Vivofold Research

Genomics & Transcriptomics

Name: Vivofold
Price range: ₹₹

Our genomics work focuses on the reliability of standard analyses: how batch effects, design choices and method defaults change conclusions, and how to make differential expression, enrichment and variant analyses robust and reproducible.

Collaborate

Volcano plot from a differential-expression test. Genes beyond |log₂FC| > 1 at 5% FDR are coloured: up-regulated in vermilion, down-regulated in blue.

Questions

What we want to know

How sensitive are published differential-expression results to reasonable analysis choices?
Which batch-correction strategies preserve biology in small, unbalanced designs?
How should single-cell annotations be validated when no ground truth exists?

Approach

How we work on it

Re-analysis of public datasets with documented, versioned pipelines
Simulation studies with planted effects
Comparison of methods under controlled conditions

Methods already implemented

Open projects

Projects you can join

Robustness of RNA-seq conclusions

Re-analyse published RNA-seq studies under alternative, defensible pipelines and measure how conclusions change.

Batch correction in small designs

Benchmark correction methods on simulated and public data with known batch structure.

Annotation agreement in single-cell data

Quantify agreement between automated cell-type annotation methods across public atlases.

Across Vivofold

Learn it, use it, commission it

Vedicgen courses

RNA-seq Data AnalysisUp to 4 weeks, about 32 hours live (customisable)Dry labfrom ₹4,499 + GST Single-Cell RNA-seq AnalysisUp to 4 weeks, about 32 hours live (customisable)Dry labfrom ₹5,999 + GST Multi-Omics Data IntegrationUp to 4 weeks, about 32 hours live (customisable)Dry labfrom ₹5,999 + GST

Bioinformatics & Genomics Research Internship Integrated Wet + Dry Research Internship

Research services

RNA-seq Data AnalysisDifferential expression and pathway analysis from FASTQ files or a count matrix.Single-Cell RNA-seq AnalysisQC, integration, clustering, annotation and condition comparisons for single-cell data.Multi-Omics Data IntegrationCombine two or more omics layers into one validated, interpretable analysis.

Nayancode software

Nayancode Expression StudioCounts in, differential expression and pathways out.Nayancode Single-Cell & Spatial StudioFrom matrix to annotated clusters, then into tissue space.