Services

From foundational analysis to strategic guidance, BioLentra supports the full lifecycle of genomic data analysis.

Transcriptomics

  • Bulk RNA-Seq

  • Single cell RNA-Seq

  • Spatial

Epigenomics

  • CUT&RUN

  • ChIP-Seq

  • Motif analysis

Pathway Analysis

  • GSVA / GSEA

  • Pathway enrichment (GO/EnrichR)

  • Functional interpretation

  • Cell type deconvolution

Metagenomics

  • Non-host read detection

  • Taxonomic classification

  • Pangenome analysis

Clinical & Real World Data

  • Large-scale clinical & genomic data integration

  • Clinical variable harmonization

  • Treatment response (longitudinal)

  • Biomarker discovery

ML & Statistics

  • Differential expression & differential protein binding

  • Time-to-event & survival analysis (Kaplan Meier)

  • Predictive modeling

  • Clustering and subtype detection

Interdisciplinary Collaborations

  • Cross-functional work between scientists, software engineers, clinicians, and industry partners

  • Technical and non-technical audiences

  • Project management across parallel research efforts

  • Mentorship and scientific leadership

Multi-omic Integration

  • RNASeq + clinical data integration

  • Cross-cohort harmonization

  • Metadata structuring

  • RNASeq + CUT&RUN integration

Genomic Alterations

  • Gene fusions

  • Copy number alterations

  • Mutation calling

Service Tiers

We offer three levels of engagement based on your needs

Foundational Analysis

Input → Output → Visualization

BEST FOR:

  • Well-defined datasets

  • Standard workflows

  • Processed data tables and figures

Tier One

Insight Generation

Biological Interpretation

BEST FOR:

  • Complex datasets

  • Hypothesis generation

  • Interpretation beyond outputs

Tier Two

Strategic Guidance

Driving Decisions from Data

BEST FOR:

  • Study design and planning

  • Modeling direction

  • Multi-project support

Tier Three

Ways to work together

Targeted Analysis

Focused support for clearly defined questions or datasets

Ideal for

  • Differential gene expression

  • Pathway enrichment (GSEA, Enrichr)

  • Survival analysis (Kaplan–Meier, Cox models)

  • Publication-ready figures

  • Pipeline troubleshooting

What you get

  • Clean, reproducible analysis

  • Clear interpretation of results

  • Publication-quality visualizations

Investment

Per project budget or hourly engagement rate (starting at $65/hr)

Translational Partnership

High-level collaboration for complex, publication or application-driven research

Ideal for

  • Biomarker discovery

  • Immunotherapy response analysis

  • Multi-cohort / multi-omics integration

  • Study design and analytical strategy

  • Manuscript-focused work

What you get

  • Deep biological interpretation

  • Strategic guidance on analysis direction

  • Prioritization of meaningful signals

  • Presentation- and publication-ready outputs

Investment

Hourly rate or custom project proposals ($5k-15k+)

Ongoing Scientific Support

Embedded bioinformatics expertise for active research programs

Ideal for

  • Multi-step genomics projects

  • Clinical metadata integration

  • Iterative hypothesis testing

  • Collaboration with trainees and lab teams

  • Workflow development

What you get

  • Ongoing collaboration and check-ins

  • Iterative analysis and refinement

  • Scalable, reproducible pipelines

  • A reliable computational partner for your lab

Investment

Hourly rate or monthly retainers from $3,500+

How I Work

  1. Initial Consultation
    We discuss your data, goals, and research questions

  2. Project Scoping
    Clear deliverables, timelines, and pricing

  3. Analysis & Iteration
    Transparent communication and collaborative refinement

  4. Delivery
    Interpretable results, figures, and insights ready for presentation or publication

Who I Work With

  • Academic research labs

  • Translational and clinical research teams

  • Early-stage biotech companies

  • Investigators working with genomics and multi-omics data

Why BioLentra?

  • Deep expertise across wet lab + computational biology

  • Strong focus on biological interpretation - not just analysis

  • Experience with large-scale, multi-cohort datasets

  • Proven ability to generate publication-ready insights

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