Discovering the Language of Genes
Unravel the mysteries encoded in your RNA with precision and innovation. Advanced transcriptomics analysis for groundbreaking discoveries.
Our Transcriptomics Capabilities
In the ever-evolving landscape of genomics, understanding the intricate language of genes is pivotal. Our Transcriptomics Data Analysis Service empowers researchers to glean unprecedented insights from transcriptomic data, informing drug discovery, biomarker identification, and personalized medicine initiatives.
RNA Sequencing (RNA-seq) Analysis
We provide a full suite of RNA-seq analysis services, starting from raw data quality control to quantification and differential expression.
- Data Quality Control and Preprocessing
- Read Alignment and Quantification
- Normalization of Read Counts
- Differential Gene Expression (DEGs) Identification
Functional & Advanced Analysis
Move beyond gene lists to understand the biological meaning. We offer advanced analyses to uncover functional insights and regulatory networks.
- Functional Enrichment Analysis (Gene Ontology & Pathway Analysis)
- Co-expression Network Analysis
- Long Non-Coding RNA (lncRNA) Analysis
- Small RNA Analysis (miRNA, siRNA, etc.)
Integrative Analysis
Gain a holistic view of your biological system by integrating transcriptomic data with other omics layers.
- Multi-Omics Integration (Transcriptomics with Genomics, Proteomics, Metabolomics)
- Correlation with Genomic and Proteomic Data
- Regulatory Network Reconstruction
Our Transcriptomics Analysis Workflow
Quality Control & Preprocessing
Comprehensive QC including adapter trimming, quality filtering, and rRNA removal.
Alignment & Quantification
Read alignment to reference genome and transcript/gene quantification.
Differential Expression
Statistical analysis to identify significantly differentially expressed genes.
Functional Interpretation
Pathway analysis, network modeling, and biological context interpretation.
Get a Quote for Your Transcriptomics Project
Our team is ready to help you design the best analysis strategy for your RNA-Seq data.
Frequently Asked Questions
Find answers to common questions about our transcriptomics services and processes.
We support various RNA types and sequencing approaches:
PolyA-selected, stranded and unstranded
rRNA-depleted, whole transcriptome
miRNA, siRNA, piRNA analysis
10X, Smart-seq, Drop-seq platforms
We employ multiple statistical approaches for robust results:
Negative binomial models for count data with multiple testing correction
Linear models with precision weights for complex designs
Specialized methods for single-cell RNA-seq data
ComBat, Harmony, and other methods for technical variation
Yes, we provide comprehensive experimental design support:
Design Consultation
- Replicate number optimization
- Batch effect minimization strategies
- Control selection and experimental setup
- RNA quality and quantity assessment
Power Analysis
- Sample size calculation for desired power
- Effect size estimation from pilot data
- Multiple testing burden assessment
- Cost-benefit analysis for sequencing depth
Gene Set Enrichment
Pre-ranked and competitive enrichment analysis
Pathway Databases
Comprehensive pathway and process annotation
Note: Single-cell analyses typically require additional time due to computational complexity.