Transcriptomics Services: RNA-Seq Data Analysis for Microbial and Host Transcriptomes
From raw FASTQ files to differential gene expression, functional enrichment, and publication-ready figures.
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. For a more detailed explanation about what transcriptomics is, you should read the dedicated post in our blog!
While genomics, metagenomics, or microbiome analysis can help identify which organisms or genes are present, transcriptomics reveals which genes are actively expressed and how expression changes across conditions. RNA-seq analysis is therefore often integrated withother approaches such as metagenomics, microbiome analysis or microbial genomics.
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 RNA-Seq Analysis?
RNA-seq analysis provides insight into the functional biology of your system by measuring gene expression across conditions. Whether you are studying microbes, hosts, or mixed systems, transcriptomics can help identify regulatory responses, pathway changes, and condition-specific expression patterns.
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 RNA-Seq Data Analysis 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 analysis.
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 environmental transcriptomics or host-associated response studies.
Integration with Other -Omics
Combine transcriptomic data with metagenomics, proteomics and metabolomics for systems-level understanding of cellular regulation.
RNA-Seq Analysis Workflow
Our transcriptomics pipeline processes raw RNA-Seq reads into biologically
interpretable results, including differential gene expression and pathway
analysis. For a broader explanation of a typical RNA-Seq pipeline, see our guide: RNA-Seq Data Analysis Pipeline: From FASTQ Files to Differential Gene Expression
Our RNA-Seq Data Analysis Services
We provide end-to-end RNA-seq analysis services for microbial, host, and environmental transcriptomes. From raw reads to publication-ready visualizations and statistical results, each workflow is tailored to your organism, experimental design, and research question. Our RNA-seq analysis pipelines rely on widely used bioinformatics tools such as STAR, HISAT2, Salmon, DESeq2, and edgeR for robust and reproducible differential gene expression analysis.
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.
What Data Do You Need to Start?
- Raw RNA-Seq FASTQ files (Illumina or other platforms)
- Single-end or paired-end sequencing reads
- Reference genome or transcriptome (optional)
- Sample metadata and experimental design
If a reference genome is not available, we can perform de-novo transcriptome
assembly and downstream analysis
Supported Organisms and Systems
Bacterial transcriptomics
Archaeal gene expression analysis
Microbial communities
Host–microbe interaction studies
Environmental transcriptomics
Why Choose Our RNA-Seq Analysis Services?
Our transcriptomics services combine biological expertise with a flexible, hands-on approach to deliver analyses that are accurate, reproducible, and tailored to your research question. We do not rely on one-size-fits-all workflows: each project is adapted to your design, organism, and analytical 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 heatmaps to volcano 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.
RNA-Seq Analysis Deliverables
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 Asked Questions (F.A.Q.)
Q1. What kinds 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!