SeekGene Bio Documentation Center

Author: Liu Xin

Time: 100 min

Words: 19.9k words

Updated: 2026-07-17

Reads: 0 times

document_library

Overview

This center brings together standardized documentation covering the entire process from experimental preparation and sequencing to data analysis, aiming to provide clear and accurate operational guidance and theoretical support to help your research progress efficiently and smoothly.

Document Browsing

Use the filters on the left and the search box on the right to quickly locate documents; browse the list with pagination, and click a title to open the corresponding guide.

Filter

Products

• SeekSoul™ Online
• scATAC + RNA-seq
• Spatial-seq
• 3' scRNA-seq
• 5' + Immune Profiling
• scFAST-seq
• FFPE scRNA-seq
• scMethyl + RNA-seq

Topic

• Analysis Guide
• Notebooks
• Method
• FAQ

Analysis Type

• Data Integration
• Batch Effect
• Basic Analysis
• Cell Annotation
• Peak-Gene Links
• SNP Enrichment
• Differential Enrichment
• Co-localization
• Plotting
• Activity
• Copy Number Variation
• Pseudotime
• Niche
• Mutation
• Cell Communication
• Correlation

List

SeekSoul™ Online platform overview and entry

SeekSoul™ Online is a one-stop single-cell multi-omics data mining and visualization online tool developed by SeekBio over two years covering standard and advanced analysis workflows for single-cell transcriptomics single-cell immunology and SeekBio's in-house single-cell spatial transcriptomics products. The analysis results are highly consistent with those from code execution providing users with comprehensive deep data analysis solutions across multiple fields including disease mechanism exploration biological target mining and basic scientific research.

Tag：SeekSoul™ Online

2025/8/28

DD ATAC + RNA multi-omics to 10x and Cell Ranger ARC analysis guide

Coverage of converting DD ATAC/GE data to 10x ARC supported format fastp quality control barcode conversion and Cell Ranger ARC running examples.

Tag：scATAC + RNA-seq , Analysis Guide , FAQ

2025/8/7

scATAC-seq Differential Accessibility and Functional Enrichment Analysis Tutorial

ATAC_DiffEnrich is a workflow for differential accessibility and enrichment analysis of scATAC-seq in single-cell multi-omics data.

Tag：scATAC + RNA-seq , Analysis Guide , Notebooks , Differential Enrichment⬇ Export ipynb

2026-01-29

scATAC-seq Pseudotime Analysis: Chromatin Dynamic Trajectory Resolution

The ATAC_Monocle3 analysis pipeline is designed for trajectory inference and developmental dynamics research of single-cell ATAC-seq data.

Tag：scATAC + RNA-seq , Analysis Guide , Notebooks , Pseudotime⬇ Export ipynb

2026-01-29

scATAC-seq Advanced Analysis: Peak-Gene Regulatory Association Analysis

ATAC_Peak2Gene is a Peak-to-Gene association analysis pipeline for integrating scATAC-seq and scRNA-seq in single-cell multi-omics data.

Tag：scATAC + RNA-seq , Analysis Guide , Notebooks , Peak-Gene Links⬇ Export ipynb

2026-01-29

scATAC-seq Variation Analysis: SNP Enrichment in Chromatin Open Regions

Genome-Wide Association Studies (GWAS) are key tools for resolving the genetic basis of complex traits.

Tag：scATAC + RNA-seq , Analysis Guide , Notebooks , SNP Enrichment⬇ Export ipynb

2026-01-29

ataCNV Analysis Tutorial: Tumor Copy Number Variation Resolution Based on scATAC-seq

Chromosomal Copy Number Variation (CNV) is a hallmark of tumor genomic instability, characterized by large-scale amplification or deletion of chromosomal segments.

Tag：scATAC + RNA-seq , Analysis Guide , Notebooks , Copy Number Variation⬇ Export ipynb

2026-01-29

CopyscAT Analysis: scATAC-seq-based CNV Inference and Tumor Identification

Chromosomal Copy Number Variation (CNV) is a typical hallmark of tumor genomic instability, characterized by large-scale amplification or deletion of chromosomal segments.

Tag：scATAC + RNA-seq , Analysis Guide , Notebooks , Copy Number Variation⬇ Export ipynb

2026-01-29

epiAneufinder Analysis: Aneuploidy Detection Based on scATAC-seq

Chromosomal Copy Number Variation (CNV) is a hallmark of tumor genome instability, characterized by large-scale amplification or deletion of chromosomal segments.

Tag：scATAC + RNA-seq , Analysis Guide , Notebooks , Copy Number Variation⬇ Export ipynb

2026-01-29

Single-Cell Spatial Transcriptomics Quality Control Report Documentation

This document details the definitions, calculation methods, and interpretation guidelines for various metrics and charts in the spatial transcriptomics quality control report generated by the SeekSpace Tools software. It aims to help users understand the sequencing data and library quality, and provide a reference for subsequent data analysis.

Tag：Spatial-seq , Analysis Guide

2026-04-01

Single-Cell Spatial Transcriptomics - H&E and DAPI Image Registration Guide

A standardized operating guide using GIMP to spatially register H&E brightfield images with DAPI fluorescent images, covering DAPI preprocessing, layer stacking and opacity settings, move/scale/rotate registration, canvas and background fixing, layer merging and export, and an optional tissue extraction step.

Tag：Spatial-seq , Analysis Guide

2026-03-30

Single-Cell Spatial Transcriptomics - Spatial Visualization Guide

This tutorial is specifically designed for handling the underlying spatial geometric transformations of SeekGene single-cell spatial transcriptomics products, aiming to help you deeply understand and achieve precise alignment between chip coordinates and tissue images.

Tag：Spatial-seq , Analysis Guide , Notebooks⬇ Export ipynb

2026-04-10

Single-Cell Spatial Transcriptomics Analysis Guideline

Provides a systematic downstream analysis workflow and tutorial guideline for single-cell spatial transcriptomics data, covering key steps such as basic quality control and integration, spatial microenvironment clustering, spatial colocalization, and multi-dimensional cell communication analysis.

Tag：Spatial-seq , Analysis Guide

2026-06-22

Single-cell Spatial Transcriptomics - Spatial Clustering Analysis

This module is based on the Banksy algorithm and is designed for spatial clustering and domain segmentation of spatial transcriptomics data.

Tag：Spatial-seq , Analysis Guide , Notebooks , Niche⬇ Export ipynb

2026-04-13

Single-Cell Spatial Transcriptomics - Spatial Neighborhood Enrichment Analysis (Based on CellCharter)

This module evaluates spatial colocalization patterns between different cell populations by constructing a spatial proximity network among cells.

Tag：Spatial-seq , Analysis Guide , Notebooks , Co-localization⬇ Export ipynb

2026-05-27

Single-cell Spatial Transcriptomics - Cell Type Colocalization Analysis (Based on MISTy)

This module is used to perform multi-scale cell type colocalization and spatial dependency analysis on spatial transcriptomics data.

Tag：Spatial-seq , Analysis Guide , Notebooks , Co-localization⬇ Export ipynb

2026-05-27

Single-Cell Spatial Transcriptomics - Spatial Ligand-Receptor Colocalization Analysis (based on SpaGene)

This module is used to analyze the spatial colocalization patterns of ligands and receptors.

Tag：Spatial-seq , Analysis Guide , Notebooks , Co-localization⬇ Export ipynb

2026-05-27

Single-Cell Spatial Transcriptomics - Cell Communication Analysis (Based on COMMOT)

This module uses optimal transport theory to infer intercellular communication in spatial transcriptomics data.

Tag：Spatial-seq , Analysis Guide , Notebooks , Cell Communication⬇ Export ipynb

2026-05-27

Single-Cell Spatial Transcriptomics - Cell Communication Analysis (based on CellPhoneDB)

This module fully considers the multi-subunit structure of receptors and ligands, enabling accurate identification and representation of heteromeric complexes and intercellular interaction networks in spatial data.

Tag：Spatial-seq , Analysis Guide , Notebooks , Cell Communication⬇ Export ipynb

2026-06-04

Single-Cell Spatial Transcriptomics - Cell Communication Analysis (based on NicheNet)

This module can not only infer ligand-receptor interactions, but also link the expression of ligands in sender cells to changes in target gene expression in receiver cells.

Tag：Spatial-seq , Analysis Guide , Notebooks , Cell Communication⬇ Export ipynb

2026-06-12

Pseudotime-Dependent Gene Screening Tutorial: Exploring Dynamic Changes in Gene Expression Along Trajectories

This tutorial uses the Monocle2 framework to identify genes that change dynamically along pseudotime trajectories and fits gene expression trends using natural spline curves to explore regulatory mechanisms during cell differentiation.

Tag：3' scRNA-seq , Analysis Guide , Notebooks , Pseudotime⬇ Export ipynb

2026-01-29

DD5 VDJ Data Method

Tag：5' + Immune Profiling , Method

2026-01-29

DD5 16S Data Method

Tag：5' + Immune Profiling , Method

2026-01-29

Tumor cell calling by integrating CNV and mutations (threshold-based)

Tag：scFAST-seq , Analysis Guide

2025/12/23

Single-cell alternative splicing with STARsolo SJ and MARVEL quantification and differential analysis

Tag：scFAST-seq , Analysis Guide

2025/12/23

Full-length alternative splicing analysis with rMATS workflow and example scripts

Tag：scFAST-seq , Analysis Guide

2025/12/23

Full-length fusion detection with STAR-Fusion module guide and interpretation

Tag：scFAST-seq , Analysis Guide

2025/12/23

Full-length mutation analysis with freebayes VEP and vartrix pipeline

Tag：scFAST-seq , Analysis Guide

2025/12/23

scFAST-seq Mutation Analysis: Data Merging, UMAP Display and Integration

scFAST-seq mutation analysis tutorial, covering mutation data merging from multiple samples, UMAP dimensionality reduction visualization based on mutation features, and multi-sample integration workflow.

Tag：scFAST-seq , Notebooks , Mutation⬇ Export ipynb

2026-01-29

scFAST-seq Mutation Analysis: Dynamic Display of Mutations on Pseudotime Trajectory

Based on monocle2 pseudotime analysis results, visualize the dynamic evolution of mutations along cell development trajectories to help identify key mutations related to development or differentiation.

Tag：scFAST-seq , Notebooks , Pseudotime⬇ Export ipynb

2026-01-29

Single-cell Fine Resolution: Cell Clustering Strategy Based on LncRNA Expression Features

This article explores a supplementary strategy for cell clustering in single-cell RNA sequencing analysis using long non-coding RNAs (LncRNAs) in addition to traditional highly variable genes.

Tag：scFAST-seq , Notebooks , Basic Analysis⬇ Export ipynb

2026-01-29

FFPE single-cell data processing: ambient RNA removal doublet filtering parameter tuning

Provides background removal (SoupX) doublet filtering and parameter optimization workflows for FFPE sample background RNA doublets and quality control issues.

Tag：FFPE scRNA-seq , FAQ

2025/7/25

scMethyl + RNA Multi-omics Quality Control Report Documentation

Details the definitions, calculation methods, and interpretation guidelines for various metrics in the SeekMethyl QC report, aiming to help users understand sequencing data and library quality.

Tag：scMethyl + RNA-seq , Analysis Guideline

2026-03-16

scMethyl + RNA Multi-omics SeekSoul Online Platform Jupyter Analysis User Guide

This guide is intended for users who have completed the standard methylation pipeline analysis and wish to conduct downstream personalized analysis in the SeekSoul Online Platform Jupyter environment.

Tag：scMethyl + RNA-seq , Analysis Guideline

2026-07-06

scMethyl + RNA Multi-omics Analysis Guideline

Provides systematic downstream analysis pipelines and tutorial guidelines for single-cell methylation multi-omics, covering key steps such as doublet detection, data QC and integration, and differential and functional enrichment analysis.

Tag：scMethyl + RNA-seq , Analysis Guideline

2026-03-16

scMethyl + RNA Multi-omics - Basic Analysis

This module is designed for the basic analysis of single-cell methylation multi-omics data (containing both RNA and methylation info), implementing core workflows such as data integration, quality control, batch effect correction, and cell atlas construction.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-16

scMethyl + RNA Multi-omics - Doublet Detection

This module aims to identify and filter doublets from single-cell methylation sequencing data, providing three complementary detection methods based on transcriptome cell types, methylation read counts, and methylation rates to improve identification accuracy.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-16

scMethyl + RNA Multi-omics - Integration Analysis Tutorial Based on MOFA+ Algorithm

This tutorial details how to use the MOFA+ (Multi-Omics Factor Analysis v2) framework for multi-omics integration analysis of single-cell methylation (DNA Methylation) and transcriptome (RNA) data.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-30

scMethyl + RNA Multi-omics - Integration Tutorial Using WNN

This tutorial explains how to integrate single-cell DNA methylation and transcriptome (RNA) data using the Scanpy and Muon frameworks. You will build a joint embedding, perform clustering, and visualize results in a unified UMAP space.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-30

scMethyl + RNA Multi-omics - Differential and Functional Enrichment Analysis

This module integrates single-cell methylation differential analysis and functional enrichment analysis, aiming to identify differentially methylated regions/genes and differentially expressed genes from multi-omics data, and further analyze their biological functions via GO and KEGG.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-16

scMethyl + RNA Multi-omics - Inter-group Cell Type Differential Enrichment Analysis

Designed for inter-group differential and functional enrichment analysis of single-cell methylation multi-omics data, this module performs differential expressed gene (DEG) and differentially methylated gene (DMG) analysis for each cell type between groups.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-16

scMethyl + RNA Multi-omics - MethSCAn Differential Methylation Analysis

Based on MethSCAn, this module supports variably methylated region (VMR) detection, cell clustering, and the identification of differentially methylated regions (DMRs) between different cell populations in single-cell methylation data.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-16

scMethyl + RNA Multi-omics - DMR Functional Enrichment Analysis

Based on rGREAT, this module performs functional enrichment analysis on differentially methylated regions (DMRs), linking DMRs to adjacent genes and assessing their enrichment in functional categories like GO and MSigDB to reveal potential biological functions.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-16

scMethyl + RNA Multi-omics - DMR Motif Enrichment Analysis

Based on HOMER, this module is used for DNA sequence motif analysis in genomic regions such as DMRs. It supports de novo motif finding and known motif enrichment analysis to identify transcription factors that may be involved in regulation.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-16

scMethyl + RNA Multi-omics - CNV Analysis

Based on CopyKit, this module is designed to infer genome-wide copy number variations (CNVs) from single-cell sequencing data, supporting variant identification, differentiation between normal and tumor cells, and exploration of intra-tumor heterogeneity and clonal evolution.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-03-16

scMethyl + RNA Multi-omics - MethylTree Lineage Analysis

This module uses MethylTree to construct methylation-based lineage trees, infer clonal structures, and visualize results for scMethyl + RNA multi-omics data.

Tag：scMethyl + RNA-seq , Notebooks⬇ Export ipynb

2026-07-10

Cell Composition Analysis: Bar Plot of Cell Type Proportions Across Samples and Groups

Cell Composition Analysis: Bar Plot of Cell Type Proportions Across Samples and Groups

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Analysis Guide , Notebooks , Plotting⬇ Export ipynb

2026-01-29

Cell Type Enrichment Analysis: Heatmap Plotting Based on Chi-Square Test and R.oe Values

Cell Type Enrichment Analysis: Heatmap Plotting Based on Chi-Square Test and R.oe Values

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Analysis Guide , Notebooks , Plotting⬇ Export ipynb

2026-01-29

Cell Proportion Difference Analysis: Box Plot of Cell Proportions Between Groups

Demonstration using ESCC article reproduction - Myeloid subset reproduction workflow data

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Analysis Guide , Notebooks , Cell Annotation⬇ Export ipynb

2026-01-29

Single-cell Host-Virus Interaction: Correlation between Viral and Host Gene Expression

By observing the correlation between viral gene expression and key host genes, we explore the interaction between viral and host genes to understand how viruses affect host cell functions.

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , Analysis Guide , Notebooks , Correlation⬇ Export ipynb

2026-01-29

Single-Cell Host-Virus Interaction: Correlation Study between Gene Expression Abundance and Viral Load

Gene Expression Abundance: Number of genes expressed in cells Viral Load: Sum of normalized viral gene expression values (refer to the article above)

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , Analysis Guide , Notebooks , Correlation⬇ Export ipynb

2026-01-29

scRNA-seq Cell Annotation Tutorial: Type Identification Based on Marker Genes

Introduces how to use the SingleR automated annotation tool, combined with reference datasets like HumanPrimaryCellAtlas, to perform high-precision cell type identification and annotation for single-cell transcriptomics data.

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Analysis Guide , Notebooks , Cell Annotation⬇ Export ipynb

2026-01-29

Single-cell Visualization Customization: Custom Color and Order t-SNE and Proportion Plot

Single-cell Visualization Customization: Custom Color and Order t-SNE and Proportion Plot

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Notebooks , Cell Annotation⬇ Export ipynb

2026-01-29

Single-cell Differential Expression and Functional Enrichment Analysis Tutorial

Introduces how to perform single-cell differential expression (DE) and functional enrichment analysis (ORA/GSEA) using Seurat and clusterProfiler, covering inter-cluster and group comparisons, GO/KEGG annotations, and visualizations like volcano plots and heatmaps.

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Analysis Guide , Notebooks , Differential Enrichment⬇ Export ipynb

2026-01-29

Visualization of Single-cell Gene Expression Correlation Scatter Plots

Visualization of Single-cell Gene Expression Correlation Scatter Plots

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Notebooks , Plotting⬇ Export ipynb

2026-01-29

Single-cell Gene Expression Dynamics: Pseudotime Gene Expression Curve Fitting

Single-cell Gene Expression Dynamics: Pseudotime Gene Expression Curve Fitting

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Notebooks , Pseudotime⬇ Export ipynb

2026-01-29

scRNA-seq Multi-sample Integration Tutorial (Seurat / Harmony)

This tutorial covers the scRNA-seq multi-sample integration workflow, including two data loading methods (Cloud RDS and standard 10x matrix), Seurat object creation, QC metrics calculation (mitochondrial % / gene counts), and Harmony-based integration for batch effect removal.

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Analysis Guide , Notebooks , Data Integration⬇ Export ipynb

2026-01-29

Seurat scRNA-seq Analysis Workflow Tutorial (QC / Integration / Clustering)

Seurat is a comprehensive R package designed for quality control, analysis, and exploration of single-cell RNA sequencing data. This tutorial provides a complete analysis workflow from data loading to marker finding, covering quality control, DoubletFinder doublet removal, data integration (Harmony/CCA/Merge), dimensionality reduction, clustering, and differential expression analysis. **Important**: This tutorial should be run using the **"common_r"** kernel.

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Analysis Guide , Notebooks , Basic Analysis⬇ Export ipynb

2026-01-29

SeekGene Platform Reference Genome Guide

Systematically summarizes the version information, chromosome composition, gene type statistics, and cloud download resources of the built-in human, mouse, and rat reference genomes on the SeekGene platform, and explains the general download rules for NCBI and Ensembl.

Tag：scATAC + RNA-seq , Spatial-seq , 3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , scMethyl + RNA-seq , Analysis Guide

2026-07-09

DD3 Data Method

Tag：3' scRNA-seq , 5' + Immune Profiling , scFAST-seq , FFPE scRNA-seq , Method

2026-01-29

Hemoglobin gene contamination: sources impact and mitigation (with R examples)

Introduces the sources impacts and various handling methods (filtering gene removal and re-clustering etc.) of hemoglobin gene contamination and provides R code examples.

Tag：Analysis Guide , FAQ

2025/7/25

Exogenous GFP not detected: troubleshooting and GTF annotation fix

Locates the reasons for GFP not being quantified in featureCounts (missing gene/transcript lines in GTF annotations) and provides example commands to fix GTF.

Tag：Analysis Guide

2025/7/25

Oversized chromosome reference splitting and indexing for non-mouse species (samtools compatibility)

Explains the compatibility issues of samtools with oversized chromosome indices and provides splitting scripts and usage instructions for subsequent alignment and indexing.

Tag：Analysis Guide , FAQ

2025/8/7

DD Antibody and CRISPR QC and Cell Ranger analysis guide

Introduces the workflow and considerations for converting DD platform data to 10x format and using Cell Ranger to analyze Antibody/CRISPR data.

Tag：Analysis Guide

2025/8/7

Barcode-Converter: convert DD barcodes to 10x format

Usage instructions for barcode conversion tool example commands and parameter explanations applicable to converting DD barcodes to 10x barcodes.

Tag：Analysis Guide , FAQ

2025/8/7

SeekSoul Tools v1.3.0 special-species VDJ ref preparation workflow (IMGT TRUST4)

Ref preparation workflow for SeekSoul Tools v1.3.0 and TRUST4 including species sequence extraction from IMGT and formatting script examples

Tag：Analysis Guide , FAQ

2025/8/7

Mixed-species scRNA-seq analysis guide: principles interpretation and common issues

Explanation of the principles result interpretation and common issues regarding mixed-species data analysis

Tag：Analysis Guide , FAQ

2025/11/21

Plasma cell immunoglobulin gene contamination: detection impact and downstream recommendations

Assessment of the impact of diffuse active immunoglobulin (IG) gene expression related to plasma cells in the sample along with recommendations for downstream analysis

Tag：Analysis Guide , FAQ

2025/11/26

ATAC + RNA Multi-Omics: Analysis Guide

Systematic overview of ATAC-RNA dual-omics downstream analysis pipelines and tutorials, covering the complete analysis chain from basic quality control to regulatory network construction

Tag：ATAC + RNA Dual-Omics, Analysis Guide

2026/7/6

ATAC + RNA Multi-Omics: Basic Analysis Based on ArchR

Complete workflow for data import and preprocessing, multi-sample joint analysis, dimensionality reduction clustering, and cell type annotation of SeekArc single-cell multi-omics data based on the ArchR framework

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: Single-Sample Basic Analysis Based on Signac

Quality control, dimensionality reduction clustering, cell annotation, downstream differential analysis, Motif analysis, and Footprint analysis of single-sample SeekArc multi-omics data based on the Signac framework

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: Multi-Sample Integration Analysis Based on Signac

Batch effect correction, joint dimensionality reduction clustering, and cell type annotation of multi-sample SeekArc multi-omics data based on Signac + Harmony/CCA

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: Differential Accessibility Analysis

Identification of differentially open chromatin regions between different cell types or experimental conditions, Peak-to-nearest-gene annotation, and GO/KEGG functional enrichment analysis

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: Motif Analysis

Calculation of single-cell Motif activity based on ChromVAR, differential Motif activity analysis and Motif enrichment analysis, inference of upstream transcription factor regulatory mechanisms

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: Peak2Gene Analysis

Calculation of Peak-Gene associations based on the co-variability hypothesis, identification of co-regulated modules via K-means clustering, and Motif/GO/KEGG enrichment analysis

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: Trios Analysis

Integration of Motif activity, Peak-Gene associations, and TF expression information to screen for TF-Peak-Gene triples simultaneously satisfying physical binding, expression covariance, and activity-driven criteria

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: Footprint Analysis

Assessment of actual transcription factor binding activity at base-pair resolution by detecting Tn5 cleavage protection signals, providing direct evidence for validating TF regulatory functions

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: DORC Analysis

Identification of super target genes (DORCs) coordinately regulated by multiple cis-regulatory elements, quantification of DORC activity at single-cell level with differential analysis and visualization

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: SCENIC+ Multi-Omics Regulatory Network Analysis

Construction of a complete transcriptional regulatory network based on the SCENIC+ framework, including eRegulon quality assessment, RSS specificity scoring, multimodal dimensionality reduction, and regulatory network visualization

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: ATAC-Based Monocle3 Analysis

Reconstruction of cell developmental trajectories using the Monocle3 trajectory inference algorithm, detection of Peaks, Motif activities, and gene expression that vary along pseudotime

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks⬇ Export ipynb

2026/7/6

ATAC + RNA Multi-Omics: CopyscAT Analysis

CNV inference and tumor identification based on scATAC-seq. Copy number variation (CNV) is a hallmark of genomic instability in tumors, manifested as large-scale amplifications or deletions of chromosomal segments.

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks, Copy Number Variation Analysis⬇ Export ipynb

2026/1/29

ATAC + RNA Multi-Omics: epiAneufinder Analysis

Aneuploidy detection based on scATAC-seq. Copy number variation (CNV) is a hallmark of genomic instability in tumors, manifested as large-scale amplifications or deletions of chromosomal segments.

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks, Copy Number Variation Analysis⬇ Export ipynb

2026/1/29

ATAC + RNA Multi-Omics: ataCNV Analysis Tutorial

Tumor copy number variation analysis based on scATAC-seq. Copy number variation (CNV) is a hallmark of genomic instability in tumors, manifested as large-scale amplifications or deletions of chromosomal segments.

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks, Copy Number Variation Analysis⬇ Export ipynb

2026/1/29

ATAC + RNA Multi-Omics: Variant Analysis

SNP enrichment in open chromatin regions. Genome-wide association studies (GWAS) are key tools for dissecting the genetic basis of complex traits, and the numerous significant single nucleotide polymorphisms (SNPs) they identify often reside in non-coding regulatory regions of the genome.

Tag：ATAC + RNA Dual-Omics, Analysis Guide, Notebooks, SNP Enrichment Analysis⬇ Export ipynb

2026/1/29

Single-cell FAQ overview

Comprehensive guide covering common questions and recommendations for single-cell sample preparation transportation quality control library construction and downstream analysis.

Tag：FAQ

2025/8/28

SeekArc × 10x cross-platform scRNA-seq integration and batch-effect assessment (Monocle2 hdWGCNA)

The results show that SeekArc platform data has high consistency with 10x platform data, effectively supporting the in-depth development of cross-platform single-cell transcriptome research.

Tag：Batch Effect

2025/12/23

Single-cell annotation for special animal and plant species: markers orthologs enrichment

This article will briefly outline common approaches and methods for single-cell annotation of special species, helping you quickly grasp the relevant content.

Tag：Cell Annotation

2025/8/28

Single-Cell Spatial Transcriptomics - Basic Data Analysis (based on Seurat)

Designed specifically for SeekSpace spatial transcriptomics single-sample data based on the Seurat framework

Tag： this module provides a complete basic analysis pipeline from data loading and quality control to normalization dimensionality reduction and clustering.

./Notebooks.src/Single-Cell_Spatial_Transcriptomics_Basic_Data_Analysis_Seurat.ipynb

Single-Cell Spatial Transcriptomics - Basic Data Analysis (based on Scanpy)

Designed specifically for SeekSpace spatial transcriptomics single-sample data based on the Scanpy framework

Tag： this module provides a complete basic analysis pipeline from data loading and quality control to normalization dimensionality reduction and clustering.

./Notebooks.src/Single-Cell_Spatial_Transcriptomics_Basic_Data_Analysis_Scanpy.ipynb

Single-Cell Spatial Transcriptomics - Cell Communication Analysis (Based on CellChat)

This module is used to infer

Tag： visualize

Spatial-seq , Analysis Guide , Notebooks , Cell Communication

Single-Cell Spatial Transcriptomics - Cell Communication Analysis (based on stLearn)

This module computes ligand-receptor interaction scores and localizes hotspot regions

Tag： integrating cell type and spatial neighborhood information to reveal high-frequency communication likely occurring within tissues; it requires a longer runtime

Spatial-seq , Analysis Guide , Notebooks , Cell Communication

Troubleshooting guide for undetected specific genes (endogenous / exogenous insertion) in scRNA-seq

A structured checklist to identify why a target gene is not detected in scRNA-seq

Tag： covering biological

and computational causes (including exogenous insertions).

Page size5 / page10 / page20 / page30 / page40 / page50 / page100 / pageAllPage 1 / 1 · Total 0

Let's explore the infinite possibilities of life science together!

Built with ❤️ by SeekSoul™ Online Team

---