Fueling discovery with data.


1. Service Model

Tier 1: Basic Support ($500/month)

At this tier, the focus is on ease of use and automation, with limited customization options.

Cloud Compute Capabilities:

  • Pre-Built Pipelines: Access to automated pipelines for common analyses (e.g., RNA-seq, variant calling).
  • Basic Visualization Tools: Use drag-and-drop interfaces to create basic visualizations (e.g., heatmaps, bar charts).
  • Limited Customization: Adjust basic parameters (e.g., thresholds, filters) through a user-friendly interface.

What a Tech Can Do:

  • Upload data and run pre-built pipelines with minimal input.
  • Customize basic parameters (e.g., adjust fold-change thresholds for differential expression analysis).
  • Generate and export publication-ready figures.

Example:

A Tech uploads RNA-seq data, selects a pre-built pipeline, adjusts the p-value threshold, and generates a heatmap of differentially expressed genes.

Tier 2: Advanced Support ($1,500/month)

At this tier, Tech users gain access to more advanced tools and customization options, allowing them to tailor analyses to their specific needs.

Cloud Compute Capabilities:

  • Custom Workflows: Create and modify workflows for specific projects (e.g., multi-omics integration).
  • Advanced Visualization Tools: Use interactive dashboards to explore data (e.g., network graphs, pathway maps).
  • API Access: Access APIs to integrate our tools into their workflows or scripts.
  • Batch Processing: Run large-scale analyses with batch processing capabilities.

What a Tech Can Do:

  • Design custom workflows by combining pre-built modules (e.g., RNA-seq + metabolomics integration).
  • Use APIs to automate data uploads and analysis from their local systems.
  • Create advanced visualizations (e.g., pathway maps, network graphs) and customize them for publications.
  • Run batch jobs to process multiple datasets simultaneously.

Example:

A Tech uses the API to upload RNA-seq and metabolomics data, runs a custom multi-omics integration workflow, and creates an interactive pathway map to explore the results.

Tier 3: Premium Support ($3,000/month)

At this tier, Tech users have access to full customization, dedicated support, and cutting-edge tools, enabling them to tackle complex projects with ease.

Cloud Compute Capabilities:

  • Custom Algorithm Development: Work with our team to develop custom algorithms for unique projects.
  • High-Performance Computing (HPC): Access to scalable, high-performance resources for large-scale analyses.
  • Real-Time Collaboration: Share data and results with collaborators in real time.
  • Priority Access: Early access to new tools and features.

What a Tech Can Do:

  • Collaborate with our team to develop custom algorithms (e.g., a novel cross-omics integration tool).
  • Use HPC resources to analyze large datasets (e.g., whole-genome sequencing for hundreds of samples).
  • Share results with collaborators in real time using interactive dashboards.
  • Experiment with new tools and features before they’re released to other tiers.

Example:

A Tech works with our team to develop a custom algorithm for integrating single-cell RNA-seq and proteomics data. They use HPC resources to analyze a large dataset and share the results with collaborators through an interactive dashboard.

Summary of Cloud Compute Capabilities by Tier

CapabilityBasicAdvancedPremium
Pre-Built Pipelines✅✅✅
Basic Visualization Tools✅✅✅
Custom Workflows❌✅✅
Advanced Visualization Tools❌✅✅
API Access❌✅✅
Batch Processing❌✅✅
Custom Algorithm Development❌❌✅
High-Performance Computing❌❌✅
Real-Time Collaboration❌❌✅
Priority Access to New Tools❌❌✅

Key Takeaways

  • Tier 1: Focuses on ease of use and automation, with limited customization. Ideal for labs with basic needs.
  • Tier 2: Adds advanced tools, customization options, and API access. Perfect for labs with more complex projects.
  • Tier 3: Offers full customization, HPC resources, and dedicated support. Best for labs tackling cutting-edge research.

By offering tiered access to cloud compute capabilities, we can cater to a wide range of clients, from those with minimal technical expertise to those with advanced needs. This approach ensures that every lab gets the tools and support they need to succeed, while also maximizing our profitability and scalability.

2. Pricing Model

Tier 1: Basic Support ($500/month)

  • Includes:
    • Access to automated pipelines for common analyses (e.g., RNA-seq, variant calling).
    • Basic data visualization tools (e.g., heatmaps, bar charts).
    • Email support with a 48-hour response time.
    • 1 hour of consultation per month.

Tier 2: Advanced Support ($1,500/month)

  • Includes:
    • Everything in Tier 1.
    • Custom analysis workflows (e.g., multi-omics integration).
    • Advanced data visualization tools (e.g., network graphs, pathway maps).
    • Phone and chat support with a 24-hour response time.
    • 3 hours of consultation per month.
    • Training sessions for lab members.

Tier 3: Premium Support ($3,000/month)

  • Includes:
    • Everything in Tiers 1 and 2.
    • Dedicated account manager for personalized support.
    • Priority access to new tools and features.
    • Unlimited consultation hours.
    • On-site or virtual training for the entire lab.
    • Custom algorithm development (e.g., cross-omics integration).

4. Custom Projects

For one-off projects or specialized needs, charge based on complexity:

  • Standard Custom Workflow: $500 − $2,000/project.
  • Custom Algorithm Development: $3,000 − $5,000/project.

5. Free or Discounted Pilots

To attract new clients, offer:

  • Free Pilot: Analyze a small dataset for free in exchange for feedback and a testimonial.
  • Discounted Pilot: Offer a 50% discount on the first project.

6. Referral Incentives

Encourage referrals by offering:

  • Discounts: 10% off future services for successful referrals.
  • Free Hours: 1 free consultation hour for every new client referred.

7. Cloud Infrastructure Costs

Estimate cloud costs based on client usage:

  • Basic Support Clients: ~$9.50/month.
  • Advanced Support Clients: ~$47.50/month.
  • Premium Support Clients: ~$95.00/month.

8. Profitability Example

With 10 clients (4 Basic, 4 Advanced, 2 Premium):

  • Monthly Revenue: $14,000.
  • Monthly Costs: $7,418 (cloud, salaries, other expenses).
  • Monthly Profit: $6,582.

Key Takeaways

  • Competitive Pricing: Charge half of competitor’s rates while maintaining profitability through automation and efficiency.
  • Tiered Subscriptions: Offer Basic, Advanced, and Premium tiers to cater to different budgets and needs.
  • Custom Solutions: Provide tailored workflows and algorithms for unique projects.
  • Free Pilots: Attract new clients with free or discounted pilots.
  • Referral Incentives: Encourage word-of-mouth marketing with discounts and free hours.

This pricing structure is designed to be affordable for clients, profitable for us, and scalable as our business grows. By offering a mix of subscription tiers, sample-based services, and custom solutions, we can cater to a wide range of clients and build a sustainable business.

3. Server Model

1. Dedicated Servers for Each Tier

Each tier (Basic, Advanced, Premium) would have its own dedicated server with pre-configured tools and pipelines. Here’s how it would work:

Tier 1: Basic Support ($500/month)

  • Server Access: Limited access to pre-built pipelines and basic tools.
  • Capabilities:
    • Run pre-configured pipelines (e.g., RNA-seq, variant calling).
    • Adjust basic parameters (e.g., thresholds, filters).
    • Generate basic visualizations (e.g., heatmaps, bar charts).
  • User Interface: Web-based interface with drag-and-drop functionality.
  • Example Use Case: A lab member uploads RNA-seq data, selects a pipeline, and adjusts the p-value threshold to generate a list of differentially expressed genes.

Tier 2: Advanced Support ($1,500/month)

  • Server Access: Full access to custom workflows, advanced tools, and APIs.
  • Capabilities:
    • Create and modify workflows (e.g., multi-omics integration).
    • Use APIs to automate data uploads and analysis.
    • Generate advanced visualizations (e.g., network graphs, pathway maps).
  • User Interface: Web-based interface with optional command-line access for advanced users.
  • Example Use Case: A Tech uses the API to upload RNA-seq and metabolomics data, runs a custom multi-omics integration workflow, and creates an interactive pathway map.

Tier 3: Premium Support ($3,000/month)

  • Server Access: Full access to custom algorithms, HPC resources, and real-time collaboration tools.
  • Capabilities:
    • Develop custom algorithms with support from our team.
    • Use HPC resources for large-scale analyses.
    • Share data and results with collaborators in real time.
  • User Interface: Web-based interface with full command-line access and dedicated support.
  • Example Use Case: A Tech collaborates with our team to develop a custom algorithm for single-cell RNA-seq analysis, uses HPC resources to process a large dataset, and shares the results with collaborators through an interactive dashboard.

2. Should Labs Analyze Their Data Themselves?

This depends on the lab’s preferences and technical expertise. Here’s how to cater to both scenarios:

Option 1: Labs Analyze Their Own Data

  • Pros:
    • Gives labs more control and flexibility.
    • Appeals to technically inclined users who enjoy hands-on work.
    • Reduces our workload for routine analyses.
  • Cons:
    • Requires labs to have some technical expertise.
    • May lead to more support requests if users encounter issues.

Option 2: We Analyze the Data for Them

  • Pros:
    • Saves labs time and effort.
    • Ensures high-quality, reproducible results.
    • Reduces the risk of user errors.
  • Cons:
    • Limits labs’ control over the analysis process.
    • Increases our workload for routine analyses.

3. Hybrid Approach: Offer Both Options

To cater to both types of clients, we can offer a hybrid approach:

  • Self-Service Option: Labs can log onto their dedicated server and analyze their data themselves.
  • Full-Service Option: We handle the analysis for them, providing results and visualizations.

How It Works:

  • Self-Service:
    • Labs access their dedicated server through a web-based interface or SSH.
    • They run pre-configured pipelines or create custom workflows.
    • We provide documentation, tutorials, and support to help them get started.
  • Full-Service:
    • Labs upload their data to the server.
    • We run the analysis, generate results, and provide a detailed report.
    • Labs can log in to review the results and visualizations.

4. Infrastructure Setup

Here’s how we can set up the dedicated servers for each tier:

Tier 1: Basic Support

  • Server Type: Shared server with limited resources.
  • Tools: Pre-configured pipelines, basic visualization tools.
  • Access: Web-based interface only.

Tier 2: Advanced Support

  • Server Type: Dedicated virtual machine (VM) with moderate resources.
  • Tools: Custom workflows, APIs, advanced visualization tools.
  • Access: Web-based interface and command-line access.

Tier 3: Premium Support

  • Server Type: High-performance computing (HPC) cluster or dedicated VM with scalable resources.
  • Tools: Custom algorithms, HPC resources, real-time collaboration tools.
  • Access: Web-based interface, full command-line access, and dedicated support.

5. Pricing and Profitability

The hybrid approach allows us to maximize revenue while keeping costs manageable:

  • Self-Service Option: Labs pay for server access and support.
  • Full-Service Option: Labs pay for server access, support, and analysis services.

Example:

  • Tier 2 Client (Self-Service): $1,500 / month for server access and support.
  • Tier 2 Client (Full-Service): $1,500/month for server access + $/project for analysis services.

6. Hourly Charges (Non-Sample-Based)

These rates are for consulting, training, and custom development work.

Service Provided ByOur Rate
Analyst$50/hr
Senior Analyst$75/hr

7. Sample-Based Services

These rates are for analyzing specific types of data.

Type of ServiceOur Rate
RNA-Seq$50/sample (up to 12), 50/sample (up to 12), 38/additional sample
Exome-Seq$50/sample (up to 12), 50/sample (up to 12), 38/additional sample
WGS$75/sample (up to 12), $75/sample (up to 12), $63/additional sample
RNA-seq/DNA-Seq for specific gene panel$25/sample (up to 50), $25/sample (up to 50), $20 (51-100), $15/additional sample
10x Genomics Single Cell$125/first library, $50/additional
Metagenomics – WGS$50/sample (up to12), $50/sample(up to 12), $38/additional sample
Metagenomics – 16s$25/sample
Microbial de novo assembly$25/sample
IPA/GSEA/GO Analysis$70/gene or protein list
Heatmap/Venn Diagram/PCA$35/plot
NIH GEO Submission (RNA-seq/microarray)$70/submission (up to 12 samples)
NIH SRA Submission (DNA-seq)Hourly basis (half of competition’s rate)

8. Compute/Dev Time Spent Per Client

The time we spend per client will depend on their tier of service (basic, advanced, premium) and the complexity of their projects. Here’s an estimate:

Tier 1: Basic Support ($500/month)

  • Time Spent: ~2-3 hours/week
    • Onboarding: 1 hour (initial setup and training).
    • Support: 1-2 hours (email/chat support, troubleshooting).
  • Activities:
    • Helping clients upload data and run basic analyses.
    • Answering questions about results and visualizations.

Tier 2: Advanced Support ($1,500/month)

  • Time Spent: ~5-7 hours/week
    • Onboarding: 2 hours (custom workflow setup and training).
    • Support: 3-5 hours (phone/chat support, troubleshooting, consultation).
  • Activities:
    • Customizing pipelines for specific projects.
    • Providing in-depth analysis and interpretation of results.
    • Training lab members on advanced tools.

Tier 3: Premium Support ($3,000/month)

  • Time Spent: ~10-12 hours/week
    • Onboarding: 3 hours (dedicated account manager, custom algorithm development).
    • Support: 7-9 hours (dedicated support, consultation, training).
  • Activities:
    • Developing custom algorithms and workflows.
    • Providing ongoing consultation and strategic advice.
    • Hosting training sessions and workshops for the lab.

9. Key Takeaways

  • Dedicated Servers: Offer each tier its own server with pre-configured tools and pipelines.
  • Hybrid Approach: Allow labs to analyze their own data or outsource the work to us.
  • Flexibility: Cater to both technically inclined users and those who prefer a hands-off approach.
  • Scalability: Use cloud infrastructure (e.g., AWS, Azure, Google Cloud) to scale resources as needed.

By offering dedicated servers and a hybrid approach, we can provide a flexible, user-friendly solution that meets the needs of a wide range of clients. This approach not only enhances the value of our service but also positions us as a trusted partner in their research.

4. Marketing

1. Network

Our network is our most valuable asset at this stage. Here’s how to make the most of our connections:

  • Ask for Introductions: Request introductions to other PIs, lab managers, or researchers who might benefit from our service.
  • Collaborate on a Pilot Project: Offer to analyze data from our mentor’s lab for free or at a discounted rate in exchange for a testimonial or case study.
  • Co-Author a Paper: If someone is publishing research, offer to contribute bioinformatics analysis and co-author the paper. This will give us credibility and visibility.

2. Build an Online Presence

A strong online presence is essential for attracting clients. Start with these steps:

a. Create a Professional Presence

  • Key Points:
    • Value: Explain our services and value proposition.
    • Services: Detail our offerings (e.g., RNA-seq analysis, cross-omics integration).
    • Case Studies: Showcase success stories.
    • Blog: Share insights on bioinformatics trends, tips, and best practices.
    • Contact: Make it easy for potential clients to reach us.
  • Tools: https://www.genomabfx.com

b. LinkedIn Profile

  • Optimize Profile: Highlight our expertise, services, and success stories.
  • Engage with Content: Share articles, comment on posts, and join bioinformatics-related groups to build visibility.
  • Connect with Researchers: Reach out to PIs, lab managers, and researchers with a personalized message introducing our service.

c. Social Media

  • Twitter/X: Share insights, tools, and success stories using hashtags like #bioinformatics, #genomics, and #omics.
  • YouTube: Create short tutorials or demos of our tools (e.g., “How to Analyze RNA-seq Data in 5 Minutes”).
  • Reddit: Participate in subreddits like r/bioinformatics and r/labrats to share our expertise and subtly promote our service.

3. Offer Free or Discounted Pilots

To attract our first clients, offer free or discounted pilot projects in exchange for feedback and testimonials. Here’s how:

  • Target Labs: Reach out to labs working on projects that align with our expertise (e.g., RNA-seq, multi-omics).
  • Pitch Our Value: Explain how our service can save them time, reduce costs, or uncover new insights.
  • Deliver Exceptional Results: Use the pilot to demonstrate our expertise and build trust.

4. Network at Conferences and Events

Even without a large network, we can start building connections at:

  • Local Meetups: Attend bioinformatics or genomics meetups in our area.
  • Conferences: Present a poster or give a talk at conferences like ASHG, ISMB, or AGBT.
  • Workshops: Host or attend workshops on bioinformatics tools and techniques.

Pro Tip: Bring business cards and a one-page flyer summarizing our services to hand out.

5. Collaborate with Core Facilities

Many universities and research institutions have core facilities that provide bioinformatics services. We can:

  • Partner with Them: Offer to complement their services (e.g., by providing cross-omics integration or advanced visualization).
  • Refer Clients: If a core facility is overwhelmed, they may refer clients to us.

6. Write Guest Articles or Blogs

Publishing articles in reputable outlets can establish us as an expert and drive traffic to our website. Consider:

  • Scientific Blogs: Write for platforms like Medium, Towards Data Science, or BioIT World.
  • Industry Publications: Pitch articles to journals or magazines like Nature Bioinformatics, Genome Biology, or The Scientist.
  • University Newsletters: Offer to write a guest piece for institutions or other universities.

7. Create Educational Content

Educational content can attract potential clients while showcasing our expertise. Ideas include:

  • Tutorials: Create step-by-step guides for common bioinformatics tasks (e.g., “How to Analyze RNA-seq Data”).
  • Webinars: Host free webinars on topics like “Introduction to Multi-Omics Integration” or “Best Practices for Data Visualization.”
  • Cheat Sheets: Design downloadable resources (e.g., “Top 10 Bioinformatics Tools for Genomics Research”).

8. Join Online Communities

Engage with researchers and bioinformaticians in online communities to build relationships and promote our service:

  • ResearchGate: Share our expertise and connect with researchers.
  • LinkedIn Groups: Join groups like “Bioinformatics and Genomics Professionals” or “Life Science Innovators.”
  • Slack Communities: Participate in bioinformatics-focused Slack groups like Bioinformatics Chat.

9. Leverage University Resources

If they’re affiliated with a university, take advantage of its resources:

  • Tech Transfer Office: They may help us connect with researchers or commercialize our service.
  • Alumni Network: Reach out to alumni working in bioinformatics or related fields.
  • Department Seminars: Offer to give a seminar or workshop on our services.

10. Use Cold Outreach (Carefully)

While cold outreach can be hit-or-miss, it can work if done thoughtfully:

  • Personalized Emails: Research labs and PIs, then send personalized emails explaining how our service can help them.
  • Focus on Pain Points: Highlight specific challenges (e.g., data integration, visualization) and how we can solve them.
  • Follow Up: Send a polite follow-up email if we don’t hear back.

11. Offer Referral Incentives

Encourage early clients to refer others by offering incentives:

  • Discounts: Provide a discount on future services for successful referrals.
  • Free Hours: Offer free consultation hours or analysis for every new client they bring in.

12. Track and Optimize Efforts

Use analytics tools to track the effectiveness of our marketing efforts:

  • Website Analytics: Use Google Analytics to monitor traffic and conversions.
  • Social Media Insights: Track engagement on platforms like LinkedIn and Twitter.
  • Client Feedback: Ask early clients how they found us and what convinced them to try our service.

Even without an established network, we can effectively market our bioinformatics service by leveraging connections, building an online presence, offering free pilots, and engaging with the research community. Focus on providing value, building relationships, and showcasing our expertise, and we’ll gradually attract clients and grow our business.