Genomics & Variant Analysis
WGS paired-end reads become filtered germline VCFs through pinned FASTQ-to-VCF workflows, QC figures, scripts, and a Methods draft [1].
| Category | Details |
|---|---|
| Supported platforms / instruments | Illumina NovaSeq X / 6000 / NextSeq 2000, HiSeq 2500/4000; MGI DNBSEQ-T7 / G400 / G99 when scoped at kickoff; Element Biosciences AVITI and Ultima Genomics UG100 when scoped at kickoff. PacBio Revio and Oxford Nanopore deferred to long-read DNA-seq spoke |
| Input requirements | Paired-end FASTQ (≥2×150 bp typical); ≥30× mean autosomal depth and >95% callability recommended [2]; ≥95% autosomes at ≥15× per Genomics England rare-disease QC [3]. Cohort VQSR: typically ≥30 samples or one high-quality WGS per GATK guidance [4] |
| Reference builds supported | Human GRCh38 primary (GATK resource bundle 4.6); legacy GRCh37/hg19 on request; mouse GRCm39; custom references scoped at kickoff |
| Primary tools (with versions) | BWA-MEM2 2.2.1; GATK 4.6.0.0; Picard 3.2.0; samtools 1.21; bcftools 1.21; mosdepth 0.3.3; Ensembl VEP 112; fastp 0.23.4; FastQC 0.12.1; MultiQC 1.25. DeepVariant 1.8.0 optional |
| Typical turnaround time | 2-4 weeks (single-sample germline); 4-8 weeks (multi-sample cohort with joint genotyping). Confirmed at kickoff |
| Deliverable formats | .bam, .g.vcf.gz, filtered .vcf.gz, annotation .tsv; PDF/SVG figures; HTML QC report; documented bash/R/Python scripts; Methods draft |
| Key cited best-practice reference | Van der Auwera et al. [1], Current Protocols in Bioinformatics; Regier et al. [5], Nature Communications; Rehm et al. [2], npj Genomic Medicine |
| Custom / bespoke analysis | Non-standard inputs, outputs, and methods scoped at kickoff, for example client BAMs, custom references, custom annotation fields, GWAS-ready plink exports, or tumor-normal somatic extensions |
WGS aligns short reads across the full nuclear genome, recalibrates base qualities, and discovers germline SNVs and indels relative to GRCh38, not only coding exons. Unlike WES, WGS covers introns, promoters, and intergenic regions where pathogenic variants can occur [2]. At ~30× mean mapped depth, ~90% of the genome was callable in early benchmarks; callable fraction matters as much as mean depth [6]. Pepkio starts from FASTQs or client BAMs and returns filtered VCFs with coverage QC. The UK 100,000 Genomes Project analyzed 10,478 cancer genomes across 35 tumor types [7]. Custom inputs and deliverables are agreed at kickoff. See the whole-genome sequencing glossary.
WGS is a fit when you need a germline variant catalog across coding and non-coding sequence, more uniform coverage outside capture targets, or SNV/indel discovery with optional CNV/SV add-ons.
| Approach | Best for | Limitations | Approximate cost range |
|---|---|---|---|
| WGS (short-read) | Rare undiagnosed disease, population cohort catalogs, non-coding variant discovery, uniform genome-wide coverage | Higher sequencing cost per sample than WES; repetitive regions remain challenging; storage and compute heavier than exome | Library prep + sequencing + bioinformatics vary by depth, sample count, and joint-calling scope |
| WES (capture) | Coding-region variant discovery at lower per-sample sequencing cost | Gaps in non-coding, mitochondrial, and off-target regions; uneven coverage in low-complexity targets [2] | Lower sequencing cost than WGS; capture kit and target breadth affect sensitivity |
| Targeted gene panel | Known gene sets, high depth for low-VAF mosaicism in specific loci | Limited to panel genes; misses novel loci outside design | Lowest per-sample sequencing cost; panel size drives sensitivity |
Pepkio verifies FASTQ integrity (MD5 checksums), read length, paired-end structure, and read groups (@RG tags) required by GATK [1]. Sample sex, batch, and sequencing center are recorded in sample_manifest.csv; sub-threshold yield is flagged before alignment.
Tools used: md5sum; custom validation scripts
Output: sample_manifest.csv with sample IDs, flowcell/lane, read counts, and QC flags
FastQC assesses per-base quality, adapter content, and duplication; fastp trims adapters and low-quality ends when needed. Libraries with low Q30 yield or extreme adapter contamination are flagged before alignment.
Tools used: FastQC 0.12.1; fastp 0.23.4
Output: fastqc/ reports; fastp.json / fastp.html trim statistics; trimmed FASTQs when trimming is applied
Paired-end reads are aligned to GRCh38 (or agreed build) with BWA-MEM2 (-M for Picard/GATK compatibility; [9]), producing coordinate-sorted BAM. Mapping rate and insert-size distribution are compared against expected ranges.
Tools used: BWA-MEM2 2.2.1; samtools 1.21
Output: {sample}.sorted.bam; alignment summary metrics
PCR and optical duplicates are marked with Picard MarkDuplicates so downstream callers do not double-count clustered molecules [1]. Elevated duplicate rates trigger review of library prep metadata. BAM indices are generated for random access.
Tools used: Picard 3.2.0 MarkDuplicates; samtools 1.21 index
Output: {sample}.dedup.bam and .bai; duplicate metrics table
GATK BaseRecalibrator and ApplyBQSR adjust per-base qualities using known polymorphism sites from the GATK resource bundle [1]. Recalibration reports are inspected for covariate drift across cycles and read groups.
Tools used: GATK 4.6.0.0 BaseRecalibrator; GATK ApplyBQSR
Output: {sample}.recal.bam; recalibration report PDF
mosdepth and Picard CollectWgsMetrics report mean coverage and pct autosomes at ≥15×/≥20×. Callable breadth, not mean depth alone, is reported because ~30× mean depth leaves ~10% of the genome uncalled in benchmarks [6]. Samples below agreed thresholds are flagged before calling.
Tools used: mosdepth 0.3.3; Picard 3.2.0 CollectWgsMetrics
Output: coverage_summary.csv; mosdepth.global.dist.txt; wgs_metrics.txt; coverage histogram and CDF plots
GATK HaplotypeCaller runs in -ERC GVCF mode per sample, emitting gVCF blocks that retain reference confidence across uncalled regions [1]. DeepVariant 1.8.0 is available as an alternative single-sample caller when scoped at kickoff [10]. Ti/Tv ratios and variant counts are checked against expectations for the species and build.
Tools used: GATK 4.6.0.0 HaplotypeCaller
Output: {sample}.g.vcf.gz and .tbi; per-sample variant count summary
For multi-sample projects, gVCFs are imported into GenomicsDB and joint-genotyped with GenotypeGVCFs, rescuing variants weakly supported in individual samples [1]. Single-sample projects skip this step and proceed directly to filtering. GenomicsDB workspace paths and interval lists are documented for reproducibility.
Tools used: GATK 4.6.0.0 GenomicsDBImport; GATK GenotypeGVCFs
Output: {cohort}.joint.vcf.gz; GenomicsDB workspace; sample count and site-level summary
When cohort size supports it, GATK VariantRecalibrator applies VQSR [4]; smaller cohorts use documented hard filters. Filtered and pass-only VCFs are exported with Ti/Tv sanity checks on pass sites.
Tools used: GATK 4.6.0.0 VariantRecalibrator / ApplyVQSR or VariantFiltration; bcftools 1.21
Output: {cohort}.filtered.vcf.gz; {cohort}.pass-only.vcf.gz; VQSR tranche plots or hard-filter summary
Ensembl VEP annotates consequences (for example missense, frameshift, splice region), gene symbols, and population or clinical fields when reference databases are configured for the project [11]. MultiQC aggregates QC metrics across samples. Final scripts, README, Methods draft, and HTML QC report are packaged per agreed retention policy.
Tools used: Ensembl VEP 112; bcftools 1.21; MultiQC 1.25
Output: variant_annotation_master.tsv; MultiQC report; final deliverable bundle with scripts and Methods draft
For germline SNV/indel discovery on GRCh38, Pepkio recommends ~30× mean autosomal depth with >95% callability [2] and ≥95% autosomes at ≥15× where Genomics England-style QC applies [3]. VQSR typically requires at least one WGS or ~30 exomes [4]. Thresholds are confirmed at kickoff.
Yes, with caveats. Low Q30 yield, high adapter content, or mean depth below ~20× reduce callable fraction [6]. Sub-threshold samples are flagged; re-sequencing is discussed before full calling. Partial analysis is possible when re-sequencing is not feasible.
Illumina NovaSeq X, 6000, NextSeq 2000, and HiSeq data use the standard BWA-MEM2 + GATK workflow. MGI DNBSEQ-T7, G400, and G99 FASTQs are processed when scoped at kickoff with adapter/QC validation in the report. Element AVITI and Ultima UG100 FASTQs can be processed when scoped at kickoff. PacBio and Oxford Nanopore WGS are referred to the long-read DNA-seq spoke.
Single-sample germline projects typically complete in 2-4 weeks; multi-sample cohorts with joint genotyping and VQSR typically require 4-8 weeks. Timelines are confirmed at kickoff.
Yes. You retain full ownership of code, scripts, and results. Pepkio delivers commented bash, R, and Python scripts with environment lock files. Jupyter or R Markdown delivery is available on request.
Yes. Checkpoint reviews occur after alignment QC, coverage assessment, and before final delivery. A PhD-level scientific contact leads the project.
Clarification of methods, QC thresholds, and minor figure or table revisions within agreed scope (typically ≤20% of deliverables). Methods and Supplementary drafts are included for analyses we performed; substantial new reviewer requests are scoped separately.
No. Pepkio does not require co-authorship unless explicitly discussed. Acknowledgment of bioinformatics support is standard practice.
Pepkio defaults to GRCh38 with the GATK 4.6 resource bundle [4, 5]. GRCh37/hg19 is supported on request for legacy cohorts with matching annotation builds. Build choice is documented in the Methods draft.
Harmonized pipelines reduce batch-driven call differences [5]. Pepkio stratifies sequencing center, flowcell, and batch in QC reports. Joint genotyping via gVCF aggregation can improve sensitivity for weakly supported variants [1]. Batch-specific correction beyond standard QC is scoped at kickoff when needed.
Somatic tumor-normal WGS is a separately scoped milestone, not the default germline workflow. Matched normals, higher tumor depth, and distinct callers are defined at kickoff.
Yes. Custom work such as client BAMs, custom references, plink exports, pedigree filtering, or CNV/SV integration is scoped at kickoff with milestone pricing.
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