Single Cell Discoveries vs Pepkio: Bioinformatics Service Comparison | Pepkio Compare

Single Cell Discoveries vs Pepkio: Quick Comparison Table

Aspect	Pepkio	Single Cell Discoveries
Analysis types supported	Bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics (10x Visium/Visium HD), WGS/WES variant calling, ChIP-seq, ATAC-seq, metagenomics, and proteomics	Single-cell RNA-seq (10x Chromium 3'/5', Flex, Immune Profiling; Parse Evercode; SORT-seq; VASA-seq), spatial transcriptomics (10x Visium/Visium HD, Xenium), high-throughput screening (DRUG-seq, Discovery-seq), scATAC-seq, ATAC Multiome, low-input bulk RNA-seq
Pipeline tools & versions disclosed	Documented open-source tools (STAR, fastp, DESeq2, Seurat, GATK) with versions, parameters, and executable code included in project deliverables	Documented software tools (Cell Ranger, Seurat, Scanpy, STAR/STARsolo, Alevin-fry, BBrowser) with versions and parameters detailed in project reports
Code & pipeline deliverables	Executable R and Python scripts; optional Nextflow or Snakemake workflows and Docker or Conda containers	Seurat objects (`.rds`), 10x Loupe files (`.cloupe`), BBrowser files, count matrices, and interactive HTML reports; proprietary wet-lab protocols and internal automation scripts are retained by vendor
Reproducibility approach	Executable R/Python script handover, parameter logging, and optional containerized or workflow execution environments	Pre-compiled `.rds`, `.cloupe`, and BBrowser data objects, filterable count tables, and documented methodology in project HTML reports
Publication-quality figures	Editable high-resolution vector graphics (SVG, PDF) and raster formats (PNG, TIFF)	Exploratory HTML report graphics; publication-ready vector and raster graphics available via custom bioinformatics consulting
Methods-section support	Drafted publication-ready Methods text detailing tools, reference builds, parameters, and citations	Structured HTML project report descriptions of wet-lab protocols, software tools, reference assemblies, and parameters
Reviewer-response support	Direct technical support from assigned senior bioinformaticians for reviewer queries and re-analyses	Post-submission support, target re-clustering, and dataset re-analysis available through custom bioinformatics consulting engagements
Turnaround time	2–4 weeks for standard dry-lab cohorts; 4–6 weeks for complex multi-contrast or multi-omics studies	1–2 weeks for sequencing-only of client libraries; 4–9 weeks for full wet-lab to dry-lab single-cell projects
Direct analyst access	Direct ongoing contact with lead senior bioinformatician via email and video calls	Direct access to PhD-level scientists for initial scoping calls and custom bioinformatics consulting engagements
Pricing transparency	Quote-based fixed project pricing scoped upfront per study	Quote-based pricing calculated per sample volume, assay technique, and cell count; no public fixed price list
Data ownership	100% client ownership of raw/processed data, custom scripts, and intellectual property	Client ownership of dataset results upon payment; vendor retains proprietary rights to internal wet-lab protocols and pipeline code
Best suited for	Labs with raw FASTQ/BAM files seeking dry-lab analysis, executable script handover, direct analyst access, and 2–4 week delivery	Researchers needing end-to-end wet-lab processing, specialized single-cell assays (VASA-seq, SORT-seq, DRUG-seq), and pre-compiled interactive data objects (.rds, .cloupe)

What Single Cell Discoveries Does

Single Cell Discoveries runs an integrated wet-lab and dry-lab facility for single-cell genomics, spatial transcriptomics, and transcriptomic profiling. Researchers submit biological specimens (fresh or frozen tissue, dissociated cell suspensions, isolated nuclei, PBMCs, or FFPE tissue sections) or send raw sequencing files for standalone dry-lab analysis.

The laboratory processes samples on microfluidic platforms (10x Chromium), spatial analyzers (10x Xenium), microplate automation, and high-throughput sequencers (NovaSeq series). Assays include standard 10x single-cell RNA-seq (3', 5', Flex, and Immune Profiling), Parse Biosciences Evercode combinatorial barcoding, 10x Visium, Visium HD, Xenium In Situ, 10x scATAC-seq, ATAC Multiome, and low-input bulk RNA-seq. Specialized workflows include SORT-seq (plate-based FACS scRNA-seq), VASA-seq (total RNA single-cell sequencing that captures spliced, unspliced, and non-coding RNA), and DRUG-seq for high-throughput compound screening.

Bioinformatics deliverables are built around pre-compiled data structures and exploratory reports. Standard outputs include raw FASTQ files, count matrices (including spliced and unspliced tables for VASA-seq), Seurat objects (.rds), 10x Loupe Browser files (.cloupe), BBrowser project files, and interactive HTML reports with QC metrics, clustering, and differential expression tables. They do not offer primary WGS/WES variant calling, ChIP-seq, or mass-spectrometry proteomics.

What Pepkio Does

Pepkio provides standalone dry-lab bioinformatics analysis for research teams with raw sequencing datasets. Analysis modalities include bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics (10x Visium/Visium HD), WGS/WES variant calling, ChIP-seq, ATAC-seq, metagenomics, and proteomics.

Pipelines use standard open-source tools such as STAR, fastp, DESeq2, Seurat, and GATK. Deliverables include executable R and Python scripts, parameter logs, normalized expression matrices, differential expression tables, editable vector figures (SVG/PDF), and a draft Methods section. Workflows can optionally be delivered as Nextflow or Snakemake pipelines and packaged in Docker or Conda containers.

Researchers work directly with an assigned senior computational biologist through project scoping, parameter customization, report delivery, and post-submission peer-review revisions.

Head-to-Head Comparison

Analysis scope and supported data types

Single Cell Discoveries focuses on single-cell, spatial transcriptomics, and bulk transcriptomic assays across human, mouse, rat, zebrafish, plant, and microbial specimens. Specialized wet-lab technologies include VASA-seq for total RNA single-cell sequencing, SORT-seq for FACS-sorted cells, and DRUG-seq for high-throughput screening. They do not support WGS/WES variant calling, ChIP-seq, or mass-spectrometry proteomics.

Pepkio focuses on dry-lab computational workflows across a wider set of omics data, including bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, WGS/WES variant calling, ChIP-seq, ATAC-seq, metagenomics, and proteomics.

Pipeline transparency and parameter documentation

Single Cell Discoveries lists primary software tools (Cell Ranger, Seurat, Scanpy, STAR), reference genome builds, alignment metrics, and key analytical settings in delivered HTML project reports. Software versions and parameter logs are included in standard project deliverables.

Pepkio delivers raw R and Python code with explicit parameter values, filtering thresholds, and command-line arguments. Software versions and reference builds are documented in script headers and execution logs.

Reproducibility and code delivery

Single Cell Discoveries delivers pre-compiled data objects for interactive exploration in R or desktop viewers, including Seurat .rds objects, 10x Loupe .cloupe files, BBrowser project files, and filtered count matrices. Vendor-internal wet-lab protocols and core pipeline automation scripts stay with the provider and are not distributed as customer-facing code repositories.

Pepkio delivers executable R and Python scripts alongside processed data tables and parameter logs. Workflows can optionally be delivered as Nextflow or Snakemake pipelines and containerized with Docker or Conda, so researchers can rerun or modify the computational pipeline on local infrastructure.

Publication support: figures, Methods text, and reviewer responses

Single Cell Discoveries includes structured methodology summaries in HTML project reports, which researchers can adapt for manuscript Methods sections. Reports contain standard exploratory plots; publication-ready custom vector figures (such as high-resolution UMAPs, volcano plots, or heatmaps) and post-submission reviewer support are available through dedicated bioinformatics consulting engagements.

Pepkio provides publication-ready editable vector graphics (SVG, PDF) and high-resolution raster files (PNG, TIFF) plus a drafted Methods section. The assigned senior bioinformatician can help during peer review with requested re-analyses, figure changes, or draft responses to reviewer comments.

Turnaround time and project timelines

Single Cell Discoveries typically needs about 1 to 2 weeks for sequencing-only projects that use pre-made libraries. Full-service projects that include biological sample processing, library preparation, sequencing, and preliminary bioinformatics reporting typically take 4 to 9 weeks from sample receipt.

Pepkio typically completes dry-lab analyses for standard cohorts within 2 to 4 weeks after receiving raw data files. Complex multi-contrast or integrated multi-omics studies typically take 4 to 6 weeks.

Communication model and analyst access

Single Cell Discoveries provides consultation with PhD-level single-cell specialists for initial project design, protocol selection, and custom analytical scoping. Ongoing technical queries and custom post-delivery analyses are handled through specialized consulting interactions.

Pepkio pairs researchers directly with the senior computational biologist doing the data processing. Communication is by email and video calls across scoping, analysis, report review, and peer-review revisions.

Pricing model and service scoping

Single Cell Discoveries uses custom project quotes based on sample count, target cell recovery, assay type, and sequencing depth. Standard quotes include sample processing, sequencing, demultiplexing, exploratory HTML report generation, and .rds / .cloupe object delivery; advanced custom analyses are scoped as separate bioinformatics consulting.

Pepkio uses study-based fixed project quotes set after initial scoping. Quotes cover data processing, executable R/Python script handover, vector figure generation, Methods text drafting, and reviewer-response support.

Data ownership and IP rights

Single Cell Discoveries transfers ownership of generated sequencing data, count matrices, and analytical results to the client upon invoice payment, and retains proprietary rights over internal laboratory protocols and workflow scripts.

Pepkio grants clients 100% ownership of raw data, processed outputs, custom R/Python scripts, and associated intellectual property upon delivery.

When Pepkio Is the Better Fit

You already have raw FASTQ, BAM, or count matrix files and need dry-lab computational analysis.
Your project requires executable R or Python scripts for local execution, modification, or audit.
You prefer optional containerized environments (Docker/Conda) or workflow manager scripts (Nextflow/Snakemake).
You require dry-lab turnaround within 2 to 4 weeks.
Your study involves omics modalities beyond single-cell/spatial transcriptomics, such as WGS/WES variant calling, ChIP-seq, ATAC-seq, metagenomics, or proteomics.
You want direct ongoing communication with the senior bioinformatician executing your analysis through manuscript revision.

When Single Cell Discoveries Is the Better Fit

You require end-to-end wet-lab processing starting from physical tissue, frozen specimens, cell suspensions, nuclei, or FFPE sections.
Your project uses specialized single-cell assays such as VASA-seq (total RNA single-cell sequencing), SORT-seq (plate-based FACS scRNA-seq), or DRUG-seq (high-throughput compound screening).
You want pre-compiled interactive data files, including Seurat .rds objects, 10x Loupe .cloupe files, and BBrowser project files for GUI-based exploration.
You need guidance on wet-lab experimental design, tissue dissociation protocols, and cell isolation before sample collection.
Your study timeline can accommodate 4 to 9 weeks for physical wet-lab processing, sequencing, and report generation.

Frequently Asked Questions

Do I receive the R or Python code used for my analysis?

Pepkio delivers raw executable R and Python scripts along with parameter logs, with options for Docker/Conda environments or Nextflow/Snakemake workflows. Single Cell Discoveries provides pre-compiled data files (Seurat .rds, 10x Loupe .cloupe, BBrowser project files) and HTML reports, and keeps core internal pipeline code within its infrastructure.

What sample materials are required to start a project?

Single Cell Discoveries receives physical biological specimens, including fresh or frozen tissue, cell suspensions, nuclei, PBMCs, or FFPE sections, for wet-lab processing. Pepkio receives raw digital sequencing files, such as FASTQ, BAM, VCF, or count matrices, for dry-lab processing.

Can I submit raw FASTQ files if sequencing is already completed?

Yes. Both providers accept raw FASTQ files or feature-barcode matrices for standalone computational analysis. Single Cell Discoveries processes existing datasets through dry-lab consulting. Pepkio handles them under standard dry-lab project scopes.

What file formats are delivered for local data exploration?

Single Cell Discoveries delivers Seurat objects (.rds), 10x Loupe files (.cloupe), BBrowser project files, cell-by-gene matrices, and interactive HTML reports. Pepkio delivers executable R and Python scripts, normalized expression matrices, Seurat objects, and editable vector graphics (SVG, PDF).

What is the expected turnaround time from project kickoff to data delivery?

Single Cell Discoveries full-service projects typically take 4 to 9 weeks from sample arrival, covering tissue handling, library preparation, sequencing, and report generation (sequencing-only projects typically take 1 to 2 weeks). Pepkio dry-lab analyses typically take 2 to 4 weeks from dataset receipt for standard cohorts, and 4 to 6 weeks for complex multi-contrast studies.

Will either service draft the Methods section for a manuscript?

Pepkio provides a drafted, publication-ready Methods section detailing alignment tools, software settings, reference builds, and statistical criteria. Single Cell Discoveries includes structured experimental protocols, software names, assemblies, and parameters within HTML reports, which researchers adapt into manuscript text.

How are reviewer comments and re-analyses handled post-submission?

Pepkio includes direct support from the assigned senior bioinformatician to perform requested re-analyses, update figure formatting, and answer reviewer questions. Single Cell Discoveries provides post-submission support, target re-clustering, and dataset re-analysis through custom bioinformatics consulting engagements.

Can I communicate directly with the bioinformatician handling my dataset?

Yes. Pepkio assigns a senior computational biologist who communicates directly with researchers via email and video calls from project kickoff through manuscript revision. Single Cell Discoveries offers consultation with PhD-level single-cell specialists during scoping calls and custom consulting projects.

Are project prices published online?

Neither provider posts fixed price lists online. Both offer custom quotes following project scoping: Single Cell Discoveries quotes based on sample volume, cell count, and assay type, while Pepkio provides study-based fixed project pricing.

Who owns the resulting data, code, and intellectual property?

Researchers retain ownership of data, results, and intellectual property upon invoice payment with both providers. Pepkio also transfers 100% ownership of custom R and Python scripts written for the project. Single Cell Discoveries retains ownership of proprietary wet-lab protocols and internal pipeline code.

How are non-standard analytical requests handled?

Single Cell Discoveries addresses custom analytical needs, such as trajectory inference, batch correction, or specialized GSEA, through dedicated custom consulting, and provides specialized wet-lab assays like VASA-seq. Pepkio incorporates custom script adjustments, trajectory modeling, and advanced statistical integration directly into the dry-lab scope.

Do both services support omics modalities outside single-cell and spatial transcriptomics?

Pepkio provides dry-lab analysis across bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, WGS/WES variant calling, ChIP-seq, ATAC-seq, metagenomics, and proteomics. Single Cell Discoveries specializes in single-cell, spatial, and transcriptomic assays, and does not offer primary WGS/WES, ChIP-seq, or mass-spectrometry proteomics services.

Bottom Line

The choice between Single Cell Discoveries and Pepkio depends on whether your study needs integrated wet-lab tissue processing or standalone dry-lab computational analysis. Single Cell Discoveries fits teams that need physical sample prep, cell isolation, sequencing, and specialized assays like VASA-seq or SORT-seq, plus interactive .rds and .cloupe files. Pepkio fits labs that already have raw FASTQ files and want 2 to 4 week dry-lab execution, executable R/Python script ownership, optional containerized environments, direct analyst communication, and analysis across a wider set of omics modalities.