WES / WGS Variant Analysis

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Overview

Variant analysis turns sequencing reads into an interpretable list of genomic changes and, more importantly, into a judgement about which of them matter. We call SNVs, indels, copy number changes and structural variants using established best-practice workflows, annotate them functionally and clinically, and classify them by predicted consequence. Both germline and somatic settings are supported, including tumour–normal paired analysis, tumour mutational burden and mutational signature extraction.

Schematic: raw reads become a quantified matrix, then tested differences, then annotated populations — with the statistics matched to the study design.

Key Advantages

Best-Practice Calling Workflows

Alignment, duplicate marking, recalibration and filtering follow established consortium recommendations, with parameters recorded so the calls can be defended and repeated.

All Variant Classes

SNVs, indels, copy number and structural variants are called together, because restricting analysis to point mutations misses a substantial share of driver events.

Interpretation, Not Only Annotation

Variants are prioritised by predicted functional impact, population frequency, clinical evidence and relevance to your biological question, rather than handed over as a raw annotated file.

Coverage Honestly Reported

Regions with insufficient depth are identified explicitly, so absence of a variant call in a poorly covered region is not mistaken for absence of a variant.

Where This Service Is Used

Identifying candidate causal variants in rare disease or family studies

Somatic mutation profiling of tumour samples with matched or unmatched normals

Calculating tumour mutational burden and extracting mutational signatures

Characterising resistance mutations arising in treated patients or cell models

Verifying the genomic integrity of engineered cell lines or models

Methods and Techniques Applied

Read quality control, alignment, duplicate marking and base quality score recalibration

Germline calling with joint genotyping, and somatic calling with paired or panel-of-normals approaches

Copy number and structural variant detection with purity and ploidy estimation for tumour samples

Functional annotation covering consequence, population frequency, conservation and predicted pathogenicity

Clinical and knowledge base annotation against curated variant resources

Prioritisation and, where requested, mutational signature and tumour mutational burden analysis

What We Need From You

FASTQ, BAM or VCF files with the capture kit or library preparation described

Sample metadata including tumour–normal pairing, tissue type and any known variants

The question: diagnostic candidate search, driver discovery, resistance profiling or quality verification

Species and reference build preference, with any custom regions of interest

What You Receive

Annotated variant files in VCF and tabular form, with all annotation fields documented

Prioritised candidate list with the evidence supporting each variant

Coverage and quality report including regions with insufficient depth

Copy number and structural variant summaries with visualisation

Signature, burden and comparative analyses where they were part of the scope

What We Compute and Report

Variant calls with quality scores, allele fractions and genotype confidence

Functional consequence, population frequency and pathogenicity predictions per variant

Copy number profiles with tumour purity and ploidy estimates where applicable

Coverage statistics with the regions too shallow to support a negative result identified

Mutational signature contributions and tumour mutational burden where in scope

Interpretation and Limitations

Computational predictions prioritise hypotheses; they do not independently establish binding, biological activity, therapeutic efficacy, safety or clinical validity. Performance depends on input quality, target class, the structural evidence available and the applicability domain of the selected methods. Scores used for ranking are comparative devices and should not be read as measured quantities. All deliverables are for research use only and are not intended for diagnostic or therapeutic use.

Specifications

Item	Specification	Notes
Sample types	WES, WGS, panels	Germline and somatic, paired or unpaired
Typical turnaround	2–5 weeks	Whole genome cohorts at the longer end
Cohort size	1–1,000+ samples	Joint calling applied where appropriate
Output	VCF, tables, report	With coverage assessment per sample

Service Workflow

Step 01

Scientific Consultation

We discuss the objective, the decision it supports and the data you hold. Nothing is quoted before we understand what the result has to answer.

Step 02

Feasibility Review

We check that the data, target class and available structural evidence can support the proposed approach, and say plainly where they cannot.

Step 03

Technical Proposal

Scope, methods, deliverables, timeline and price are confirmed in writing, together with the limitations we expect to report.

Step 04

Computation and QC

The analysis runs on pinned tool versions in a containerised environment, with quality checkpoints and method comparison where that is informative.

Step 05

Report and Follow-Up

You receive the ranked results, the documented methods, the limitations and a proposed validation plan, plus support in interpreting them.

Is This the Right Service for You?

Choose this service when

Candidate causal variants must be identified in a rare disease or family study

Somatic profiling is needed with or without matched normals

Mutational burden or signatures are required for a translational question

Consider another service when

Expression rather than genotype is the question

Bulk & Single-Cell RNA-Seq Analysis

A predictive model on clinical variables is the goal

Clinical Prediction Modeling

What Goes Wrong, and How We Handle It

The failure modes that produce confident-looking results which do not survive the next experiment. Each one is designed against rather than discovered afterwards.

Coverage is reported per region, and areas too shallow to support a negative conclusion are identified explicitly.

Case Studies

The situation

A previous analysis reported no plausible causal variant, and the referring clinicians suspected the pipeline.

What the work involved

The data was reprocessed from raw reads with recalibration and joint genotyping, coverage was assessed across the candidate gene panel, and structural and copy number calling was added.

What came back

Three exons of the strongest candidate gene had fallen below callable coverage. Targeted re-analysis revealed a small deletion that the original variant-only pipeline could not have detected.

Illustrative of the shape this work takes. Details are generalised, no client or target is identified, and scope and outcome vary with the system in question.

Questions We Are Asked Before Scoping

Note: ICDMO delivers computational (in silico) services. Results prioritise hypotheses for testing; they do not by themselves establish binding, biological activity, efficacy or safety. All deliverables are for research use only and are not intended for diagnostic or therapeutic use. Downstream experimental work is scoped separately and executed through qualified partners.

Get in Touch
about WES / WGS Variant Analysis

Tell us about the target, the data you hold and the decision the result needs to support. A scientist reviews every enquiry and replies within one business day.

Feasibility reviewed before any scope or price is fixed

Methods, parameters, confidence and limitations in every report

Confidentiality agreement available before data is shared