BioTeam vs Pepkio: Bioinformatics Service Comparison

Quick Comparison Table

What BioTeam Does

BioTeam is a scientific IT, high-performance computing (HPC), cloud architecture, and computational biology consultancy, not a per-sample sequencing CRO or wet lab. Researchers provide raw FASTQ files, BAM/CRAM alignments, VCF files, or expression matrices stored on local HPC clusters or cloud object storage such as AWS S3 or GCP Cloud Storage.

BioTeam engineers custom Nextflow, Snakemake, WDL, and Cromwell pipelines for bulk RNA-seq, Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES), variant calling, and ChIP-seq, plus automated workflows for multi-omics datasets. Workflows are containerized with Docker and Singularity (Apptainer), managed with Conda, and deployed with infrastructure-as-code tools such as Terraform or cloud services such as AWS HealthOmics.

Deliverables include workflow repositories, container recipes, cloud deployment scripts, FAIR data management documentation, and technical training for internal engineering teams. Code and data stay in the client's own cloud tenant or HPC infrastructure, so clients keep ownership. BioTeam works with biotech companies, pharmaceutical firms, academic medical centers, and federal research institutes.

What Pepkio Does

Pepkio provides dry-lab bioinformatics analysis for research teams with raw sequencing or multi-omics datasets. Analytical modalities cover 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 documented open-source tools such as STAR, fastp, DESeq2, Seurat, and GATK. Standard deliverables include raw executable R and Python scripts, parameter logs, normalized count tables, differential expression lists, editable vector figures (SVG/PDF), and a publication-ready Methods section. Nextflow or Snakemake workflows, as well as Conda or Docker environments, are optional deliverables.

Researchers communicate directly with the senior computational biologist assigned to their project, from initial scoping through parameter adjustments and post-delivery help with peer-reviewer queries.

BioTeam vs Pepkio: Head-to-Head Comparison

Analysis scope and supported data types

Both options process data from human, animal, plant, microbial, and environmental samples across various experimental designs. BioTeam engineers custom automated pipelines and HPC/cloud data hubs for client-specified datasets, with a focus on bulk RNA-seq, WGS, WES, variant calling, and ChIP-seq workflow architecture. Off-the-shelf per-sample service menus for scRNA-seq, spatial transcriptomics, or proteomics are not publicly listed on their website. Pepkio provides dry-lab analysis across bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics (10x Visium/Visium HD), WGS/WES variant calling, ChIP-seq, ATAC-seq, metagenomics, and proteomics.

Pipeline transparency

Both options use open-source pipeline transparency rather than black-box processing. BioTeam designs workflows with Nextflow, Snakemake, WDL, and Cromwell, and defines environments in Docker containers, Singularity definitions, and Conda files. Tool configurations and parameters are tailored to cluster specifications in client Statements of Work. Pepkio delivers the underlying R and Python scripts used during data processing, with tool parameters, filtering cutoffs, and reference genome builds documented in project deliverables.

Reproducibility & code delivery

Both options deliver code, with different execution targets. BioTeam hands over Nextflow, WDL, or Snakemake workflow repositories, Docker/Singularity container recipes, and Terraform infrastructure scripts so internal engineering teams can run automated pipelines repeatedly on cloud tenants (AWS HealthOmics, GCP) or HPC hardware. Pepkio hands over raw, executable R and Python scripts, parameter logs, and optional workflow manager files (Nextflow/Snakemake) or container definitions (Docker/Conda), so research labs can re-run or edit statistical analyses locally.

Publication support

Pepkio includes manuscript-focused deliverables with every project: editable vector graphics (SVG, PDF), high-resolution raster figures (PNG, TIFF), a drafted publication-ready Methods section, and direct analyst help for re-analyses requested by journal reviewers. BioTeam focuses on computational infrastructure, workflow engineering, and data architecture. Drafting manuscript Methods sections, generating standalone publication figures, or setting fixed post-delivery revision rounds for peer review are not publicly listed as standard deliverables on BioTeam's website, though technical follow-up can be included under ongoing consulting SOWs.

Turnaround & deadline flexibility

Pepkio typically completes standard cohort analyses in 2 to 4 weeks, with complex multi-contrast projects often taking 4 to 6 weeks. BioTeam turnaround is project-dependent and set in negotiated Statements of Work (SOW), from about 1 to 2 weeks for initial computational assessments up to multi-month infrastructure implementations.

Communication model

Both teams connect researchers directly with computational specialists rather than routing messages through sales representatives. BioTeam client teams work with senior scientific IT consultants, cloud architects, and bioinformaticians via email, video meetings, shared Slack or Teams channels, GitHub repository tracking, and on-site whiteboarding sessions. Pepkio pairs researchers with the lead computational biologist running their analysis via direct email and video calls throughout the project.

Pricing & project scoping

Neither provider lists static prices on public web pages. BioTeam works on custom consulting contracts and Statements of Work (SOW), with project-based milestone pricing, time-and-materials billing, or retainer/FTE arrangements, plus a US Federal GSA MAS contract for government procurement. Pepkio provides fixed-scope study quotes scoped upfront per project, covering raw data processing, executable R/Python script handover, vector figures, Methods text drafting, and reviewer support.

Data security & ownership

BioTeam builds pipelines that run inside the client's own cloud tenant (AWS, GCP) or local HPC storage cluster. BioTeam does not store or host client biological data on vendor servers, so data retention and governance follow internal client IT policies. Pepkio receives raw data files (FASTQ, BAM, count tables) to run analyses, and transfers 100% ownership of processed outputs, custom scripts, and intellectual property back to the client upon project completion.

Handling custom or non-standard analyses

BioTeam is built around custom workflow design, containerization, and enterprise data architecture, including bespoke Nextflow or WDL pipelines for novel assay combinations or multi-omics integration. Pepkio handles custom statistical designs, tailored contrasts, and specialized visualisations within supported omics modalities like single-cell RNA-seq or spatial transcriptomics.

When Pepkio Is the Better Fit

• You need a dry-lab partner to analyze a dataset and return raw, executable R or Python scripts for local modification.
• Your project requires publication-ready vector figures (SVG/PDF), a drafted Methods section, and direct analyst help during peer review.
• You prefer fixed-price project quotes with a typical 2-to-4-week turnaround.
• Your study falls under standard or complex omics modalities like bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, variant calling, or proteomics.
• You want ongoing direct communication with the bioinformatician performing your data analysis.

When BioTeam Is the Better Fit

• Your organization needs to build, containerize, and deploy automated Nextflow, WDL, or Snakemake pipelines inside your own cloud tenant (AWS HealthOmics, GCP) or HPC cluster.
• You need high-performance computing (HPC) architecture consulting, cloud infrastructure design, or FAIR data ecosystem implementation.
• You require enterprise contracting models, time-and-materials consulting, FTE retainers, or procurement through a US Federal GSA MAS contract.
• Your computational team needs container recipes (Docker/Singularity) and infrastructure-as-code (Terraform) to maintain internal pipeline autonomy.
• You are implementing large-scale automated data workflows for institutional or enterprise multi-omics projects.

Frequently Asked Questions

Do I get the actual R or Python scripts used for my analysis?

Pepkio delivers raw, executable R and Python scripts along with parameter logs. Nextflow or Snakemake workflows, as well as Docker or Conda environments, are optional deliverables. BioTeam hands over Nextflow, WDL, or Snakemake workflow repositories, Docker/Singularity container recipes, and infrastructure code so internal engineering teams can run pipelines independently.

Can BioTeam build Nextflow or WDL pipelines for an internal HPC cluster?

Yes. BioTeam builds containerized Nextflow, WDL, Snakemake, and Cromwell pipelines tailored to run on local HPC clusters or cloud environments like AWS HealthOmics and GCP.

Will either team write the Methods section for my manuscript?

Pepkio includes a draft publication-ready Methods section detailing tools, reference genome builds, parameters, and citations with every project. Methods section drafting is not publicly listed as a standard deliverable on BioTeam's public web pages.

How do both teams handle reviewer comments during peer review?

Pepkio provides direct post-delivery support where the assigned lead bioinformatician helps answer reviewer queries, update figures, or run additional statistical contrasts. BioTeam handles technical follow-up or pipeline modifications through ongoing consulting Statements of Work (SOW).

Do I need my own cloud infrastructure to work with BioTeam?

BioTeam builds pipelines that run within the client's own cloud tenant (AWS, GCP) or local HPC environment. They do not store or host client biological data on vendor-managed servers, so data remains under internal IT policies.

What file formats are delivered for publication figures?

Pepkio supplies publication-ready visualisations as editable vector graphics (SVG, PDF) and high-resolution raster files (PNG, TIFF). BioTeam deliverables center on computational workflows, container recipes, and data hubs; publication figures are not publicly listed as a primary deliverable.

How do turnaround times compare for standard RNA-seq projects?

Pepkio typically completes standard bulk RNA-seq cohort analyses in 2 to 4 weeks from receiving raw data. BioTeam works on custom Statements of Work (SOW), where timelines are negotiated based on pipeline engineering scope, from brief 1-to-2-week strategic assessments to multi-month implementations.

Are prices published online for either service?

Neither provider posts static price tables online. Both require initial project consultations to generate custom quotes, with Pepkio offering fixed project-based quotes per study and BioTeam providing milestone-based, time-and-materials, or retainer contracts.

Who owns the data and pipeline code created during the project?

Under both options, clients retain 100% ownership of their biological data, results, and intellectual property. BioTeam builds custom workflows directly in client code repositories, with full ownership of workflow code and container recipes transferred to the client, while Pepkio transfers complete ownership of custom R and Python scripts written for the analysis.

Do I talk directly to the bioinformatician analyzing my data?

Yes. Pepkio pairs researchers directly with the senior computational biologist executing their analysis via direct email and video calls. BioTeam clients work directly with senior scientific IT consultants, cloud architects, and computational biologists through video meetings, direct email, shared Slack channels, and GitHub repository tracking.

Can BioTeam help convert legacy bioinformatics scripts into containerized workflows?

Yes. BioTeam bioinformatics consulting includes converting legacy bioinformatics scripts into reproducible, containerized Docker and Singularity (Apptainer) workflows managed with Conda and Nextflow or WDL.

What options exist if a lab requires custom statistical contrasts or specialized filtering?

Pepkio handles tailored statistical contrasts, custom cutoffs, and specialized visualisations within supported omics modalities as part of project scoping. BioTeam engineers custom pipeline logic to accommodate non-standard analytical requirements specified in a project Statement of Work.

Bottom Line

The choice between BioTeam and Pepkio depends on whether you need computational infrastructure engineering or outsourced dry-lab data analysis. Pepkio fits research groups that want fixed-scope data processing, raw R and Python script delivery, publication-ready vector figures, draft Methods text, and direct bioinformatician support during peer review. BioTeam fits biotech, pharma, and academic institutions that want to build, containerize, and deploy automated Nextflow or WDL pipelines inside their own cloud tenants or HPC clusters.