Basepair vs Pepkio: Bioinformatics Service Comparison | Pepkio Compare

Quick Comparison Table

Feature	Pepkio (Outsourced CRO)	Basepair (DIY SaaS)
Primary model	Full-service bioinformatics CRO	Self-service cloud SaaS platform
Supported analyses	Custom bulk RNA-seq, single-cell RNA-seq, DNA-seq, epigenomics, non-model organisms, de novo assembly, bespoke multi-omics	Pre-configured workflows for bulk RNA-seq, single-cell RNA-seq, WGS/WES variant calling, ChIP-seq, ATAC-seq, miRNA-seq, Methyl-seq
Bioinformatics skills required	None (handled end-to-end by CRO bioinformaticians)	Low for GUI workflows; moderate for custom Nextflow or WDL pipelines
Infrastructure requirements	None	Web browser for GUI; AWS account for Connected Cloud (BYOC)
Turnaround time	1–3 weeks for interpreted reports, figures, and Methods	Compute finishes in hours; setup takes minutes to hours
Statistical customization	Bespoke linear models, custom filtering, and complex contrast matrices	Standard GUI parameter toggles; custom logic requires Nextflow or WDL development
Reproducibility deliverables	Custom R and Python code archives, Methods text, optional Nextflow or Snakemake workflows and Conda or Docker environments	Automated cloud lineage graphs, execution logs, and exportable Nextflow or WDL files
Code deliverables	Documented custom R/Python analysis scripts	Raw execution logs and exportable workflow files
Publication figure support	Custom multi-panel figures formatted to target journal specifications	Interactive web plots with SVG, PDF, and PNG export
Reviewer-response support	Direct scientist-to-scientist re-analysis, custom text, and figure updates	Self-service re-analysis and offline scripting by the researcher
Pricing structure	Fixed project-based fee	Subscription or pay-as-you-go per sample (+ AWS compute/storage under BYOC)
Lab personnel effort	Minimal hands-on analysis time	1–3 hours per standard run; additional hours for cloud setup or custom pipelines

What Is Basepair?

Basepair is a cloud software platform for NGS data processing. It offers point-and-click, command-line, and API interfaces, and is available through pay-as-you-go or annual subscription pricing.

The platform supports standard NGS workflows, including bulk RNA-seq with STAR and DESeq2, single-cell RNA-seq with Cell Ranger and Seurat, DNA-seq variant calling with NVIDIA Parabricks, and epigenomics pipelines such as MACS2 peak calling. Users can run analyses in the web GUI or through the Python SDK (pip install basepair) and REST API. Compute can run on managed infrastructure or in a customer's AWS account through Connected Cloud.

What Is Pepkio?

Pepkio is an outsourced bioinformatics CRO service that takes sequencing projects from raw files to publication assets. Instead of having researchers configure and run software themselves, Pepkio assigns bioinformaticians to execute the work.

Deliverables include custom statistical tables, multi-panel figures, Materials & Methods draft text, and documented R or Python scripts. Nextflow or Snakemake workflows plus Conda or Docker environments are available as optional deliverables. Projects use fixed-fee pricing and include scientist-to-scientist support during peer review.

Pepkio vs Basepair Key Differences

Setup and Infrastructure

Basepair requires only a web browser for the GUI, and teams can usually register and launch a standard workflow in 10 to 15 minutes. Connected Cloud setup in an institution-owned AWS environment usually takes 1 to 3 hours of IT work for IAM roles and CloudFormation. Pepkio does not require installation or cloud setup from the client side because the CRO team manages compute and storage.

Customization and Analytical Depth

Basepair handles standard model-organism datasets through built-in pipelines and GUI parameter settings. Non-standard statistical designs, unannotated genomes, or custom filtering generally require custom Nextflow or WDL work. Pepkio provides project-specific customization, including custom reference indexing, complex batch-effect modeling, and custom contrast matrices.

Turnaround Time and Workload

Basepair pipeline execution usually finishes in hours, but researchers still need to review QC metrics, inspect results, validate assumptions, and format figures for manuscripts. Pepkio delivers a full package in 1 to 3 weeks, including validated outputs, formatted figure panels, and written summaries.

Reproducibility and Deliverables

Basepair tracks parameters, sample metadata, and container lineage, and lets users export logs plus Nextflow or WDL workflow definitions. Pepkio provides documented R and Python scripts, raw and processed data matrices, and Materials & Methods draft text for submission workflows. Nextflow or Snakemake workflows and Conda or Docker environments are optional based on project needs.

Cost Structure

Basepair uses per-sample pay-as-you-go pricing or subscription licenses. Under Connected Cloud, AWS compute, S3 storage, and egress are billed separately by AWS. Pepkio uses a fixed project fee that includes compute, storage, analysis labor, and re-analysis support.

Scientific Support and Peer Review

Basepair provides email support, ticketing, and documentation. If data shows unexpected batch effects or quality issues, researchers usually troubleshoot and re-analyze on their own. Pepkio assigns bioinformaticians who troubleshoot anomalies, adjust models, update figures, and help draft peer-review responses.

When Should You Choose Pepkio?

Pepkio is a practical choice for projects that need custom statistical modeling, non-model organism work, or manuscript-ready deliverables.

Complex experimental designs: Your study involves nested batch effects, custom contrast matrices, or multi-omics integration.
Non-model organisms: Your dataset relies on species without reference genome annotations, requiring custom indexing or de novo assembly.
Turnkey manuscript assets: You require publication-ready multi-panel figures, written Materials & Methods text, and documented R or Python code.
Peer-review assistance: You want bioinformaticians to perform re-analyses and help draft responses to reviewer comments.
No internal bioinformatics capacity: Your lab prefers a fixed service fee over managing pipeline software and cloud infrastructure.

When Should You Choose Basepair?

Basepair is a practical choice for teams with standard model-organism datasets that prefer to run pipelines themselves through a web UI or API.

Standard NGS workflows: Your project uses established pipelines for bulk RNA-seq, single-cell RNA-seq, ChIP-seq, ATAC-seq, or variant calling.
Existing AWS infrastructure: Your institution requires data to remain inside a private AWS perimeter using the Connected Cloud model.
Self-service facility portals: You want to provide bench scientists or clients with a point-and-click portal to run standard pipelines.
GPU-accelerated variant calling: You require fast secondary analysis for WGS or WES using NVIDIA Parabricks.
Programmatic execution: You want to integrate pipeline runs into custom software using a Python SDK or REST API.

Trade-Offs at a Glance

The main trade-off is self-service software costs and internal labor versus outsourced analysis and publication support.

Basepair:
- Strengths: Fast cloud compute execution; intuitive web GUI for non-coders; Python SDK and REST API access; secure AWS Connected Cloud integration.
- Considerations: Researchers must perform statistical validation, quality assurance, and figure design; custom pipelines require Nextflow or WDL development; separate AWS compute charges apply under Connected Cloud.
Pepkio:
- Strengths: Zero hands-on labor for lab personnel; bioinformaticians handle complex experimental designs; turnkey figures, Methods text, and reviewer support; full custom R and Python code provided.
- Considerations: Turnaround takes 1 to 3 weeks rather than automated execution in hours; higher per-project cost compared to self-service software licenses.

Frequently Asked Questions

What is the main difference between Pepkio and Basepair?

Basepair is self-service cloud software for running standard NGS pipelines. Pepkio is an outsourced bioinformatics CRO where bioinformaticians run the analysis, handle custom statistics, generate publication figures, and draft manuscript text.

Do I need programming skills to use Basepair?

No, Basepair provides a web-based GUI that lets bench scientists run standard pipelines for RNA-seq or variant calling using point-and-click controls. However, building custom pipelines or non-standard statistical filters requires command-line scripting with Nextflow or WDL.

Do I get the underlying analysis scripts from Pepkio and Basepair?

Yes, both platforms provide access to workflow logic. Basepair allows users to inspect execution parameters and export Nextflow or WDL workflow definitions. Pepkio provides documented R and Python analysis scripts used for your project, with Nextflow or Snakemake workflows available as optional deliverables.

How long does an analysis take on Basepair compared to Pepkio?

Basepair pipelines can finish in hours, but teams may still spend days or weeks on QC review, parameter adjustments, and figure preparation. Pepkio typically delivers a full package in 1 to 3 weeks, including statistical validation, figures, and written text.

How do Pepkio and Basepair handle non-model organisms?

Basepair's GUI includes pre-configured reference genomes for common model organisms, so analyzing non-model species requires uploading custom FASTA and GTF files or writing CLI pipeline definitions. Pepkio's bioinformaticians routinely handle non-model species by building custom reference indexes or performing de novo assembly as part of the service.

What happens if peer reviewers request a new statistical contrast?

On Basepair, your team must log into the platform, update workflow parameters, re-run the pipeline, or perform offline scripting in R or Python. With Pepkio, bioinformaticians handle reviewer requests directly by executing new contrasts, updating figure panels, and writing response text.

How does the cost compare between self-service software and an outsourced CRO?

Basepair charges a software license fee per sample or annual subscription, plus variable AWS compute and storage costs when using Connected Cloud. Pepkio charges a transparent, fixed project fee that covers compute, storage, bioinformatician labor, figure creation, and reviewer support without extra licensing costs.

Can Basepair run inside an existing AWS cloud environment?

Yes, Basepair offers a Connected Cloud model that uses AWS CloudFormation templates and IAM roles to run compute and store data inside an organization's AWS S3 buckets. This configuration allows institutions to use existing cloud credits while meeting internal data compliance policies.

Does Basepair or Pepkio write the Materials & Methods section for publication?

Basepair provides software execution logs and parameter summaries, but does not write manuscript text. Pepkio provides a publication-ready Materials & Methods section tailored to target journal reporting standards alongside the final results.

Bottom Line

The decision mostly comes down to whether your team wants self-service cloud execution or complete analytical delivery from a CRO.

If your lab works on standard model-organism datasets and has time for QC review, statistical design, and figure assembly, Basepair can work well as a DIY platform. If your project involves non-model species, complex designs, or you want to outsource analysis, code delivery, and manuscript drafting, Pepkio offers a full CRO service.