Unlock Full-Length Transcript Diversity with Advanced Bioinformatics
Single-cell long-read sequencing captures full-length transcript isoforms, but the computational analysis remains a bottleneck. Our custom bioinformatics service provides end-to-end analysis pipelines tailored to your project’s goals. From raw read alignment to isoform quantification, splicing analysis, and cell-type annotation, we apply validated methods to extract maximal biological insight from your long-read single-cell data. Whether you are studying novel isoform discovery, allelic expression, or alternative splicing in disease contexts, our team delivers actionable results supported by rigorous quality control.
Building on established workflows such as FLAMES, SiCeLoRe, and bambu-clump, we customize the analysis to your sequencing platform (e.g., PacBio HiFi, Oxford Nanopore) and experimental design. Our approach handles the sparse coverage and high dropout rates inherent to single-cell long-read data, ensuring sensitive detection of low-abundance isoforms. We also provide interactive visualizations and comprehensive reports to facilitate downstream interpretation.
What We Offer
Full-Length Isoform Discovery
Detect novel isoforms, splice variants, and fusion transcripts at single-cell resolution using pipelines benchmarked for long-read data. Custom filtering and annotation ensure biologically relevant results.
Cell-Type Annotation & Clustering
Apply marker-based or unsupervised methods to assign cell identities, integrate with reference atlases, and resolve rare or transitional populations from full-length transcript profiles.
Multi-Omics Integration
Combine single-cell long-read transcriptomics with other modalities (e.g., proteomics, epigenomics) to uncover regulatory mechanisms and biomarker candidates. Analysis scoped per project.
Our Analysis Workflow
Raw long reads are demultiplexed, adapter-trimmed, and quality filtered. Poly(A) tail detection and UMI deduplication are performed using platform-specific tools to produce clean, error-corrected transcripts.
Full-length reads are aligned to the reference genome with long-read aware aligners (e.g., minimap2). Transcript assembly is carried out using tools like FLAMES or bambu to reconstruct full-length isoforms.
Isoform-level expression is quantified using count-based or probabilistic methods. Differential isoform usage and alternative splicing events (e.g., intron retention, exon skipping) are identified across conditions.
Single-cell expression matrices are clustered using graph-based or iterative methods. Cell-type identities are annotated via marker gene lists, reference mapping, or automated classifiers tailored to your tissue or species.
Interactive reports include UMAP/t-SNE projections, isoform heatmaps, splicing event summaries, and gene-level comparisons. All outputs are delivered in standard formats (e.g., PDF, HTML, CSV) for easy downstream analysis.
Deliverables & Scope
| Item | Description |
|---|---|
| Data Processing | FASTQ processing, quality control reports, and deduplication |
| Isoform Detection | Full-length isoform identification, quantification, and annotation |
| Splicing Analysis | Differential splicing, intron retention, and alternative isoform usage |
| Cell-Type Annotation | Clustering, marker-based annotation, and visualization |
| Final Report | Comprehensive HTML report with interactive figures and data tables |
| Technical Support | Subject to customer service consultation |
Why Choose Our Service
Platform Agnostic
Our pipelines support data from PacBio HiFi, Oxford Nanopore, and other long-read platforms. We adapt alignment parameters and error-correction strategies to match your sequencing technology.
Validated Pipelines
We use established, benchmarked workflows (e.g., FLAMES, SiCeLoRe, bambu-clump) that have been systematically evaluated for accuracy in isoform detection and quantification from single-cell long-read data.
Customizable Scope
Analyses are tailored per project — from simple quantification to multi-omics integration. Scope is defined in a detailed Statement of Work before initiation, ensuring alignment with your scientific goals.
Rigorous Quality Control
Each step includes QC metrics (read mapping rates, UMI collapse efficiency, isoform complexity) to flag technical artifacts and ensure data reliability before biological interpretation.
Recent Advances in the Field
Research Spotlight
Single-cell and long-read sequencing to enhance modelling of splicing and cell-fate determination
View on PubMedReady to Analyze Your Single-Cell Long-Read Data?
Contact our bioinformatics team to discuss your project requirements and receive a customized analysis plan tailored to your experimental design and research questions.