Understand how your samples respond under different conditions. We quantify RNA expression to reveal which genes are active, suppressed, or differentially expressed, giving you insights into biological pathways, disease mechanisms, and treatment effects.

Perfect for understanding cellular responses, validating targets, or exploring functional genomics.

• Bulk RNA-seq: Quantify and classify bulk RNA content by aligning overlapping short reads to the genome using STAR, and count reads aligned to known genes. Compare differential expression between treatment groups using edgeR, following robust statistical methods to deliver meaningful results and generate publication ready data. 

  Related data: Illumina Stranded mRNA, Illumina Total RNA, Small RNA (link to each)

• Single cell RNA-seq: Single-cell RNA sequencing uncovers cellular diversity and rare populations by profiling individual cell gene expression and enabling differential expression analysis between cell communities and conditions. This service transforms biological samples into high-resolution data that advances research across diverse biological applications. 

  Related data:  10X, HIVE, Parse Biosciences

• Proteomics: Quantify relative protein expression levels using highly sensitive proximity extension assays across a variety of curated Olink panels containing biologically meaningful protein targets. Compare treatment groups using popular statistical methods to detect significant population level differences in expression for both high and low abundance proteins. 

  Related data: Olink HT, Olink Reveal, Olink Target

• Methylation: Differential methylation profiling can reveal meaningful insights into epigenetic mechanisms linked to your phenotypes of interest. Our analysis solutions utilise powerful statistical methods to investigate these patterns through annotated CpG sites (using the EPIC and Methylation Screening Arrays), and across the whole genome (EM-Seq, PacBio 5mC). 

  Related data:  Infinium arrays, Enzymatic Whole Genome Methyl-Seq, RRBS, PacBio

Ideal for researchers studying genetic disease, cancer, plant or animal breeding, or evolutionary change.

Discover the genetic differences that drive traits, disease, or performance. Our variant detection services identify SNPs, insertions, deletions, and other mutations across your samples — helping you pinpoint key changes that influence biology or health.

• Somatic SR - WGS/WES ISO17025

• ISO17025 Research uses, SNV, SV, CNV, Annotation, mitochondrial, HLA - SR and LGR

• Pharmacogenomic

• Polygenic Risk Score analysis

• Non-human variant calling

• Sanger Primer Designs

Clinically (ISO15189) accredited services:

• Germline/hereditary SR - ISO15189 clinical accreditation

• Somatic SR - TSO500 ISO15189, gene fusions

At AGRF, we help researchers understand the genetic makeup of individuals and populations. Genomic characterisation involves mapping and analysing the DNA of organisms to reveal their unique genetic features. Population genomic structure examines how genetic variation is distributed across groups, populations, or species, providing insights into ancestry, diversity, and evolution. Together, these analyses support research in fields such as agriculture, conservation, health, and personalised medicine.

• Large genome and transcriptome assembly

• Plasmid/small genome assembly

• Genome annotation

• Transcript isoform assembly

• CRISPR-Cas9 & transgenic changes

• Advanced Genomic Services: such as Hi-C, Micro-C, Omni-C, CUT&RUN, ATAC-seq

• Allegro - Allegro uses a capture based method to amplify genomic regions for variant calling. Analysis method genotypes specific markers.

• Population Genomics - Genotyping by Sequencing (GBS) -> SNP identification; reference-free genotyping. SNP discovery to characterise populations. Analysis method often used to characterise species with low reference genomes and as a low cost alternative to WGS in agricultural projects.

At AGRF, we help researchers explore the communities of microorganisms that live in and around us. Microbiome bioinformatics involves analysing complex microbial data to understand which microbes are present, how they interact, and how they influence health, disease, or the environment. These insights can guide research in medicine, agriculture, ecology, and beyond, unlocking the hidden impact of microbes on our world.

• Gene targeting for taxonomic annotation using 16S, ITS, CO1, or custom primers on request

• Taxonomic and functional characterisation using MetaWGS

• Metagenome contig assemblies through Long-Read

• Functional screening

• Differential abundance analysis

• Overall community structure analysis (alpha/beta diversity)