--- title: LockSeq Bioinformatics Pipeline | Countagen description: "How LockSeq turns sequencing reads into a per-site call: UMI consensus, raw-read confirmation, control comparison and one interactive report." --- [![Logo\_horizontal\_colored logo with black text](https://www.countagen.com/hubfs/Logo_horizontal_colored%20logo%20with%20black%20text.png)](https://www.countagen.com/?hsLang=en) - [Home](https://www.countagen.com?hsLang=en) - [Technology](https://www.countagen.com/technology?hsLang=en) - [Bioinformatics](https://www.countagen.com/bioinformatics) - [Sample Report](https://www.countagen.com/lockseq-sample-report?hsLang=en) - [Resources](https://www.countagen.com/resources?hsLang=en) - [FAQ](https://www.countagen.com/faq?hsLang=en) - [About Us](https://www.countagen.com/about-us?hsLang=en) [REQUEST A QUOTE](https://www.countagen.com/contact?hsLang=en) Bioinformatics # From FASTQ to confident variant calls The LockSeq pipeline checks each variant twice, in raw reads and in UMI consensus reads, then against your untreated control. You get one interactive report with a status for every site in your panel. [Explore the sample report](https://www.countagen.com/lockseq-sample-report?hsLang=en)[Request a quote](https://www.countagen.com/contact?hsLang=en) READS AT ONE SITERaw layerevery read, as sequencedConsensus layerone read per UMI familyCALLConfirmed, treated-associatedIn both layers · absent from the untreated controlEdit, in every readError, in one read 0.1% VAF Standard limit of detection, lower with deeper sequencing 3 reads Minimum UMI family size for a consensus read 1,000 / 30 Raw and consensus reads a site needs to be called 3 platforms Illumina, MGI and Oxford Nanopore, same pipeline The pipeline ## Six modules, from FASTQ to report Every run goes through the same steps, whether the panel has 20 sites or 1,000+, so results compare across panels, sequencers and time. 01 · Read QC ### Clean reads in, run quality on record Trims adapters, filters low-quality reads and writes a quality summary for every sample in the run. 02 · UMI extraction ### Each read keeps its molecule tag Reads the unique molecular identifier off every read and stores it with the read before anything is aligned. 03 · Mapping ### Reads placed on their target site Aligns reads to the reference sequence of each target site on GRCh38, then sorts and indexes the alignments. 04 · Consensus building ### One consensus read per original molecule Groups reads that share a UMI. A family of at least 3 reads becomes one consensus read, so errors that appear in a single read drop out. 05 · Variant annotation Runs on raw and consensus reads ### SNVs and indels, allele by allele Aligns every read at the site against its reference and annotates substitutions, insertions and deletions per allele and per sample. 06 · Comparison & report ### Treated vs control, both layers, one report Checks each variant against both evidence layers and your untreated controls, assigns every site a data status and writes the interactive report. Two layers of evidence ## A variant is confirmed only when both layers agree Raw reads show everything the sequencer saw. Consensus reads keep only what each original molecule carried. A real edit is in every read from a molecule, so it survives consensus building. A PCR or sequencing error sits in one read and doesn't. The pipeline reports the variant frequency from the consensus layer and needs matching evidence in the raw reads before it calls a variant confirmed. Anything that only shows up in one layer stays in the report with its own flag, so you can see it and judge it yourself. | Evidence flag | Consensus | Raw | | --- | --- | --- | | ConfirmedVariant in both layers | ✓ | ✓ | | Raw support below limitRaw evidence matches but sits below the raw reporting threshold | ✓ | ~ | | No raw supportConsensus variant not found in the raw reads | ✓ | – | | Not confirmedRaw-read variant with no consensus evidence | – | ✓ | Checked against your control ## Background variants are kept apart from edits Every genome differs from the reference at millions of positions. So each treated sample is compared with your own untreated control, not only with the reference genome. A variant at a similar frequency in treated and control samples is classed as common background. Only treated-associated variants count as editing signal. LockSeq report · Variant Frequency Overview ![Variant frequency heatmap: three on-target sites at about 70 to 78 percent in the three treated samples and 0 percent in controls; off-target sites show similar low frequencies around 0.5 percent in treated and control samples](https://www.countagen.com/hubfs/LockSeq-report-variant-frequency-heatmap.png) Sample reportThe three on-target sites carry the edit in treated samples only. The off-target rows below show the same low-level background in treated and control samples, so they aren't counted as edits. Synthetic demo data. Allele-level view ## See the alleles behind every number For each site and sample, the report shows the allele mix behind the frequency: which deletions, insertions and substitutions, how often, and from how many consensus reads. Any call can be checked by eye. Both layers have their own allele plots, so you can put the raw and consensus view of the same site side by side. LockSeq report · Consensus allele plot ![Consensus allele plot for one on-target site: reference sequence on top, 29 percent unedited reads, then deletions of 2 to 6 base pairs at the cut site at decreasing frequencies, and one G to T substitution](https://www.countagen.com/hubfs/LockSeq-report-consensus-allele-plot.png) Sample reportOne on-target site in one treated sample: 29% of consensus reads unedited, the rest a mix of deletions at the cut site. Synthetic demo data. Reporting rules ## Every site gets a status. None disappear quietly. The thresholds are the same on every run and printed in every report, so you know exactly why a site was called the way it was. 30consensus reads per site for an interpretable call 1,000raw reads per site for usable raw evidence 3 / Nlower reportable limit, where N is the consensus depth. 3,000 consensus reads gets you to 0.1% VAF. ~80%of sites typically within 80% of the mean read depth, so you don't over-sequence the panel to reach the weakest site Reportable Enough consensus support to report a variant frequency. Raw evidence only Raw reads show evidence, but consensus support is below the reporting guide. Low support Consensus depth below the interpretable threshold. Dropout No usable consensus reads for one or more samples. Probe review A capture or alignment pattern, such as reads from a second locus, flagged for manual review. What you get back ## The report, the data and no extra fees ### Interactive HTML report One self-contained file that opens in any browser. Filter by coverage, compare against controls, open the reads and export tables as CSV. ### FASTQ and BAM files Your raw and aligned data, ready for your own team to reanalyse in-house. ### Analysis included No separate software, analysis or per-run fees. The pipeline is part of the project price. ### 15 business days From the day your DNA arrives in our Solna lab to the delivered report. See it for yourself ## Open a full LockSeq report Click through the sample report, or send us your nominated sites and we'll scope your panel within 24 hours. 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