Analyses for Genetic Variation
We offer a range of services to interrogate genetic variation and association with clinical outcomes or phenotype including:
- WGS/WES sequence analysis to call SNPs or mutations
- Copy number variation (CNV) calling and analysis
- Somatic vs germline mutation detection
- GWAS studies
How it works
Novus Genomics offers established, cost-efficient and rapid turnaround analysis services for gene expression data from a range of platforms including bulk RNAseq, array and NanoString, as well as CRISPR knockout data.
For RNAseq data, we offer analyses of not only mRNA but also miRNA and other small RNAs if required.
We are able to receive data in various formats for analysis such as raw FastQ files, aligned BAM/SAM files for Next Generation Sequencing (NGS) data, and raw or normalised (FPKM/TPM) count matrices at gene or transcript level. Platform-specific file formats such as CEL for arrays (e.g. from Affymetrix, Illumina, Agilent) or nCounter (RCC files) for NanoString are also routinely handled.
Gene expression analyses are relevant for a range of applications such as:
- Target identification and validation in drug discovery
- Identification of novel biomarkers or gene signatures associated with drug response or survival
- Profiling of normal vs. diseased tissue
Analyses of this kind are applicable to a very broad range of therapeutic areas including (but not limited to) oncology, cardiovascular and metabolic disease.
Interested in Gene Expression Data Analysis?
Genetic Variation Analysis: What We Offer
Whole exome or whole genome sequencing (WES or WGS) or SNP arrays can be used to profile genetic variation across many sites in the genome simultaneously. However, sequence data is often generated on the scale of terabytes which makes the data challenging to handle, process and analyse.
At Novus, we have workflows and compute resources that can process data generated from most next generation sequencing (NGS) and array-based technologies at scale. Where necessary, we can also leverage cloud computing for high throughput of large data sets.
Our Genetic Variation Services
We offer a range of services to interrogate genetic variation and association with clinical outcomes or phenotype, including:
- WGS/WES sequence analysis to call SNPs or mutations
- Copy number variation (CNV genetics) calling and analysis
- Somatic vs germline mutation detection
- Genome-wide association studies (GWAS) and haplotype analysis to facilitate the discovery and/or typing of SNPs implicated in disease
A typical genetic variation analysis pipeline includes:
- SNP calling (where necessary) and quality control (e.g. filtering low quality calls, low frequency alleles and those that depart from Hardy-Weinberg equilibrium)
- Somatic variation calling and quality control including, for example, evaluation of sequence data, alignment to the genome and sample uniformity
- Unsupervised analysis to detect and attribute, for example, demographic clustering within the data
- Association testing, correcting for population stratification as necessary, e.g. using PLINK
- Computation of a polygenic risk score (PRS) if required
Every time our clients work with us, they benefit from:
- A dedicated analyst, backed by an experienced team, to curate all data and identify the most appropriate statistical approach to take before providing a biological interpretation of results.
- An interactive data analysis report, internally peer-reviewed, including all analysis methods and results.
- Post-report follow ups upon receipt of our data analysis report. We arrange a teleconference so that our lead analyst can talk through the results.
- Access to large capacity computing and secure data storage facilities
We have helped our clients with the following types of projects:
- Identifying genomic loci associated with disease status
- Identifying SNPs associated with poorer drug response and survival
- Assessment of tumour mutational burden and its association with response to immunotherapy and survival
- Associating copy number variants with cancer cell line gene dependency (CNV Genetics)
- Investigating associations between pharmacokinetic data and genetic variation
- Multivariate analysis across RNAseq and SNP/CNV data, alongside efficacy data from over 800 CRISPR screens.
- Association of gene expression or mutations that confer sensitivity to CRISPR gene knockout in cell lines of interest.
We have utilized the Bioinformatics team at Novus Genomics for many of our drug discovery projects, as they provide expertise in the analysis of complex bioinformatic datasets. This includes large scale datasets from public sources as well as internally generated datasets. In many instances, at the start of a project, we have planned our large scale transcriptomic/proteomic studies with the Novus team, to ensure that the data generated would provide the information we need, and that our projects had the highest chance of success. We have been consistently impressed with the rigor of Novus’ work, their communication throughout the projects, and the rapid speed at which they complete their analyses.
