Transcriptome Analysis (RNA-Seq)
End-to-end RNA-Seq analysis — quality control, alignment / quantification, differential expression and functional enrichment — turning raw reads into biological insight.
What we offer
What you receive
Workflow
Sample & QC
Extraction, QC and library prep under documented, standardised protocols.
Sequencing / Processing
Calibrated runs and pipelines on validated platforms.
Bioinformatics
HPC-backed assembly, alignment, variant calling and annotation.
Report & Insight
Publication-ready reports, with a dedicated project manager throughout.
Frequently asked
We accept tissue, whole blood, cell pellets, extracted DNA/RNA and a range of environmental and microbial samples. Our team advises on collection and shipping for each project.
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Tell us your sample type, scope and timelines — we'll respond within one business day.
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Transcriptome Analysis (RNA-Seq)
Decode gene expression dynamics. We map the functional state of cells through rigorous statistical modeling, Differential Gene Expression (DGE), and AI-driven pathway interpretation.
Core Analyses
1. Differential Gene Expression (DGE)
Identifying statistically significant Up-regulated and Down-regulated genes across biological conditions, time-series, or developmental stages.
2. Functional Enrichment & Pathways
Contextualizing DGE results against Gene Ontology (GO), KEGG, and Reactome databases to highlight altered systemic biological pathways.
3. Advanced Structural Analysis
Alternative splicing detection, novel transcript discovery, and Gene Co-expression Network Analysis (WGCNA).
Application Areas
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Microbial: Response to stress, antibiotic resistance gene expression, and Dual RNA-Seq.
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Plant: Abiotic/biotic stress responses, crop yield traits, and developmental tissues.
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Animal & Human: Biomarker discovery, cancer transcriptomics, immunology profiling, and toxicology.
Short-Read Platforms
Illumina (NextSeq 2000, NovaSeq X), MGI (DNBSEQ-G400), AVITI, Thermo Ion GeneStudio. Best for robust DGE.
Long-Read Platforms
PacBio (Iso-Seq), Oxford Nanopore (Direct RNA-Seq). Best for full-length isoform discovery.
AI Advantage
We utilize Predictive ML models for biomarker classification and LLM-driven synthesis to summarize complex biological pathways from highly enriched gene modules.
Data & Quality Requirements
- • Format: De-multiplexed FASTQ with MD5 checksums
- • Read Depth: 20-30 Million Reads/Sample (Eukaryotic), 5-10M (Microbial)
- • Quality Metric: Q30 > 85%
- • Sample Integrity: RNA Integrity Number (RIN) > 7.0 (via Agilent 2100)
Pipeline Tools
Alignment & Quant: STAR, HISAT2, Salmon, featureCounts
Statistical DGE: DESeq2, edgeR, limma-voom
Functional Mapping: clusterProfiler, g:Profiler, STRING
Commercials & Data Deliverables
| Analysis Depth | TAT | Approx Price |
|---|---|---|
| Standard DGE Analysis | 14 Days | ₹8,000 - ₹15,000 / Sample |
| Advanced (Iso-Seq/Long Read) | 21 Days | ₹10,000 - ₹18,000 / Sample |