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CN EN

Variant calling and annotation (WGS / WES / targeted)

For human, animal and plant whole-genome, exome and panel data: family, case–control and tumour–normal designs. We follow GATK Best Practices and write every filter parameter into the report.

Standard analysis

  • QC, alignment (BWA-MEM), duplicate marking and base quality recalibration
  • SNP / InDel calling (GATK HaplotypeCaller, joint calling)
  • Variant QC and filtering (VQSR or hard filters)
  • Annotation (ANNOVAR / VEP: gene, consequence, population frequency, pathogenicity predictions)
  • Variant statistics and plots: distribution, types, Ti/Tv
  • Candidate variant tables by inheritance model or frequency threshold

Optional advanced modules

  • CNV and structural variant detection
  • Family analysis: de novo variants, segregation, runs of homozygosity
  • Somatic variants (Mutect2), tumour mutational burden, mutation spectrum patterns
  • Mitochondrial variants, HLA typing, STR analysis
  • ACMG-style tiering of candidates (research use)

What you send and what comes back

You provideYou receive
fastq or bam filesQC and coverage report
Sample sheet: pedigree, phenotype, pairingVCF plus annotated variant tables (Excel)
Reference genome version (hg38/hg19 or other species)Candidate variant tables and figures
Target bed file (WES / panel)Code, parameters and methods paragraph

Typical turnaround: 7–12 working days for the standard scope; complex designs as stated in the written analysis plan. Quotes are per project, returned within 1 working day.

Sample deliverable (real run on public data)

Read depth along the genome
Read depth along the genome
Variant types and predicted effects
Variant types and predicted effects

Open the full sample report

How many samples are needed for joint calling?

Joint calling works from 2 samples; more samples make low-frequency filtering more stable. Single samples are fine too, and the report explains the difference.

Can the variant tables be used for a clinical report?

Our deliverables are for research use. Clinical interpretation must be done by an accredited laboratory.

Can CNVs be added to existing WES data?

Yes. Exome-based CNV calling is less precise than WGS and the report includes a confidence statement.

Population resequencing / GWAS / evolution

For animal, plant, microbial and human cohorts from resequencing or array data: population structure, selection signals, trait association, domestication and evolutionary history.

Standard analysis

  • Population-level SNP calling and filtering (missing rate, MAF, HWE)
  • Population structure: PCA, ADMIXTURE, phylogenetic tree
  • LD decay, nucleotide diversity (π), Fst, Tajima's D
  • Selective sweep scans (XP-CLR, iHS)
  • GWAS with mixed linear models (GEMMA/GCTA), Manhattan and QQ plots
  • Annotation of significant loci and candidate gene lists

Optional advanced modules

  • Demographic history (PSMC/SMC++, effective population size, divergence times)
  • Gene flow and admixture (TreeMix, D-statistics)
  • Genomic prediction / genomic selection (GBLUP, rrBLUP)
  • Pan-genome and structural variant population analysis
  • eQTL and GWAS co-localisation

What you send and what comes back

You provideYou receive
fastq, bam or VCF filesHigh-quality SNP set (VCF) with statistics
Sample sheet: population, phenotype, geographyPublication-ready figures for structure, selection and GWAS
Reference genome and annotationCandidate region and gene tables

Typical turnaround: 15–25 working days for the standard scope; complex designs as stated in the written analysis plan. Quotes are per project, returned within 1 working day.

No public example is available for this analysis yet. Deliverables follow the same structure as our sample reports (report, figures, tables, code, methods text); the specific figures are listed in the written plan.

How many samples does a GWAS need?

It depends on heritability and effect size; there is no single answer. At the plan stage we state the effect range detectable with your sample size.

Will population structure cause false positives?

Mixed linear models correct for structure and relatedness; the report includes QQ plots and inflation factors as evidence.

Metagenomics and 16S / ITS amplicon analysis

For gut, soil, water, clinical and other microbial community studies. Amplicons suit composition comparisons; shotgun metagenomics suits function and fine taxonomy. We explain the difference at the plan stage.

Standard analysis

  • Amplicons: denoising and ASVs (QIIME2 / DADA2), taxonomy (SILVA / UNITE)
  • Alpha / beta diversity with group tests (PERMANOVA)
  • Composition bar plots, LEfSe differential taxa
  • Shotgun: QC, host removal, assembly (MEGAHIT), gene prediction and non-redundant gene catalogue
  • Taxonomic and functional annotation (Kraken2 / MetaPhlAn, KEGG / CAZy / CARD)
  • Differential functional pathways between groups

Optional advanced modules

  • Metagenome binning and MAG quality assessment
  • Strain-level analysis and SNP tracking
  • Microbe–metabolite or microbe–clinical correlation
  • PICRUSt2 functional prediction (amplicons)
  • Co-occurrence networks and keystone taxa

What you send and what comes back

You provideYou receive
fastq files and primer information (amplicons)ASV / taxon abundance and annotation tables
Sample sheet: groups, sampling time, clinical or environmental variablesPublication-ready diversity, composition and differential figures
Host genome for host removal, if applicableFunctional annotation and pathway difference tables

Typical turnaround: 10–15 working days for the standard scope; complex designs as stated in the written analysis plan. Quotes are per project, returned within 1 working day.

No public example is available for this analysis yet. Deliverables follow the same structure as our sample reports (report, figures, tables, code, methods text); the specific figures are listed in the written plan.

Can 16S resolve species?

16S routinely resolves to genus; species-level labels need caution. For species or strain resolution we recommend shotgun metagenomics and say so in the plan.

Sequencing depth varies a lot between samples.

We rarefy according to the data distribution or use rarefaction-free methods, and include rarefaction curves in the report.

Epigenomics (ChIP-seq / CUT&Tag / ATAC-seq / methylation)

For histone marks, transcription factor binding, chromatin accessibility and DNA methylation (WGBS / RRBS / 850K arrays). The focus is linking epigenetic signal to gene expression and regulatory elements.

Standard analysis

  • QC, alignment, duplicate removal and signal-to-noise assessment (FRiP, fingerprint)
  • Peak calling (MACS2/MACS3) with replicate consistency (IDR)
  • Peak annotation (promoter, enhancer, gene body) and motif enrichment (HOMER)
  • Differential peaks / accessible regions (DiffBind)
  • Methylation: alignment (Bismark), methylation levels, differentially methylated regions
  • IGV tracks, heatmaps and profile plots

Optional advanced modules

  • Integration with RNA-seq: differential peaks versus differential expression
  • Super-enhancer identification
  • Transcription factor footprinting (ATAC-seq)
  • EWAS and epigenetic age from methylation arrays
  • Chromatin-state segmentation across histone marks (ChromHMM)

What you send and what comes back

You provideYou receive
fastq files including input / IgG controls (ChIP)QC and peak-calling statistics
Sample sheet: antibody, treatment, replicatesPeak files (bed / bigWig) and annotation tables
Reference genome versionPublication-ready differential region and motif figures

Typical turnaround: 10–15 working days for the standard scope; complex designs as stated in the written analysis plan. Quotes are per project, returned within 1 working day.

No public example is available for this analysis yet. Deliverables follow the same structure as our sample reports (report, figures, tables, code, methods text); the specific figures are listed in the written plan.

Can ChIP-seq be analysed without an input control?

Peaks can be called, but the false-positive risk rises; the report says so and recommends adding a control.

How do you judge ATAC-seq replicate consistency?

With IDR and inter-replicate correlation, plus per-sample TSS enrichment scores as quality evidence.

Tell us the data type and the question you want answered. You will receive a written analysis plan and quote within 1 working day.

Request an analysis plan