{"id":18341,"date":"2024-04-25T22:04:56","date_gmt":"2024-04-25T22:04:56","guid":{"rendered":"https:\/\/www.thermofisher.com\/blog\/behindthebench\/?p=18341"},"modified":"2024-04-29T21:39:38","modified_gmt":"2024-04-29T21:39:38","slug":"smart-deep-basecaller-sdb-an-ai-solution-for-improving-sanger-sequencing-basecalling","status":"publish","type":"post","link":"https:\/\/www.thermofisher.com\/blog\/behindthebench\/smart-deep-basecaller-sdb-an-ai-solution-for-improving-sanger-sequencing-basecalling\/","title":{"rendered":"Smart Deep Basecaller (SDB)\u2013 an AI solution for improving Sanger sequencing basecalling"},"content":{"rendered":"

Sequencing using chain-terminating dideoxynucleotides \u2013 also known as Sanger sequencing \u2013 has long been recognized as the standard for DNA sequence determination.\u00a0 The uncomplicated chemistries and workflows, ease of data analysis, and clear results interpretation allow Sanger sequencing to remain an important tool in the biologist\u2019s toolbox, especially when accurately determining a sequence is extremely important.\u00a0 For example, miscalling sequences can lead to a misinterpretation of the underlying biology.\u00a0 In cancer research, it might mean making the wrong assumptions about the nature of the mutation in a tumor, affecting possible intervention choices.\u00a0 In infectious disease research, it might mean misidentifying a pathogenic strain and using an antibiotic that is ineffective against it.\u00a0 In inherited disease research, it could result in the misidentification of the causative mutation for a syndrome.\u00a0 Sanger sequencing gives researchers the confidence that their experimental results in the identification of the underlying mutation is correct, enabling them to further their research on solid foundations.<\/p>\n

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However, in spite of the robustness of Sanger workflows, there are occasionally problems that can complicate the results.\u00a0 For example, if the morphology of a peak is slightly off, base calling software may call the peak incorrectly or not at all.\u00a0 Additionally, background noise from a sequencing reaction can reduce the confidence in read quality.\u00a0 Dye blobs, resulting from incomplete clean-up of sequencing reactions, can also interfere with base calling confidence.\u00a0 Manual examination of suboptimal sequencing traces can overcome these issues, often at a cost of increased time and reduced efficiency for the lab.<\/p>\n

To overcome these problems, the innovators at Applied Biosystems\u2122 took advantage of machine learning and artificial intelligence algorithms to develop a novel Sanger sequencing basecaller solution.\u00a0 A set of algorithms, including deep neural networks, was applied to paired suboptimal traces and ground truth traces to improve basecalling accuracy in Sanger Sequencing traces. \u00a0A large collection of in-house generated, annotated Sanger sequencing datasets was then used to train and test the resulting algorithms.<\/p>\n

These development efforts produced Smart Deep Basecaller\u2122 (SDB).\u00a0 Smart Deep Basecaller, accessible within Sequencing Analysis Software 8.0, takes the output of the Applied Biosystems genetic analyzers and provides improved sequence interpretation, particularly with suboptimal traces.\u00a0 This new solution gives researchers a tool that can give them enhanced confidence in their Sanger sequencing results.<\/p>\n

Increased read lengths<\/em><\/strong><\/p>\n

Researchers are interested in getting the most information from their experiments.\u00a0 The advanced algorithm in SDB allows for greater accuracy in the 5\u2019 and 3\u2019 ends, thus optimizing the number of bases per read.\u00a0 This increase in the number of high quality basecalls at 5\u2019 and 3\u2019 ends of long reads increases the overall read length from a single reaction.\u00a0 In internal tests, SDB increased the Q20 CR length (number of contiguous bases with a QV greater than 20) between 6.2-15.5% relative to KB Basecaller, depending on the instrument and run module used.\u00a0 Another metric used to demonstrate the utility of SDB is aligned clear read length (ACR), which is the number of bases within a region that aligned with a reference sequence with high accuracy.\u00a0 This is a measure of the accuracy of a Sanger read.\u00a0 SDB increased the ACR anywhere from 3.9-12.5% on long reads, relative to the standard KB.\u00a0 These advanced features can produce read lengths of over 1200 bp.<\/p>\n

More accurate pure and mixed base calls<\/em><\/strong><\/p>\n

Another aspect of SDB functionality is that it can read through artifacts such as dye blobs, mobility-shifted peaks, malformed peaks and N-1 peaks.\u00a0 An example is shown in Figure 1.\u00a0 This example electropherogram shows a region that has a dye blob and a couple of flanking malformed peaks.\u00a0 KB\u2122 Basecaller (right) has a problem calling some of the bases co-migrating with the dye blob; five bases are incorrectly called as mixed base with poor quality.\u00a0 SDB is able to recognize the blob anomalies and can make the correct base calls, even in the presence of the anomalous peaks (left).<\/p>\n

Increased accuracy through GC-rich regions<\/em><\/strong>\u00a0<\/em><\/strong><\/p>\n

SDB is able to improve reads through difficult sequences such as homopolymeric regions and GC-rich templates.\u00a0 In internal tests, we analyzed 109 sequencing traces from a template with GC content between 60-75%.\u00a0 SDB was able to extract 8.4% longer ACR length, 10.4% longer Q20 CR length and 28.9% lower ACR error rate than KB.\u00a0 Similar results were seen on homopolymeric A\/T sequences.<\/p>\n

Improved confidence with heterozygous insertion-deletion (het indel) variants<\/em><\/strong><\/p>\n

In many cases, a genomic DNA sample contains a mixture of alleles.\u00a0 SDB can improve the basecalling of single nucleotide variants.\u00a0 Moreover, when analyzing a sequence that is heterozygous for a frameshifting insertion or deletion mutation, SDB\u2019s advanced algorithms can improve the quality value and accuracy of the basecalls (Figure 2).\u00a0 This allowed the researcher to have more confidence in the resulting sequence.<\/p>\n

Enhanced View trace visualization <\/em><\/strong><\/p>\n

Many Sanger sequencing reactions, especially long-reads, have reduced peak morphology (reduced resolution) at the 3\u2019-end of a read.\u00a0 SDB algorithms can accurately call these reduced resolution peaks by improving the baseline and increasing resolution in the 3\u2019 end of plasmid sequences.\u00a0 The results are packaged into an improved electropherogram diagram, facilitating the interpretation of the sequence in this region (Figure 3).<\/p>\n

Reduced manual review time<\/em><\/strong><\/p>\n

When Sanger sequencing reactions produce suboptimal results, the traces and sequences often have to be examined and edited manually, introducing extra time and incurring extra costs. The improvements introduced by SDB have been designed to overcome these suboptimal conditions.\u00a0 The reduced number of low-quality base calls and false positives reduce the amount of manual interpretation needed when the reactions are suboptimal.\u00a0 This eases Sanger sequencing data review, freeing staff time to work on other tasks.<\/p>\n

SDB harness the power of AI-driven advancements to improve the accuracy of Sanger sequencing.\u00a0 Use this power to reveal insights that might have been missed before.<\/p>\n

Learn more about Smart Deep Basecaller today and unlock a world of possibilities in Sanger sequencing.<\/a><\/p>\n

Watch webinar on Testing Applied Biosystems Smart Deep Basecaller for Sanger Sequencing QC<\/a><\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

For Research Use Only. Not for use in diagnostic procedures.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Sequencing using chain-terminating dideoxynucleotides \u2013 also known as Sanger sequencing \u2013 has long been recognized as the standard for DNA sequence determination.\u00a0 The uncomplicated chemistries and workflows, ease of data analysis, and clear results interpretation allow Sanger sequencing to remain an important tool in the biologist\u2019s toolbox, especially when accurately determining a sequence is extremely<\/p>\n","protected":false},"author":120,"featured_media":18345,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","_monsterinsights_skip_tracking":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[172],"tags":[],"division":[],"class_list":{"0":"post-18341","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-general","8":"entry"},"_selected_authors":"","_selected_reviewers":"","acf":[],"yoast_head":"\nSmart 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A standardized workflow combining reliable extraction, concentration and purity assessment, application-appropriate quantification, and consistent laboratory practices can help identify sample issues early, improve reproducibility,\u2026","rel":"","context":"In "General"","block_context":{"text":"General","link":"https:\/\/admin.acceleratingscience.com\/behindthebench\/general\/"},"img":{"alt_text":"Close-up shot of a dna sequence on a screen, a digital representation of genetic code, used for analysis.","src":"https:\/\/i0.wp.com\/admin.acceleratingscience.com\/behindthebench\/wp-content\/uploads\/sites\/9\/2026\/09\/iStock-2212923489_dnasequence-scaled.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/admin.acceleratingscience.com\/behindthebench\/wp-content\/uploads\/sites\/9\/2026\/09\/iStock-2212923489_dnasequence-scaled.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/admin.acceleratingscience.com\/behindthebench\/wp-content\/uploads\/sites\/9\/2026\/09\/iStock-2212923489_dnasequence-scaled.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/admin.acceleratingscience.com\/behindthebench\/wp-content\/uploads\/sites\/9\/2026\/09\/iStock-2212923489_dnasequence-scaled.jpg?resize=700%2C400&ssl=1 2x, https:\/\/i0.wp.com\/admin.acceleratingscience.com\/behindthebench\/wp-content\/uploads\/sites\/9\/2026\/09\/iStock-2212923489_dnasequence-scaled.jpg?resize=1050%2C600&ssl=1 3x, https:\/\/i0.wp.com\/admin.acceleratingscience.com\/behindthebench\/wp-content\/uploads\/sites\/9\/2026\/09\/iStock-2212923489_dnasequence-scaled.jpg?resize=1400%2C800&ssl=1 4x"},"classes":[]},{"id":19345,"url":"https:\/\/www.thermofisher.com\/blog\/behindthebench\/precision-oncology-diagnostics\/","url_meta":{"origin":18341,"position":4},"title":"The Expanding Role of Molecular Diagnostics in Precision Oncology","author":"Behind The Bench Staff","date":"January 13, 2026","format":false,"excerpt":"https:\/\/www.youtube.com\/watch?v=F6FfHIizJBY For Dr. Harald Bartsch, a clinical pathologist in southern Bavaria, molecular diagnostic tools have become an indispensable part of his arsenal. \u201cI believe molecular diagnostics play a crucial role in modern oncology, and I see this as the direction everything is headed,\u201d says Dr. Bartsch. 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