemistry** (TEXT) - Optional - Reagent type used in the experiment. Options: DDV2, DD5V1, MM, MM-D.
- **core** (INTEGER) - Optional - Maximum number of CPU cores to use for the analysis. Default: 4.
- **include-introns** - Optional - Whether to include intronic regions in the analysis.

### Request Example
```json
{
  "fq1": [
    "/path/to/demo_dd_S39_L001_R1_001.fastq.gz",
    "/path/to/demo_dd_S39_L002_R1_001.fastq.gz"
  ],
  "fq2": [
    "/path/to/demo_dd_S39_L001_R2_001.fastq.gz",
    "/path/to/demo_dd_S39_L002_R2_001.fastq.gz"
  ],
  "samplename": "demo",
  "genomeDir": "/path/to/GRCh38/star",
  "gtf": "/path/to/GRCh38/genes/genes.gtf",
  "chemistry": "DDV2",
  "core": 4,
  "include-introns": true
}
```

### Response
#### Success Response (200)
- **status** (TEXT) - Indicates the success of the operation.
- **message** (TEXT) - Provides details about the result of the analysis.

#### Response Example
```json
{
  "status": "success",
  "message": "RNA analysis with multiple FASTQ files completed successfully."
}
```
```

--------------------------------

### Verify SeekSpace Tools Installation

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/2_SeekSpace_Tools/1_v1.0.2/2_Download.html

This snippet provides the command to verify that SeekSpace® Tools has been successfully installed. Running 'seekspacetools --version' will display the installed version of the software.

```shell
seekspacetools --version
```

--------------------------------

### Run SeekSoul Tools for Basic Analysis (Shell)

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/3_Use_guide/5_probe/2_Analysis.html

This example demonstrates the basic usage of SeekSoul Tools for running an analysis. It requires specifying input FASTQ files, a sample name, the number of CPU cores to use, and an output directory. Ensure that the specified file paths for `--fq1` and `--fq2` are correct.

```shell
seeksoultools probe \
  --fq1 /path/to/demo_dd/XYRD-WTCY851_S6_L006_R1_001.fastq.gz \
  --fq2 /path/to/demo_dd/XYRD-WTCY851_S6_L006_R2_001.fastq.gz \
  --samplename WTCY851 \
  --core 8 \
  --outdir ./WTCY851
```

--------------------------------

### Display column names of colData in R

Source: https://seeksoul.online/cloudplatform-doc/zh/document/General/Notebooks.src/banksy-spatial-clustering-analysis.html

This R code snippet prints the names of all columns within the `colData` of the `spe` object. This is useful for inspecting the available metadata and identifying the cluster labels generated by Banksy, which typically start with 'clust'. The output is a numbered list of column names.

```R
colnames(colData(spe))
```

--------------------------------

### SeekSpace® Tools - Run Example

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/2_SeekSpace_Tools/1_v1.0.2/4_Analysis.html

This section demonstrates the basic usage of the `seekspacetools run` command, including setting up necessary configuration files for analysis, such as sample data paths, reagent types, genome indices, and GTF files.

```APIDOC
## POST /seekspacetools/run

### Description
Runs the primary analysis pipeline for spatial transcriptomics data. This command requires configuration of various input files and parameters to process FASTQ data, align it to a reference genome, and perform UMI counting and cell calling.

### Method
`seekspacetools run`

### Endpoint
N/A (Command-line tool)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None (Uses command-line arguments)

### Request Example
```shell
seekspacetools run \
--fq1 /path/to/demo/demo_expression_S8_L007_R1_001.fastq.gz \
--fq2 /path/to/demo/demo_expression_S8_L007_R2_001.fastq.gz \
--spatialfq1 /path/to/demo/demo_spatial_S7_L007_R1_001.fastq.gz \
--spatialfq2 /path/to/demo/demo_spatial_S7_L007_R2_001.fastq.gz \
--hdmifq /path/to/demo/2P231224030A4.fq.gz \
--samplename demo \
--outdir /path/to/outdir \
--genomeDir /path/to/GRCh38/star \
--gtf /path/to/GRCh38/genes/genes.gtf \
--chemistry DDVS \
--core 4 \
--include-introns \
--forceCell 80000 \
--min_umi 200 \
--chip_id 2P231224030A4 \
--DAPI /path/to/demo/2P231224030A4.tif
```

### Parameters Description
*   `--fq1` (string) - Required - Path to the R1 FASTQ file for the expression library.
*   `--fq2` (string) - Required - Path to the R2 FASTQ file for the expression library.
*   `--spatialfq1` (string) - Required - Path to the R1 FASTQ file for the spatial library.
*   `--spatialfq2` (string) - Required - Path to the R2 FASTQ file for the spatial library.
*   `--hdmifq` (string) - Required - Path to the HDMI library FASTQ file.
*   `--samplename` (string) - Required - Sample name. Supports only numbers, letters, and underscores.
*   `--outdir` (string) - Optional - Directory for output results. Defaults to './'.
*   `--genomeDir` (string) - Required - Path to the reference genome built by STAR. The version must be consistent with the STAR used by SeekSpace® Tools.
*   `--gtf` (string) - Required - Path to the GTF file for the corresponding species.
*   `--chemistry` (string) - Required - Reagent type. Options: DDVS (Spatial Transcriptomics Reagent Kit).
*   `--core` (integer) - Optional - Number of threads to use for analysis. Defaults to system available cores.
*   `--include-introns` (boolean) - Optional - If enabled, intron reads will also be used for quantification. Defaults to exon reads only.
*   `--forceCell` (integer) - Optional - Forces the tool to select the top N cells based on UMI counts. Defaults to 80000.
*   `--min_umi` (integer) - Optional - Minimum number of UMIs per cell. Cells with fewer UMIs will be discarded. Defaults to 200.
*   `--chip_id` (string) - Required - Chip ID.
*   `--DAPI` (string) - Optional - Path to the DAPI-stained tissue image (TIFF).
*   `--HE` (string) - Optional - Path to the H&E stained tissue image (TIFF). Requires `--HE` to be specified if provided.
*   `--skip_misB` (boolean) - Optional - Disallows base mismatches in barcodes. Defaults to allowing one mismatch.
*   `--skip_misL` (boolean) - Optional - Disallows base mismatches in linkers. Defaults to allowing one mismatch.
*   `--skip_multi` (boolean) - Optional - Discards reads that can be corrected to multiple whitelist barcodes. Defaults to correcting to the barcode with the highest proportion.
*   `--star_path` (string) - Optional - Path to a different STAR version for alignment. The version must be compatible with the `--genomeDir` version. Defaults to the STAR found in the environment.

### Response
#### Success Response (200)
Details of the analysis results, including file paths to generated reports and data.

#### Response Example
```json
{
  "status": "success",
  "message": "Analysis completed successfully.",
  "results_path": "/path/to/outdir"
}
```
```

--------------------------------

### Create and Manage Python Environment with Micromamba (Bash)

Source: https://seeksoul.online/cloudplatform-doc/zh/document/SeekSoulOnline_Document/18_Notebooks.html

This bash script demonstrates the process of creating a Python environment using micromamba, activating it, installing essential packages like ipykernel and scanpy, and then registering the Python kernel with Jupyter. It also includes steps for removing the environment and its kernel.

```bash
# Create Python environment
micromamba create --prefix /jp_envs/envs_user/{UserId}/DemoPython
micromamba activate /jp_envs/envs_user/{UserId}/DemoPython
micromamba install -c conda-forge -c bioconda -c defaults ipykernel scanpy
python -m ipykernel install --name DemoPython --display-name "DemoPython" --prefix /jp_envs/kernels_user/{UserId}/ 

# Register kernel with Jupyter
jupyter kernelspec install /jp_envs/kernels_user/{UserId}/share/jupyter/kernels/demopython --user
micromamba deactivate

# Remove Python environment and kernel
jupyter-kernelspec remove demopython
micromamba env remove --prefix /jp_envs/envs_user/{UserId}/DemoPython
```

--------------------------------

### Extract Chromosome, Start, and End from Peak Data - Python

Source: https://seeksoul.online/cloudplatform-doc/zh/document/General/Notebooks.src/atac-seq-snp-enrichment-analysis.html

This Python code processes a Pandas DataFrame containing peak identifiers. It splits the 'peak' column by '-' to extract the chromosome window, chromosome, start position, and end position. The start and end positions are converted to integers. This prepares the data for genomic interval analysis.

```python
all_peaks = pd.DataFrame(peaks.columns, columns=['peak'])

split_result = all_peaks['peak'].str.split('-', expand=True)
all_peaks['peak_window'] = split_result[1] + "_" + split_result[2]  # 直接字符串拼接
all_peaks['chrom'] = split_result[0]
all_peaks['start'] = split_result[1].astype(int)  # 转为整数
all_peaks['end'] = split_result[2].astype(int)

# 设置索引
all_peaks = all_peaks.set_index('peak')
```

--------------------------------

### Run Basic Analysis with SeekSpace Tools

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/2_SeekSpace_Tools/1_v1.0.2/4_Analysis.html

This command initiates a basic analysis using SeekSpace Tools. It requires specifying input FASTQ files for expression and spatial libraries, sample name, output directory, genome and GTF paths, chemistry type, and computational resources. Optional parameters like `--HE` for H&E images can also be included.

```shell
seekspacetools run \
--fq1 /path/to/demo/demo_expression_S8_L007_R1_001.fastq.gz \
--fq2 /path/to/demo/demo_expression_S8_L007_R2_001.fastq.gz \
--spatialfq1 /path/to/demo/demo_spatial_S7_L007_R1_001.fastq.gz \
--spatialfq2 /path/to/demo/demo_spatial_S7_L007_R2_001.fastq.gz \
--hdmifq /path/to/demo/2P231224030A4.fq.gz \
--samplename demo \
--outdir /path/to/outdir \
--genomeDir /path/to/GRCh38/star \
--gtf /path/to/GRCh38/genes/genes.gtf \
--chemistry DDVS \
--core 4 \
--include-introns \
--forceCell 80000 \
--min_umi 200 \
--chip_id 2P231224030A4 \
--DAPI /path/to/demo/2P231224030A4.tif
```

--------------------------------

### Visualize Banksy cluster results spatially in R

Source: https://seeksoul.online/cloudplatform-doc/zh/document/General/Notebooks.src/banksy-spatial-clustering-analysis.html

This code snippet generates spatial visualizations for all Banksy clustering results. It first identifies column names starting with 'clust', combines spatial coordinates with `colData`, and then iterates through each cluster column to create a spatial plot using `plotColData`. Finally, it arranges these plots in a grid using `plot_grid` for easy comparison. The plots visualize spatial patterns of different clusters.

```R
# banksy各参数组合分析得到的所有聚类标签下的空间可视化
cnames <- grep("^clust", colnames(colData(spe)), value = TRUE)
colData(spe) <- cbind(colData(spe), spatialCoords(spe))

plots <- list()

for (i in seq_along(cnames)) {
  plots[[i]] <- plotColData(spe, x = "spatial_1", y = "spatial_2", point_size = 1, colour_by = cnames[i]) + coord_equal()
}

options(repr.plot.height=16, repr.plot.width=16)

plot_grid(plotlist = plots, ncol = 2)
```

--------------------------------

### Run Basic RNA Analysis with SeekSoul Tools

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/3_Use_guide/1_rna/2_Analysis.html

This snippet demonstrates the fundamental command to initiate an RNA analysis using SeekSoul Tools. It requires specifying input FASTQ files, sample name, genome directory, GTF file, chemistry type, and the number of CPU cores.

```shell
seeksoultools rna \
--fq1 /path/to/demo_dd/demo_dd_S39_L001_R1_001.fastq.gz \
--fq2 /path/to/demo_dd/demo_dd_S39_L001_R2_001.fastq.gz \
--samplename demo_dd \
--genomeDir /path/to/GRCh38/star \
--gtf /path/to/GRCh38/genes/genes.gtf \
--chemistry DDV2 \
--core 4 \
--include-introns
```

--------------------------------

### Download SeekSoul Tools v2.0.0 using curl

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/2_Download.html

This command downloads the SeekSoul Tools v2.0.0 archive using curl. It uses the -C option to resume interrupted downloads and specifies the output filename and download URL. Ensure curl is installed on your system.

```shell
curl -C - -o seeksoultools.2.0.0.tar.gz "https://seekgene-public.oss-cn-beijing.aliyuncs.com/software/seeksoultools/seeksoultools.2.0.0.tar.gz"
```

--------------------------------

### Install and Activate SeekSpace Tools

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/2_SeekSpace_Tools/1_v1.0.2/2_Download.html

This snippet covers the installation process for SeekSpace® Tools after downloading. It includes decompressing the archive, activating a virtual environment using 'source', unpacking conda, and exporting the tool's binary path to the bashrc file for persistent access.

```shell
# decompress
tar zxf seekspacetools_v1.0.2.tar.gz

# install
source ./bin/activate
./bin/conda-unpack

# export path in bashrc
export PATH=`pwd`/bin:$PATH
echo "export PATH=$(pwd)/bin:\$PATH" >> ~/.bashrc
```

--------------------------------

### Adjust Peak Window Size - Python

Source: https://seeksoul.online/cloudplatform-doc/zh/document/General/Notebooks.src/atac-seq-snp-enrichment-analysis.html

This Python code adjusts the 'start' and 'end' columns of a Pandas DataFrame ('all_peaks') based on a specified 'window_size'. It calculates an adjustment value and applies it to the start and end positions, effectively expanding or contracting the genomic window. This is useful for defining regions of interest around peaks.

```python
# select a window size (bp) of interest (by default it is 500bp)
window_size=500
window_adjustment=(window_size-500)/2
#print('adjustment '+str(window_adjustment))
window_size_for_filename='peak_width_'+str(window_size)
#print(window_size_for_filename)

all_peaks['start']=all_peaks['start'].apply(lambda x: x-window_adjustment)
all_peaks['end']=all_peaks['end'].apply(lambda x: x+window_adjustment)
```

--------------------------------

### SeekSoul Tools RNA Analysis - Specify STAR Version

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/3_Use_guide/1_rna/2_Analysis.html

This example shows how to specify a particular version of STAR for the analysis to ensure compatibility with the generated genome index.

```APIDOC
## POST /seeksoultools/rna/run

### Description
Runs SeekSoul Tools for RNA analysis, allowing specification of a custom STAR executable path.

### Method
POST

### Endpoint
/seeksoultools/rna/run

### Parameters
#### Query Parameters
- **fq1** (PATH) - Required - Path to the Read1 FASTQ file. Can be specified multiple times.
- **fq2** (PATH) - Required - Path to the Read2 FASTQ file. Can be specified multiple times and must correspond to `--fq1`.
- **samplename** (TEXT) - Required - Name of the sample.
- **genomeDir** (PATH) - Required - Path to the directory containing the genome index. Must be compatible with the STAR version.
- **gtf** (PATH) - Required - Path to the GTF file.
- **chemistry** (TEXT) - Optional - Reagent type used in the experiment. Options: DDV2, DD5V1, MM, MM-D.
- **core** (INTEGER) - Optional - Maximum number of CPU cores to use for the analysis. Default: 4.
- **include-introns** - Optional - Whether to include intronic regions in the analysis.
- **star_path** (TEXT) - Optional - Path to the STAR executable. Defaults to the STAR found in the current environment. Must be compatible with `--genomeDir`.

### Request Example
```json
{
  "fq1": "/path/to/demo_dd/demo_dd_S39_L001_R1_001.fastq.gz",
  "fq2": "/path/to/demo_dd/demo_dd_S39_L001_R2_001.fastq.gz",
  "samplename": "demo_dd",
  "genomeDir": "/path/to/GRCh38/star",
  "gtf": "/path/to/GRCh38/genes/genes.gtf",
  "chemistry": "DDV2",
  "core": 4,
  "include-introns": true,
  "star_path": "/path/to/cellranger-5.0.0/lib/bin/STAR"
}
```

### Response
#### Success Response (200)
- **status** (TEXT) - Indicates the success of the operation.
- **message** (TEXT) - Provides details about the result of the analysis.

#### Response Example
```json
{
  "status": "success",
  "message": "RNA analysis with specified STAR version completed successfully."
}
```
```

--------------------------------

### Create and Manage R Environment with Micromamba (Bash)

Source: https://seeksoul.online/cloudplatform-doc/zh/document/SeekSoulOnline_Document/18_Notebooks.html

These bash commands illustrate how to create a new R environment using micromamba, activate it, install necessary packages like r-irkernel and r-seurat, and then install the R kernel into Jupyter. It also covers how to remove the R environment and its kernel.

```bash
# Create R environment
micromamba create --prefix /jp_envs/envs_user/{UserId}/DemoR
micromamba activate /jp_envs/envs_user/{UserId}/DemoR
micromamba install -c conda-forge -c bioconda -c defaults r-irkernel r-seurat=4.*

# Start R interactive environment and install kernel
R
Sys.setenv(PATH = paste("/home/mambauser/bin:/home/mambauser/env/jupyter/bin",Sys.getenv("PATH"), sep = ":"))
IRkernel::installspec(name = 'DemoR', displayname = 'DemoR', prefix = '/jp_envs/kernels_user/{UserId}/')
q()

# Register kernel with Jupyter
jupyter kernelspec install /jp_envs/kernels_user/{UserId}/share/jupyter/kernels/demor --user
micromamba deactivate

# Remove R environment and kernel
jupyter-kernelspec remove demor
micromamba env remove --prefix /jp_envs/envs_user/{UserId}/DemoR
```

--------------------------------

### Load R Packages for Analysis

Source: https://seeksoul.online/cloudplatform-doc/zh/document/General/Notebooks.src/banksy-spatial-clustering-analysis.html

This R code snippet loads all necessary R packages for performing spatial clustering analysis using Banksy and related tools. It includes packages like Seurat, Banksy, SummarizedExperiment, SpatialExperiment, scuttle, scater, cowplot, and ggplot2. Ensure these packages are installed before running.

```R
library(Seurat)
library(Banksy)
library(SummarizedExperiment)
library(SpatialExperiment)
library(scuttle)
library(scater)
library(cowplot)
library(ggplot2)
```

--------------------------------

### Run RNA Analysis with Multiple FASTQ Files per Sample

Source: https://seeksoul.online/cloudplatform-doc/zh/document/Software/3_SeekSoul_Tools/1_v2.0.0/3_Use_guide/1_rna/2_Analysis.html

This command illustrates how to handle scenarios where a single sample is associated with multiple pairs of FASTQ files. All relevant FASTQ files for a sample should be provided, with `--fq1` and `--fq2` arguments listed sequentially.

```shell
seeksoultools rna \
--fq1 /path/to/demo_dd_S39_L001_R1_001.fastq.gz \
--fq1 /path/to/demo_dd_S39_L002_R1_001.fastq.gz \
--fq2 /path/to/demo_dd_S39_L001_R2_001.fastq.gz \
--fq2 /path/to/demo_dd_S39_L002_R2_001.fastq.gz \
--samplename demo \
--genomeDir /path/to/GRCh38/star \
--gtf /path/to/GRCh38/genes/genes.gtf \
--chemistry DDV2 \
--core 4 \
--include-introns
```

--------------------------------

### Integrate Metadata into Seurat Object

Source: https://seeksoul.online/cloudplatform-doc/zh/document/General/Notebooks.src/banksy-spatial-clustering-analysis.html

Assigns the loaded metadata to the `@meta.data` slot of the Seurat object. This step is crucial for associating cell-specific information with the expression data.

```r
rownames(meta) = meta$barcode
obj@meta.data = meta
```

--------------------------------

### Setup seeksoultools Environment for Fusion Analysis

Source: https://seeksoul.online/cloudplatform-doc/zh/document/General/document.src/FAST_Fusion_Module_Documentation.html

Downloads and sets up the seeksoultools environment, which is a dependency for the STAR-Fusion analysis. It involves downloading a tarball and activating the environment.

```shell
# seeksoultools
wget -c -O seeksoultools_fast_mut_dev.tar.gz "https://seekgene-public.oss-cn-beijing.aliyuncs.com/software/FAST/Fusion.v1/seeksoultools_fast_mut_dev.tar.gz"
# Decompress
mkdir seeksoultools
tar -zxvf seeksoultools_fast_mut_dev.tar.gz -C seeksoultools
source seeksoultools/bin/activate
seeksoultools/bin/conda-unpack
```
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