PCR primer design, multiplex PCR, qPCR and amplicon sequencing analysis
Eleven workflows defined in the BTGenZ Master Blueprint, from designing primers for a template to analysing the data that comes back from the bench. Each section states the research problem, the input accepted, the analytical process, the parameters that matter and the output produced.
About the example outputs. Every example output on this site comes from a synthetic acceptance dataset made of software-test fixtures. It does not contain patient samples or experimental biological results, and the figures illustrate what the workflows produce, not biological findings.
Workflow 1
Conventional PCR Assay Design
Blueprint Section 7
Endpoint PCR needs primer pairs that bind the intended template, anneal at compatible temperatures and give an amplicon of a useful size. Checking each candidate by hand is slow, and a primer that also binds elsewhere in the template is easy to miss.
Input
A target template sequence in FASTA format, plus design constraints such as product size range, primer length and melting temperature window.
Analytical process
Validate the template sequence and the design constraints
Generate candidate primer pairs with Primer3
Calculate nearest-neighbour thermodynamics (SantaLucia, 1998) for each oligonucleotide
Screen specificity with BLAST+
Simulate the paired-primer virtual PCR to confirm the expected amplicon
Rank candidates and assign scientific QC statuses
Important scientific parameters
Product size
150 to 300 bp
Primer length
18 to 25 nt
Target Tm
58 to 62 °C
Maximum Tm difference
2 °C
Constraints used in the acceptance run. They are set per project.
Output
Top 5 ranked primer pairs
Nearest-neighbour thermodynamic properties
Virtual PCR amplicon simulation
Scientific PDF report and Excel workbook
Integrity-verified ZIP package
Relationship to other workflows. Its predicted amplicon sizes supply the expected sizes that Gel Electrophoresis Image Analysis (7.3) compares against.
Evidence. Acceptance run: 5 ranked candidate pairs, mean Tm of the top candidates 59.97 °C.
Primer binding map. Five ranked primer pairs placed on a 1,400 bp synthetic template, each with its predicted amplicon size.Primer property comparison. Melting temperatures sit within a narrow band across the five ranked pairs, and amplicon sizes are shown beside them.
Workflow 2
Existing Primer Evaluation & Validation
Blueprint Section 8
Laboratories often hold primer sets from earlier work or publications and need to know whether they suit a new template before ordering reagents or running a plate.
Input
Forward and reverse primer sequences (FASTA, table or manual entry) and the target template sequence.
Analytical process
Validate the submitted primer sequences and the template
Calculate melting temperature and GC content
Evaluate hairpin and dimer free energy (ΔG)
Map each primer to its binding sites on the template
Simulate virtual PCR to predict product sizes
Assess the result in a multi-tier QC evaluation
Important scientific parameters
Thermodynamics
Hairpin and dimer ΔG
Binding
Target binding topology
Product
Virtual PCR sizing
Output
Thermodynamic hairpin and dimer ΔG
Target binding topology mapping
Virtual PCR sizing simulation
Multi-tier QC evaluation
Scientific PDF report and Excel workbook
Relationship to other workflows. Uses the same nearest-neighbour thermodynamic model as the design workflows, so existing and newly designed primers are judged on a common basis.
Evidence. Acceptance run: 2 submitted primers evaluated against the template.
Workflow 3
SNP / Mutation-Specific PCR Design
Blueprint Section 9
Telling a reference allele from a variant by PCR depends on how the 3′ end of the primer behaves at the mismatch. Primers that look specific on paper can still amplify both alleles.
Input
Reference and alternate allele sequences (FASTA) and a variant definition giving the position and the two alleles.
Analytical process
Read the reference allele, the alternate allele and the variant definition
Design allele-specific forward and reverse primers
Introduce a penultimate artificial mismatch to sharpen discrimination
Model ΔTm discrimination between the two alleles
Evaluate non-specific cross-amplification
Important scientific parameters
Variant position
1-based coordinate
Alleles
Reference and alternate nucleotide
Mismatch design
3′-terminal and penultimate
Acceptance run: a single-nucleotide variant at position 650 (A to C) on a synthetic template.
Output
Allele-specific forward and reverse primers
Penultimate artificial mismatch discrimination
ΔTm discrimination modelling
Evaluation of non-specific cross-amplification
Scientific PDF report and Excel workbook
Relationship to other workflows. Stands alone, and its primers can be checked with Existing Primer Evaluation (2) or combined into a panel through Multiplex PCR Optimisation (4).
Evidence. Acceptance run: 10 allele-specific candidates designed and tested for discrimination.
Workflow 4
Multiplex PCR Optimisation
Blueprint Section 10
In a multiplex reaction every primer meets every other primer. A set that works as single-plex pairs can fail through cross-dimers, unequal annealing temperatures or amplicons that cannot be told apart on a gel.
Input
Several target sequences and either candidate primers or a multiplex panel definition (FASTA and table).
Analytical process
Validate the distinct targets
Generate candidate pairs for every target
Profile thermodynamics for each oligonucleotide
Build the pairwise heterodimer matrix and screen cross-dimers
Harmonise melting temperatures across the panel
Require amplicon size separation, then screen cross-target specificity by virtual PCR
Optimise combinations and rank the non-interfering sets
Important scientific parameters
Tm harmonisation
Span of 3.0 °C or less
Amplicon separation
At least 30 bp apart
Cross-dimer screen
Pairwise ΔG at 37 °C (N × N)
Search limit
Combinatorial sets pruned at 500 permutations
Output
Pairwise heterodimer matrix (N × N)
Tm harmonisation table
Amplicon gel separation sizing model
Optimised non-interfering multiplex primer set
Scientific PDF report and Excel workbook
Relationship to other workflows. A virtual gel of the chosen set can be compared with a real gel through Gel Electrophoresis Image Analysis (7.3).
Evidence. Acceptance run: 3 targets, 15 candidate pairs, 30 oligonucleotides profiled, 125 combinations considered and 10 ranked sets reported.
Cross-dimer heatmap. Pairwise duplex ΔG (kcal/mol, 37 °C) between the six primers of a three-target panel. Less negative values mean weaker unwanted pairing.Workflow 5
qPCR / RT-qPCR Assay Design
Blueprint Section 11
A real-time assay has to amplify the right transcript, avoid genomic DNA signal and, for probe chemistry, carry a probe that binds at a compatible temperature.
Input
A transcript or cDNA template sequence (FASTA) and the assay chemistry, dye-based or hydrolysis probe.
Analytical process
Validate the transcript template
Design primer pairs and, where requested, a dual-labelled hydrolysis probe
Assess exon-junction spanning and genomic DNA discrimination
Harmonise probe Tm relative to the primers
Report the assay with its binding positions
Important scientific parameters
Chemistry
Intercalating dye or hydrolysis probe
Probe Tm
8 to 10 °C above the primers
Template
Transcript or cDNA, for exon-aware analysis
Fluorophore and quencher choice must match the optical channels of the instrument.
Output
Dual-labelled hydrolysis probe (TaqMan) design
Intercalating dye or probe primer pairs
Exon-junction spanning and gDNA discrimination
Probe Tm harmonisation
Scientific PDF report and Excel workbook
Relationship to other workflows. The same assay logic feeds qPCR Experimental-Data Analysis (7.2) once a plate has been run.
Evidence. Acceptance run: dye-based chemistry, 5 candidate assays, with a 121 bp amplicon shown in the binding map.
qPCR assay binding map. Forward and reverse primers with their melting temperatures and the 121 bp amplicon they define on the transcript.Workflow 6
Targeted Amplicon & Sequencing Design
Blueprint Section 12
Sequencing a set of genomic regions needs overlapping amplicons that cover each region, are split into pools that do not interfere, and fit the read length of the sequencing platform.
Input
Reference sequence and target regions as a BED file or CSV table (both coordinate conventions appear in practice).
Analytical process
Validate regions and coordinates
Check the sequencing platform constraints
Tile overlapping amplicons across each region
Segregate amplicons into two pools
Calculate interval coverage and check platform adapter compatibility
Simulate virtual PCR on the template
Important scientific parameters
Coverage
Percentage of target intervals covered
Pools
Dual-pool segregation
Regions
BED (0-based) or CSV (1-based)
Platform read length limits the tiled amplicon window.
Output
Tiled overlapping amplicon panel
Dual-pool segregation matrix (Pool 1 and Pool 2)
Target region interval coverage percentage
Platform adapter compatibility check
Scientific PDF report and Excel workbook
Relationship to other workflows. Its amplicons define the reference and primers that Amplicon Sequencing Analysis (7.1) uses on real reads.
Evidence. Acceptance run: 3 target regions covered by 6 amplicons, 87.65% interval coverage.
Targeted amplicon coverage map. Three target regions on the reference with six tiled amplicons arranged in two pools.Module 7.1
Amplicon Sequencing Analysis
Blueprint Section 16
Paired-end amplicon reads must be cleaned, aligned and turned into coverage and variant evidence, with each variant call carrying an honest confidence level.
Input
Paired-end FASTQ reads (R1 and R2), a reference sequence or amplicon definition, primer sequences and sample metadata.
Analytical process
Validate the FASTQ files
Trim by quality (Mott's algorithm) and remove primer sequence
Align reads with overlap-aware (Bayesian) recalibration
Calculate per-base coverage and depth
Call variants in three confidence tiers and write a VCF table
Important scientific parameters
Read format
Paired-end, Phred+33
Read length
2 × 150 in the acceptance run
Variant calls
Three-tier confidence
Output
Quality and primer-trimmed reads
Overlap-recalibrated alignment
Amplicon coverage distribution and depth
Three-tier variant calls and VCF table
Multi-sheet Excel workbook and scientific PDF report
Relationship to other workflows. Takes its reference and primers from the design workflows, in particular Targeted Amplicon & Sequencing Design (6).
Evidence. Acceptance run: 240 reads processed, with coverage tables and a variant evidence table produced.
Module 7.2
qPCR Experimental-Data Analysis
Blueprint Section 17
Raw Ct values need replicate quality control and a defined quantification method before they can be compared between samples.
Input
A multi-well Ct export from the instrument, with a designated control sample and reference gene.
Analytical process
Ingest the instrument export (CFX, SDS and LightCycler formats are supported)
Extract Cq values and summarise replicates
Flag outliers with a two-sided Grubbs' test (α = 0.05)
Quantify by Livak (2^-ΔΔCt) or Pfaffl relative methods
Resolve melting-curve derivative peaks where melt data are supplied
Important scientific parameters
Method
Livak 2^-ΔΔCt, Pfaffl
Outlier test
Two-sided Grubbs, α = 0.05
Design
Target gene against reference gene and control sample
Standard-curve validation is separate from the ΔΔCt calculation, and equal efficiency is assumed unless it has been validated independently.
Output
Multi-instrument format ingestion
Livak and Pfaffl relative quantification
Grubbs outlier QC flags
Melting-curve peak resolution
Five-sheet Excel workbook and scientific PDF report
Relationship to other workflows. Closes the loop with qPCR / RT-qPCR Assay Design (5): the assay is designed first, then the plate is analysed here.
Evidence. Acceptance run: 24 wells analysed and 6 fold-change values computed for one target gene against GAPDH.
Relative expression. Fold change of the target gene against GAPDH for three control and three treatment samples, with 95% confidence intervals (synthetic Ct values).Replicate precision. Mean Ct with replicate spread for the target and reference gene in every sample.
Module 7.3
Gel Electrophoresis Image Analysis
Blueprint Section 18
A gel image is a qualitative picture until the lanes, bands and ladder are measured. Sizing bands against a ladder turns it into a number that can be compared with the expected amplicon.
Input
A 2D raster gel image (TIFF, PNG or JPEG) and a lane configuration naming the ladder lane, its fragment sizes and the expected bands.
Analytical process
Detect lane boundaries and extract intensity profiles
Fit Gaussian peaks and quantify bands by densitometry
Build a semi-log ladder mobility curve
Estimate fragment sizes and compare them with the expected sizes
Produce an annotated 300 DPI gel figure
Important scientific parameters
Ladder
100 to 1,000 bp in 100 bp steps
Calibration
log10(bp) against relative migration
Requirement
A visible molecular weight ladder
Output
Lane boundary and profile detection
Gaussian peak fitting and densitometric quantification
Semi-log ladder mobility curve
Observed versus expected amplicon size concordance
Annotated 300 DPI gel figure and scientific PDF report
Relationship to other workflows. Takes expected amplicon sizes from Conventional PCR Assay Design (1), which makes it the one analysis workflow with a stated dependency on a design workflow.
Evidence. Acceptance run: 4 lanes and 12 bands detected, with a ladder calibration fit of R² = 0.9913.
Ladder calibration. Ten ladder bands from 100 to 1,000 bp fitted with a semi-log line (R² = 0.9913), used to size every other band on the gel.Lane densitometry. Baseline-corrected intensity profiles for the four lanes. The ladder lane shows ten resolved peaks.
Module 7.4
Sanger Sequencing Analysis
Blueprint Section 19
A Sanger trace has to be read as signal, not just as text. Quality trimming, alignment and mixed-peak detection decide whether a base call or a variant can be trusted.
Input
A capillary trace file (SCF or AB1), a reference sequence and run metadata.
Analytical process
Extract the four-channel electropherogram
Trim by Phred quality with a sliding window (Mott's algorithm)
Align the trimmed read to the reference (semi-global)
Detect heterozygous mixed peaks and write IUPAC base calls
Important scientific parameters
Input trace
SCF or AB1
Trimming
Sliding-window Phred quality
Alignment
Pairwise semi-global against reference
Variant calling needs a reference sequence.
Output
Four-channel electropherogram extraction
Quality-trimmed consensus
Reference alignment
Mixed-peak detection with IUPAC base calls
Multi-sheet Excel workbook and scientific PDF report
Relationship to other workflows. Confirms sequences produced by the design workflows, for example the amplicons that Conventional PCR Assay Design (1) predicts.
Evidence. Acceptance run: a forward read trimmed to 230 bases and aligned across its full length.
Chromatogram and base quality. Four-channel trace with base calls and a per-base Phred quality panel. The shaded region at the 5′ end is trimmed.Module 7.5
Digital PCR Analysis
Blueprint Section 20
Digital PCR counts partitions, so quantification depends on classifying every partition correctly and on propagating uncertainty into the final concentration.
Input
A two-channel partition amplitude export (raw amplitudes per partition) and a configuration describing controls, replicates and expected clusters.
Analytical process
Cluster partitions with plateau-midpoint Otsu thresholding and K-means
Classify positive and negative partitions in each channel
Quantify absolute concentration by Poisson statistics with Clopper-Pearson 95% intervals
Pool replicates (equal or inverse-variance weighting)
Calculate copy number variation with delta-method uncertainty where configured
Screen preliminary LoB and LoD
Important scientific parameters
Partitions per well
2,400 in the acceptance run
Clusters
Double-negative, Ch1+, Ch2+, double-positive
Uncertainty
Clopper-Pearson 95% intervals
The Poisson model assumes random distribution across uniform partitions.
Output
Partition clustering
Poisson absolute quantification with confidence intervals
Volume-aware replicate pooling
CNV with delta-method uncertainty
Multi-sheet Excel workbook and scientific PDF report
Relationship to other workflows. Independent of the design workflows, and complements qPCR Experimental-Data Analysis (7.2) when absolute counts are needed.
Evidence. Acceptance run: 6 wells analysed in 4 replicate groups, with four partition clusters resolved.
Two-channel amplitude plot. Each dot is a partition. Four clusters (double-negative, Ch1+, Ch2+, double-positive) are separated by thresholds.Amplitude distribution. Channel 1 amplitude with the chosen threshold and the shaded rain zone around it.
Next step
See how the workflows were tested, and how scientific QC outcomes are kept separate from software execution.
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