Transcriptomics Services: From raw RNA‑Seq data to differential gene expression and functional interpretation.
Tailored Transcriptomics Services for microbial and host transcriptomes.
What is Transcriptomics and Why Does It Matter
Transcriptomics is the study of the transcriptome, the complete set of RNA transcripts produced by cells under specific conditions. Unlike genomics, which reveals the genetic potential of an organism, transcriptomics provides a dynamic snapshot of gene activity, showing how organisms respond to stimuli, environments, or treatments.
While genomics, metagenomics, or microbiome profiling tell us who is present, our transcriptomics services reveal what they’re doing — identifying genes that are actively expressed and how their expression changes across conditions.
This information is crucial for:
Understanding functional responses to stress or treatment
Identifying biomarkers or drug targets
Exploring regulatory pathways and gene networks
What Can You Achieve with our Transcriptomics Services?
Transcriptomic analysis opens a window into the functional biology of your system. By analyzing RNA expression, you can move beyond the question of who is present to understand how they respond, adapt, or interact. Whether you’re studying microbes, hosts, or mixed communities, our transcriptomics services deliver actionable insights across multiple biological levels.
Identify Key Regulatory Genes
Uncover transcription factors and regulators that control pathways of interest — from virulence to stress response.
Compare Gene Expression Across Conditions
Understand how gene activity shifts between time points, treatments, or environments, revealing differential patterns of expression.
Explore Pathway Activation and Suppression
Assess which biological pathways are turned on or off under specific conditions using enrichment analysis and pathway databases.
Support Hypothesis-Driven or Exploratory Research
Generate new hypotheses or validate existing ones by measuring transcript-level responses in a high-throughput, quantitative way.
Applications of our Transcriptomics Services
Functional Genomics
Identify which genes are up- or downregulated under different conditions, complementing genome annotation with real-time gene expression data.
Host–Microbe Interaction Studies
Reveal how hosts and microbes influence each other at the gene expression level — a powerful extension of microbiome profiling.
Comparative Transcriptomics
Compare expression profiles across strains, species, or experimental conditions to identify pathways involved in resistance, adaptation, or virulence — often alongside comparative genomics.
Drug & Treatment Response
Understand how organisms respond at the molecular level to antibiotics, stress, or compounds, enabling biomarker discovery and precision intervention strategies.
Environmental or Evolutionary Stress Responses
Explore how transcriptomes shift in response to temperature, salinity, pH, or nutrient limitation — ideal for researchers working with metagenomic or environmental RNA samples.
Integration with Other -Omics
Combine transcriptomic data with proteomics and metabolomics for systems-level understanding of cellular regulation.
A typical Transcriptomics Services workflow
Our Transcriptomics Services
We provide complete RNA-Seq analysis services for microbial, host, or environmental transcriptomes. From raw reads to publication-ready visualizations and statistics, our workflows are tailored to your experiment, organism, and question — whether you’re exploring differential gene expression, functional pathways, or stress responses.
Quality Control
We begin by assessing raw data quality with tools like FastQC and trimming low-quality bases or adapters using fastp or Trimmomatic, ensuring clean input for alignment.
Differential Expression Analysis
We identify genes with statistically significant expression changes between conditions using DESeq2, edgeR, or limma-voom, with full model transparency and p-value correction.
Functional Enrichment & Pathway Analysis
Enriched pathways and GO terms are detected to interpret the biological meaning of gene expression changes using tools like ClusterProfiler, GSEA, or KEGG/Reactome mapping.
Visualization & Reporting
You’ll receive volcano plots, heatmaps, PCA plots, and other visuals that clearly communicate your transcriptomic trends and clustering patterns.
Custom Comparisons & Metadata Integration
We adapt our models to your study design — time series, multifactorial comparisons, batch correction — and include relevant metadata in visualizations and stats.
Why Choose Our Transcriptomics Services?
Our Transcriptomics services combine biological expertise with a flexible, hands-on approach to deliver transcriptomic analyses that are accurate, reproducible, and tailored to your research question. We don’t just run one-size-fits-all scripts — we work with you to shape each project based on your design, organism, and goals. We deliver transcriptomic analyses that are accurate, reproducible, and ready for interpretation or publication
Scientific Expertise
Our background in microbial evolution, host-pathogen interaction, and gene regulation ensures biological relevance, not just raw outputs.
Tailored Pipelines
We help structure your contrasts, replicates, and metadata from the start — improving the power and clarity of your differential expression results.
Custom Project Design & Consultation
We support you from the start — helping define contrasts and replicates to reach your experimental goals.
Insightful Visualizations
We generate publication-quality plots covering your needs: from heat maps to vulcano plots or summary tables our deliverables are designed for insight and communication.
Responsive & Fast Turnaround
Need results for a grant, thesis, or upcoming manuscript? We offer clear timelines, ongoing updates, and responsive communication.
Deliverables – What You’ll Receive
Every transcriptomics project comes with a set of carefully curated deliverables, designed to ensure transparency, reproducibility, and scientific utility. Whether you’re preparing a manuscript, reporting to collaborators, or planning follow-up experiments, your results will be organized and ready to use.
Quality Control Report
FastQC summaries, trimming stats, and read filtering metrics in PDF and/or HTML format.
Aligned Reads (Optional)
BAM files aligned to the reference genome or transcriptome, ready for visualization or downstream analysis.
Expression Matrices
Raw and normalized counts at gene or transcript level (CSV/TSV), ready for custom plots or secondary analysis.
Differential Expression Results
Tables with log2 fold changes, p-values, adjusted p-values (FDR), and significance flags — plus volcano plots.
Functional Enrichment Analysis
Pathway enrichment and GO term outputs, including bar plots or enrichment maps for biological interpretation.
Summary Report (PDF)
A concise, human-readable document detailing the methods, parameters used, key findings, and interpretation notes.
Publication‑Ready Visualizations
Heatmaps, PCA plots, clustering trees, MA/volcano plots, and custom visual outputs (as SVG/PNG/PDF).
Frequently Asqued Questions (F.A.Q.)
Q1. What kind of data do you accept for your Transcriptomics services analyses ?
We primarily work with RNA-Seq FASTQ files from Illumina sequencing (single- or paired-end). If you have aligned data (e.g., BAM), we can adapt our workflow — just let us know.
Q2: Can you help me design my transcriptomics experiment?
Yes! Our Transcriptomics Services include project design support to help define conditions, replicates, and contrasts, ensuring your design is statistically sound and biologically relevant.
Q3: What tools and pipelines do you use?
We use tools like FastQC, Trimmomatic/fastp, STAR, Salmon, DESeq2, limma, and ClusterProfiler, adapting the workflow based on your organism and research question.
Q4: Can I request custom analyses or visualizations?
Yes! All our pipelines are customizable. Let us know if you need specific comparisons, metadata integration, or custom visual styles for figures.
Q5: How do you handle normalization and batch effects?
We apply appropriate normalization techniques (e.g., variance-stabilizing transformation) and can incorporate batch correction if needed — all steps are documented and transparent.
Q6: How long does the analysis take?
Turnaround is typically 5–10 business days, depending on dataset size and project complexity. Let us know if you have a deadline!