BIOINFORMATICS · Service

(Meta)genomics
and Multi-Omics

From raw reads to biological insights — we turn your sequencing data into scientific stories.

You generated the data. Now what? We run rigorous, reproducible bioinformatics analysis for research groups, graduate students, and industry teams — from a single 16S amplicon run to full multi-omics experiments spanning five data layers. We handle everything from quality control through publication-ready figures. Every analysis is built around your biological question, not a generic pipeline.

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Capabilities

What We Analyze

Amplicon Profiling (16S / ITS / 18S)

Bacterial and Archaeal Community Profiling (16S rRNA)

End-to-end 16S amplicon analysis — demultiplexing, quality filtering, ASV/OTU generation, taxonomic classification, and ecological analysis. We characterize community composition, alpha and beta diversity, differential abundance, and functional potential across your experimental conditions.

Fungal Community Profiling (ITS)

ITS1/ITS2 amplicon analysis for fungal diversity assessment. Taxonomic assignment against curated fungal databases (UNITE), diversity metrics, and community comparison across samples and treatments.

Microeukaryotic Profiling (18S rRNA)

Community analysis for protists and other microeukaryotes. Particularly relevant for environmental, marine, and soil ecology studies where the eukaryotic fraction is biologically significant.

Whole-Genome Shotgun Metagenomics

Taxonomic Profiling

Species- and strain-level community characterization using both read-based and assembly-based approaches. We go beyond "what is there" to quantify relative and estimated absolute abundances with proper normalization.

Functional Annotation

Gene-level and pathway-level functional profiling of microbial communities. We map reads and genes from assembled contigs to KEGG, COG, CAZy, and custom functional databases to answer "what can this community do", not just "who is there."

Genome Assembly and Binning (MAG Reconstruction)

Genome-resolved metagenomics. We assemble, bin, refine, and assess quality — reconstructing near-complete MAGs with organism-level resolution from a community sample.

Metabolic Pathway Reconstruction

From MAGs or unbinned assemblies, we reconstruct complete and partial metabolic pathways (carbon fixation, nitrogen cycling, sulfur metabolism, fermentation routes, and xenobiotic degradation) to link community membership to ecosystem function.

See also: AMR and Resistome Profiling →

(Meta)transcriptomics

Bulk RNA-Seq Analysis

Differential gene expression analysis from standard RNA-Seq experiments. Quality control, read alignment, quantification, normalization, and statistical testing. We deliver gene lists, volcano plots, heatmaps, and pathway enrichment results tied to your experimental design.

Metatranscriptomics

We distinguish what the community can do (metagenomics) from what it is actually doing (metatranscriptomics). Active pathway identification, expression-level functional profiling, and transcriptional response analysis — all tied to your experimental conditions.

(Meta)proteomics

Metaproteomic Analysis

Protein-level characterization of microbial communities. Peptide identification, protein inference, taxonomic and functional annotation, and quantitative comparison across conditions. We link expression data back to genomic origins using sample-specific databases — enabling organism-level functional interpretation.

DIA-Based Quantitative Proteomics

Data-independent acquisition proteomics analysis using DIA-NN and related tools. Library-free and library-based workflows for deep, reproducible quantification of complex proteomes across experimental conditions.

Metabolomics

Untargeted Metabolomics

Feature detection, annotation, statistical analysis, and pathway mapping from LC-MS or GC-MS metabolomics datasets. We identify significantly altered metabolites across conditions and map them onto biological pathways using custom workflows.

Targeted Pathway Analysis

Focused analysis of specific metabolic pathways or metabolite classes relevant to your study (short-chain fatty acids, amino acids, lipid profiles, and secondary metabolites) with quantitative comparison and biological contextualization.

Multi-Omics Integration

Paired Multi-Omics Analysis

Integration of two or more omics layers from the same samples (metagenomics + metatranscriptomics, genomics + proteomics, transcriptomics + metabolomics) using multivariate integration frameworks. We identify cross-omics signatures, co-varying features, and multi-layer biomarkers that no single omics layer can reveal alone.

Cross-Omics Network Analysis

Construction and analysis of multi-omics correlation networks linking taxa, genes, transcripts, proteins, and metabolites. We identify hub features, functional modules, and the regulatory or ecological relationships that drive your system.

Systems-Level Biological Interpretation

We do not just integrate data — we interpret it. Every multi-omics project ends with a coherent biological narrative: which organisms are doing what, which pathways are active, and how they connect across molecular scales. That is the "From Atoms to Systems" principle.

Outputs

Analysis and Deliverables

Every project gets a tailored analysis package — built around your question, not a fixed menu. Every deliverable goes directly into your manuscript, thesis, or technical report.

Standard Analyses

Community Ecology

  • Alpha diversity (Shannon, Simpson, Chao1, observed ASVs/species)
  • Beta diversity (Bray-Curtis, UniFrac, Jaccard) with PCoA/NMDS ordination
  • Rarefaction curves
  • PERMANOVA and ANOSIM for statistical testing of group differences
  • Co-association network

Taxonomic and Functional Profiling

  • Taxonomic stacked barplots, composition summaries (phylum to species)
  • Differential abundance analysis with effect sizes
  • Functional gene and pathway abundance profiles (KEGG, CAZy, custom DB)
  • Indicator species analysis
  • Antimicrobial resistance gene profiling (detailed analysis available as a dedicated service)

Genome-Resolved Outputs

  • MAG quality reports (completeness, contamination, strain heterogeneity)
  • Phylogenomic placement and taxonomic assignment
  • Average nucleotide identity (ANI) comparisons against reference genomes
  • Metabolic reconstruction per MAG with pathway completeness scores
  • Gene-taxa physical mapping for host organism identification
  • Pangenome analysis where relevant

Expression and Quantification

  • Raw and normalized expression matrices
  • Differential expression with multiple testing correction
  • Gene set and pathway enrichment analysis
  • Transcript-to-gene abundance ratios for paired metagenome-metatranscriptome datasets
  • Volcano plots, MA plots, heatmaps with hierarchical clustering

Multi-Omics Outputs

  • Sparse PLS and canonical correlation plots
  • Multi-omics factor loadings and variance decomposition
  • Cross-omics correlation networks with hub identification
  • Integrated pathway diagrams linking genomic potential to expression to metabolite levels

What You Receive

01

Analysis Report

A structured, narrated report walking through every analysis step with publication-quality figures, statistical summaries, and biological interpretation. For academic clients, written to slot directly into your results and methods sections. For industry clients, formatted as a technical report with executive summary.

02

Publication-Ready Figures

High-resolution figures (PDF/SVG/PNG at 300+ dpi) with consistent styling, proper axis labels, legends, and statistical annotations. Designed for journal submission or internal presentations.

03

Data Package

Processed data tables (ASV/OTU tables, gene abundance matrices, MAG statistics, expression matrices), publication-ready figures, and a detailed methods report for full reproducibility.

04

Methods Text

A ready-to-use methods section for your manuscript, thesis, or report, citing all software, databases, and parameters used.

05

Pipeline Documentation

Step-by-step record of every tool, version, parameter, and database used. Full computational reproducibility guaranteed.

Technical Stack

Tools and Platforms

Industry-standard and state-of-the-art platforms across every omics layer, ensuring reproducibility and methodological rigor from raw data to final interpretation.

Amplicon Analysis

QIIME2 DADA2 SILVA UNITE Phyloseq MicrobiomeAnalyst

Taxonomic and Functional Profiling

Kraken2 Bracken MetaPhlAn HUMAnN3 Kaiju

Assembly and Genome Resolution

MEGAHIT metaSPAdes Bowtie2 Prodigal DIAMOND MaxBin2 MetaBAT2 CONCOCT DAS Tool CheckM GTDB-Tk

Transcriptomics and Expression

STAR HISAT2 featureCounts Salmon DESeq2 edgeR

Proteomics

DIA-NN MaxQuant Perseus

Metabolomics

MetaboAnalyst XCMS MS-DIAL

Multi-Omics Integration

mixOmics MOFA2 NetworkX igraph WGCNA

Workflow and Reproducibility

Snakemake Nextflow nf-core/mag Docker Singularity Git

Computing Infrastructure

Linux HPC clusters SLURM workload management Scalable from single-sample to large cohorts
Process

How We Work

A structured, transparent process from your first message to the final figure: every decision documented, every output explained, every result interpreted in the context of your biology.

01

Consultation and Experimental Design Review

You share your question, study design, and data. We review your setup and tell you whether it can answer your question. If you are still planning — we help you optimize sequencing depth, replication, and multi-omics strategy before you spend on sequencing.

02

Data Quality Control

We assess raw data quality, trim adapters, filter reads, remove chimeras, and decontaminate host reads. You receive a QC summary before we proceed. No analysis runs on bad data.

03

Core Analysis

The main analytical pipeline, tailored to your data type and question. For amplicon data: ASV generation through diversity analysis. For metagenomics: assembly through MAG reconstruction and functional annotation. For multi-omics: individual layer processing followed by integration. Every step is documented and version-controlled.

04

Interpretation and Contextualization

We do not hand you a folder of tables and call it done. We interpret the results in the context of your biological question, your experimental design, and the relevant literature. If something unexpected emerges, we flag it and suggest follow-up analyses or validation experiments.

05

Delivery and Post-Delivery Support

You receive the full package: report, figures, data tables, scripts, and methods text. We stay with you through publication — revision requests, reviewer responses, additional analyses, and figure updates all included.

Pricing

Standard Packages

Structured tiers matched to the scope and complexity of your project. All packages include raw processed data, reproducible scripts, and post-delivery support through publication or project completion. Pricing provided upon consultation.

Starter

Single-Layer Amplicon Analysis

Best for: A lab or student with one 16S/ITS dataset that needs proper analysis for a paper or thesis.

  • Quality control and ASV/OTU generation
  • Taxonomic classification and composition visualization
  • Alpha and beta diversity analysis with statistical testing
  • Differential abundance analysis across experimental groups
  • Predicted functional potential
  • Analysis report with publication-quality figures
  • Methods section for manuscript or thesis
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Standard

Shotgun Metagenomics

Best for: Research groups with whole-genome shotgun data who need both community profiling and functional characterization.

  • Read-based and assembly-based taxonomic and functional profiling as needed
  • Metagenomic assembly and gene prediction
  • MAG reconstruction, quality assessment, and taxonomic placement
  • Metabolic pathway reconstruction per MAG
  • Comparative analysis across conditions as needed
  • Comprehensive report with figures, data tables, and methods text
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Advanced

Multi-Omics Integration

Best for: Projects with two or more omics layers that need integrated analysis and systems-level interpretation.

  • Individual processing and analysis of each omics layer
  • Cross-omics integration using multivariate frameworks
  • Correlation network construction and hub feature identification
  • Integrated pathway mapping and systems-level narrative
  • Full report with multi-panel figures and integrated interpretation
  • Methods text covering all layers and integration approaches
Get a Quote →
Custom

Ongoing Support

Best for: Labs, research centers, or companies that generate omics data routinely and need a dedicated bioinformatics partner.

  • Flexible scope: monthly retainer, per-project, or per-dataset pricing
  • Priority scheduling and dedicated support
  • Co-authorship arrangements where appropriate (academic)
  • Confidential deliverables under NDA (industry)
  • Suitable for longitudinal studies, clinical cohorts, and environmental monitoring
  • Experimental design consultation included
Discuss Terms →
FAQ

What to Expect

An amplicon analysis (Starter) typically takes 1–2 weeks. Shotgun metagenomics with MAG reconstruction takes 3–5 weeks depending on dataset size and complexity. Multi-omics integration projects take 4–8 weeks. Timelines are confirmed during consultation based on your specific data.
Yes. Send us the raw FASTQ files (or a download link) along with your sample metadata and experimental design, and we can begin within days. We work with data from any sequencing platform: Illumina, Oxford Nanopore, and PacBio.
Absolutely. This is the ideal time to engage us. We advise on sequencing depth, replication strategy, sample collection, DNA/RNA extraction considerations, and which omics layers will best answer your question. Getting the design right saves significant time and money downstream.
Raw FASTQ files (paired-end or single-end) for sequencing data. Raw instrument files or peak tables for metabolomics. For proteomics, raw mass spec files or processed peptide lists. We also need a metadata file describing your samples, conditions, and experimental design; we provide a template.
Yes. We work with Illumina short reads, Oxford Nanopore long reads, PacBio HiFi reads, and hybrid assemblies. For multi-platform datasets, we design the analysis strategy to leverage the strengths of each technology.
We offer modular services. If you already have assembled MAGs and just need functional annotation, or you have processed expression matrices and need differential expression and pathway analysis; we scope the work to exactly what you need. No unnecessary steps, no inflated pricing.
That is the explicit goal. For academic clients, every deliverable is designed to go directly into a manuscript or thesis: figures at journal resolution, methods sections with proper citations, and statistical analyses with appropriate corrections. We also support reviewer responses if your computational methods are questioned during peer review.
For academic projects involving substantial intellectual contribution (experimental design input, interpretation, and manuscript writing), co-authorship is discussed upfront and follows standard academic norms. For straightforward service work, acknowledgment is sufficient. Terms are always agreed before work begins.
Yes. For industry and commercial clients, we work under NDAs and maintain strict confidentiality. For academic clients, we follow standard collaborative norms and do not share data outside the project. Raw data is deleted from our systems after project completion unless you request otherwise.
We offer flexible pricing for student projects. A focused amplicon analysis or a single metagenome for a thesis chapter is very accessible. Reach out and we will work something out.
Amplicon sequencing (16S/ITS) tells you who is in your community; it is cheaper, well-established, and sufficient for many ecology and diversity studies. Shotgun metagenomics tells you both who is there and what they can do; it provides functional information, genome-level resolution, and strain-level discrimination. We help you decide which approach matches your question and budget during consultation.
Yes. Our pipelines are designed for scalability using workflow managers (Snakemake, Nextflow) and containerized environments (Docker, Singularity). Whether you have 20 samples or 2,000, the analytical framework is consistent, reproducible, and efficient.
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Ready to Decode Your Data?

Have sequencing data waiting for analysis? A multi-omics experiment to design? Send us your data and your question — we will build the right analytical strategy.

Discuss Your Project

Typical response time: 48 hours. We work with data from any sequencing platform, any sample type, any scale.