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Journal articles on the topic 'Somatic variant calling'

Author: Grafiati

Published: 4 June 2025

Last updated: 15 July 2025

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1

Shem-Tov, Doron, Maya Levy, Gil Hornung, et al. "Abstract 4926: Advancements in somatic variant calling from UG100 whole genome and whole exome sequencing data." Cancer Research 84, no. 6_Supplement (2024): 4926. http://dx.doi.org/10.1158/1538-7445.am2024-4926.

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Abstract Somatic variant calling involves the identification of genomic alterations that occur in somatic cells, requiring deep coverage to enable high sensitivity for low-frequency variants. Characterizing somatic variants across the entire genome therefore benefits from novel cost-efficient sequencing platforms, such as UG100. Here, we present optimization of variant calling tools for short and structural variants on WGS and WES data from UG100. For calling short variants, we optimized DeepVariant (DV) for somatic calling using data from matched tumor-normal sample pairs, improving both vari

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Levy, Maya, Doron Shem-Tov, Hila Benjamin, et al. "Abstract 3134: Calling somatic variants from UG100 data using deep learning." Cancer Research 83, no. 7_Supplement (2023): 3134. http://dx.doi.org/10.1158/1538-7445.am2023-3134.

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Abstract UG100 is a novel next-generation sequencing platform that combines high throughput with significantly lower sequencing cost. Previous studies have demonstrated broad applicability of UG100 data for whole-genome germline variant calling, single cell transcriptomics and whole-genome methylation analysis, as well as for recalling cancer signatures from cfDNA at very low fraction of circulating tumor DNA. Somatic variant calling is a natural application for this platform as it can benefit from lower sequencing cost to enable deeper sequencing coverage. Here, we describe the implementation

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Chowdhury, Murad, Brent S. Pedersen, Fritz J. Sedlazeck, Aaron R. Quinlan, and Ryan M. Layer. "Searching thousands of genomes to classify somatic and novel structural variants using STIX." Nature Methods 19, no. 4 (2022): 445–48. http://dx.doi.org/10.1038/s41592-022-01423-4.

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AbstractStructural variants are associated with cancers and developmental disorders, but challenges with estimating population frequency remain a barrier to prioritizing mutations over inherited variants. In particular, variability in variant calling heuristics and filtering limits the use of current structural variant catalogs. We present STIX, a method that, instead of relying on variant calls, indexes and searches the raw alignments from thousands of samples to enable more comprehensive allele frequency estimation.

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Huang, Weitai, Yu Amanda Guo, Karthik Muthukumar, Probhonjon Baruah, Mei Mei Chang, and Anders Jacobsen Skanderup. "SMuRF: portable and accurate ensemble prediction of somatic mutations." Bioinformatics 35, no. 17 (2019): 3157–59. http://dx.doi.org/10.1093/bioinformatics/btz018.

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Abstract Summary Somatic Mutation calling method using a Random Forest (SMuRF) integrates predictions and auxiliary features from multiple somatic mutation callers using a supervised machine learning approach. SMuRF is trained on community-curated matched tumor and normal whole genome sequencing data. SMuRF predicts both SNVs and indels with high accuracy in genome or exome-level sequencing data. Furthermore, the method is robust across multiple tested cancer types and predicts low allele frequency variants with high accuracy. In contrast to existing ensemble-based somatic mutation calling app

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Ura, Hiroki, Sumihito Togi, and Yo Niida. "Dual Deep Sequencing Improves the Accuracy of Low-Frequency Somatic Mutation Detection in Cancer Gene Panel Testing." International Journal of Molecular Sciences 21, no. 10 (2020): 3530. http://dx.doi.org/10.3390/ijms21103530.

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Cancer gene panel testing requires accurate detection of somatic mosaic mutations, as the test sample consists of a mixture of cancer cells and normal cells; each minor clone in the tumor also has different somatic mutations. Several studies have shown that the different types of software used for variant calling for next generation sequencing (NGS) can detect low-frequency somatic mutations. However, the accuracy of these somatic variant callers is unknown. We performed cancer gene panel testing in duplicate experiments using three different high-fidelity DNA polymerases in pre-capture amplif

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Bennett, Mark F., Michael S. Hildebrand, Sayaka Kayumi, et al. "Evidence for a Dual-Pathway, 2-Hit Genetic Model for Focal Cortical Dysplasia and Epilepsy." Neurology Genetics 8, no. 1 (2022): e0652. http://dx.doi.org/10.1212/nxg.0000000000000652.

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Background and ObjectivesThe 2-hit model of genetic disease is well established in cancer, yet has only recently been reported to cause brain malformations associated with epilepsy. Pathogenic germline and somatic variants in genes in the mechanistic target of rapamycin (mTOR) pathway have been implicated in several malformations of cortical development. We investigated the 2-hit model by performing genetic analysis and searching for germline and somatic variants in genes in the mTOR and related pathways.MethodsWe searched for germline and somatic pathogenic variants in 2 brothers with drug-re

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Smith, Kyle S., Vinod K. Yadav, Shanshan Pei, Daniel A. Pollyea, Craig T. Jordan, and Subhajyoti De. "SomVarIUS: somatic variant identification from unpaired tissue samples." Bioinformatics 32, no. 6 (2015): 808–13. http://dx.doi.org/10.1093/bioinformatics/btv685.

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Abstract Motivation: Somatic variant calling typically requires paired tumor-normal tissue samples. Yet, paired normal tissues are not always available in clinical settings or for archival samples. Results: We present SomVarIUS, a computational method for detecting somatic variants using high throughput sequencing data from unpaired tissue samples. We evaluate the performance of the method using genomic data from synthetic and real tumor samples. SomVarIUS identifies somatic variants in exome-seq data of ∼150 × coverage with at least 67.7% precision and 64.6% recall rates, when compared with p

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Valecha, Monica, and David Posada. "Somatic variant calling from single-cell DNA sequencing data." Computational and Structural Biotechnology Journal 20 (2022): 2978–85. http://dx.doi.org/10.1016/j.csbj.2022.06.013.

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Hutter, Stephan, Niroshan Nadarajah, Manja Meggendorfer, Wolfgang Kern, Torsten Haferlach, and Claudia Haferlach. "Whole Genome Sequencing in Routine Hematologic Samples: How to Proceed Analyses Best When Germline Controls Are Missing?" Blood 132, Supplement 1 (2018): 5275. http://dx.doi.org/10.1182/blood-2018-99-113294.

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Abstract Background: The human genome is very heterogeneous on the individual level which challenges interpretation of whole genome sequencing (WGS) data. In order to reduce complexity in tumor genetics WGS of a tumor is performed together with WGS of "normal" tissue from the respective patient (i.e. fingernails, skin biopsy, hair, buccal swaps) which is used as the germline sequence (tumor/matched normal approach, TMNA). This approach allows the extraction of somatic mutations acquired in the tumor through sophisticated algorithms. In routine diagnostics, especially in hematological neoplasms

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Zhang, Peng, Kai Wang, Ming Yao, et al. "Accurate prediction of somatic variants using deep learning model." Journal of Clinical Oncology 38, no. 15_suppl (2020): e13659-e13659. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e13659.

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e13659 Background: Efficient and accurate identification of somatic variant is important for understanding the formation, progression, and treatment of cancer. It is necessary to conduct manual review by Integrative Genomic Viewer (IGV) in traditional variant calling process. However, the traditional manual is heavy workload when evaluating tumor with a high variant burden. In this study, a new convolutional neural network (CNN) method was created to train models for somatic mutation identification, which was suitable for Panel sequencing platform with different tumor purities. Methods: A tota

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Arnaud, Pauline, Hélène Morel, Olivier Milleron, et al. "Unsuspected somatic mosaicism for FBN1 gene contributes to Marfan syndrome." Genetics in Medicine 23, no. 5 (2021): 865–71. http://dx.doi.org/10.1038/s41436-020-01078-6.

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Abstract Purpose Individuals with mosaic pathogenic variants in the FBN1 gene are mainly described in the course of familial screening. In the literature, almost all these mosaic individuals are asymptomatic. In this study, we report the experience of our team on more than 5,000 Marfan syndrome (MFS) probands. Methods Next-generation sequencing (NGS) capture technology allowed us to identify five cases of MFS probands who harbored a mosaic pathogenic variant in the FBN1 gene. Results These five sporadic mosaic probands displayed classical features usually seen in Marfan syndrome. Combined with

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Yaung, Stephanie J., Jian Li, Adeline Pek, Lili Niu, John F. Palma, and Maximilian Schmid. "Evaluation of a regularly updated knowledge base for curation of somatic mutations detected in whole exomes of melanoma and lung, colorectal, and breast cancers." Journal of Clinical Oncology 38, no. 15_suppl (2020): e14072-e14072. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e14072.

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e14072 Background: Evolving medical guidelines and complex multi-variant data from next-generation sequencing (NGS) testing of cancer samples make routine clinical interpretation of somatic variants challenging. We assessed the ability of NAVIFY(R) Mutation Profiler*, a CE-IVD somatic variant interpretation tool, to yield accurate time- and geography-specific clinical content on 2511 samples from The Cancer Genome Atlas (TCGA) across six solid tumor types. Methods: Whole exomes from lung adenocarcinoma (n = 469), lung squamous cell carcinoma (n = 325), colon adenocarcinoma (n = 368), rectum ad

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Choi, Ji Won, Kwangsung Ahn, Sangsoo Kim, Dong-Il Park, and Soo-kyung Park. "Abstract 6253: RNA-seq based somatic variant calling and gene expression analysis reveals tumor heterogeneity and metastatic potential in colorectal cancers." Cancer Research 82, no. 12_Supplement (2022): 6253. http://dx.doi.org/10.1158/1538-7445.am2022-6253.

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Abstract Colorectal cancer (CRC) is the third common malignant tumor and the second most responsible for worldwide cancer deaths. Also, RNAseq technology has been used for two purposes: to find exonic regions on the genome and quantify the expression level of the gene. We tried to validate the pipeline for identifying somatic variants from RNA-seq data, mainly following GATK4 somatic calling pipelines with some optimizing modifications. It is intended to examine whether somatic mutations driven from RNAseq data are associated with the biological behaviors of the individual colorectal cancer ce

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Jiang, Liqun, Xijun Zhang, Camille Alba, et al. "Abstract 211: The performance characteristic of the low input tagmentation-based whole genome sequencing in high quality somatic variant calling." Cancer Research 83, no. 7_Supplement (2023): 211. http://dx.doi.org/10.1158/1538-7445.am2023-211.

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Abstract Whole genome sequencing (WGS) is widely used for cancer diagnostic and therapeutic applications in clinical practice and clinical trials. Currently, the Truseq PCR-free library preparation methods are routinely used in genomics laboratories. However, microgram amounts of DNA input is a limitation due to limited materials often from clinically-derived specimens. Here, we evaluated a novel low input (100-300 ng) PCR-free tagmentation (TAG) based library preparation for WGS. Replicates of TAG- and ligation-based (Illumina TruSeq) sequencing libraries were prepared from 3 pairs of breast

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Peculis, Raitis, Vita Rovite, Kaspars Megnis, et al. "Whole exome sequencing reveals novel risk genes of pituitary neuroendocrine tumors." PLOS ONE 17, no. 8 (2022): e0265306. http://dx.doi.org/10.1371/journal.pone.0265306.

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Somatic genetic alterations in pituitary neuroendocrine tumors (PitNET) tissues have been identified in several studies, but detection of overlapping somatic PitNET candidate genes is rare. We sequenced and by employing multiple data analysis methods studied the exomes of 15 PitNET patients to improve discovery of novel factors involved in PitNET development. PitNET patients were recruited to the study before PitNET removal surgery. For each patient, two samples for DNA extraction were acquired: venous blood and PitNET tissue. Exome sequencing was performed using Illumina NexSeq 500 sequencer

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Huang, Xiu, Ruobai Sun, Pablo Cingolani, et al. "Strategy for sensitive and specific somatic SNV/InDel calling: Leveraging different callers with in-house generated gold standard variant sets." Journal of Clinical Oncology 35, no. 15_suppl (2017): e13104-e13104. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e13104.

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e13104 Background: Somatic mutation calling is critical for cancer genotyping. Although rapid development of mutation detection is witnessed with the maturity of NGS, the need for high sensitivity often results in compromised specificity and manual inspection. Here, we propose a methodology that leverages different variant callers to account for specificity without compromising sensitivity. Methods: We designed a cohort of training samples (n = 22), each with known set of SNVs/InDels that were discovered by KEW CANCERPLEX platform. We assessed the performance of four prevailing mutation caller

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Yoo, Byunggil, Erin Guest, and Midhat S. Farooqi. "Abstract LB329: Pathway-based analysis of genomic alterations in infant ALL." Cancer Research 85, no. 8_Supplement_2 (2025): LB329. https://doi.org/10.1158/1538-7445.am2025-lb329.

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Abstract Introduction: Infant acute lymphoblastic leukemia (ALL) is an aggressive subtype, characterized by early onset and poor clinical outcomes, with about 70% of cases involving KMT2A gene rearrangements (KMT2A-r). This study investigates whether pathway-specific genomic alterations influence prognosis by analyzing sequence variants in infant ALL patients from the Children’s Oncology Group trial AALL0631. Methods: We conducted WGS and WES on DNA extracted from peripheral blood or bone marrow from 48 infant ALL patients across three cohorts at diagnosis and at remission. The three infant AL

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Vats, Pankaj, Ankit Sethia, Mehrzad Samadi, and Timothy T. Harkins. "Abstract 1900: Rapid variant detection and annotations from next generation sequencing data using a GPU accelerated framework." Cancer Research 82, no. 12_Supplement (2022): 1900. http://dx.doi.org/10.1158/1538-7445.am2022-1900.

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Abstract Introduction Next Generation Sequencing (NGS) played a crucial role in revolutionizing the field of human genetics to become an integral part of research and clinical management. Some examples are diagnosis and treatment of cancer patients, identifying syndromes in the NICU (Neonatal Intensive Care Units), insights into neuro-degenerative disease to name a few. NGS integrated with multi-omics data provides greater insight to underlying molecular mechanisms and helps to identify alterations specific to the disease condition. Accurate and robust detection of somatic and germline genomic

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Saunders, Christopher T., Wendy S. W. Wong, Sajani Swamy, Jennifer Becq, Lisa J. Murray, and R. Keira Cheetham. "Strelka: accurate somatic small-variant calling from sequenced tumor–normal sample pairs." Bioinformatics 28, no. 14 (2012): 1811–17. http://dx.doi.org/10.1093/bioinformatics/bts271.

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Razavi, Pedram, Bob T. Li, Chenlu Hou, et al. "Cell-free DNA (cfDNA) mutations from clonal hematopoiesis: Implications for interpretation of liquid biopsy tests." Journal of Clinical Oncology 35, no. 15_suppl (2017): 11526. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.11526.

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11526 Background: A large fraction of cfDNA fragments are derived from hematopoietic sources. Somatic alterations in cfDNA can be tumor-derived but also could represent somatic changes associated with clonal hematopoiesis. We performed deep sequencing of both plasma cfDNA and matched white blood cell (WBC) genomic DNA (gDNA) to determine the contribution of clonal hematopoiesis to the variants observed in cfDNA. Four cohorts were investigated: metastatic breast (BC), non-small cell lung (NSCLC), castration-resistant prostate cancer (CRPC), and non-cancer participants (pts). Methods: Metastatic

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Atzeni, Rossano, Matteo Massidda, Enrico Pieroni, Vincenzo Rallo, Massimo Pisu, and Andrea Angius. "A Novel Affordable and Reliable Framework for Accurate Detection and Comprehensive Analysis of Somatic Mutations in Cancer." International Journal of Molecular Sciences 25, no. 15 (2024): 8044. http://dx.doi.org/10.3390/ijms25158044.

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Accurate detection and analysis of somatic variants in cancer involve multiple third-party tools with complex dependencies and configurations, leading to laborious, error-prone, and time-consuming data conversions. This approach lacks accuracy, reproducibility, and portability, limiting clinical application. Musta was developed to address these issues as an end-to-end pipeline for detecting, classifying, and interpreting cancer mutations. Musta is based on a Python command-line tool designed to manage tumor-normal samples for precise somatic mutation analysis. The core is a Snakemake-based wor

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Metzger, Patrick, Maria Elena Hess, Andreas Blaumeiser, et al. "MIRACUM-Pipe: An Adaptable Pipeline for Next-Generation Sequencing Analysis, Reporting, and Visualization for Clinical Decision Making." Cancers 15, no. 13 (2023): 3456. http://dx.doi.org/10.3390/cancers15133456.

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(1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge of both bioinformatics and oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses and annotation of NGS data including quality control, alignment, variant calling, copy number variation estimation, evaluation of complex biomarkers, and RNA fusion detection. (3) Results: MIRACUM-Pipe offers

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Bodini, Margherita, Chiara Ronchini, Luciano Giacò, et al. "The hidden genomic landscape of acute myeloid leukemia: subclonal structure revealed by undetected mutations." Blood 125, no. 4 (2015): 600–605. http://dx.doi.org/10.1182/blood-2014-05-576157.

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Abstract The analyses carried out using 2 different bioinformatics pipelines (SomaticSniper and MuTect) on the same set of genomic data from 133 acute myeloid leukemia (AML) patients, sequenced inside the Cancer Genome Atlas project, gave discrepant results. We subsequently tested these 2 variant-calling pipelines on 20 leukemia samples from our series (19 primary AMLs and 1 secondary AML). By validating many of the predicted somatic variants (variant allele frequencies ranging from 100% to 5%), we observed significantly different calling efficiencies. In particular, despite relatively high sp

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Kueffner, Robert, Hui Li, Kakit Cheung, et al. "VONC: A solution for the clinical assessment of somatic genomic alterations." Journal of Clinical Oncology 37, no. 15_suppl (2019): e13155-e13155. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e13155.

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e13155 Background: Next generation sequencing (NGS) technology is transforming the diagnosis and treatment of cancer. However, the massive scale of data has overwhelmed pathologists who need streamlined tools to process this data, automate report generation and minimize human errors. Methods: We developed the Variant interpretation station for ONCology, VONC, as an end-to-end solution for moving from NGS whole exome and transcriptome data to actionable clinical reports that support cancer diagnosis, prognosis, and personalized treatment strategies for solid and hematologic malignancies. Result

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Ashraf, Bourawy, and Abdalla Abdalmunam. "Germline Short Variant Discovery and Annotation Pipeline using GATK Tool." Alq J Med App Sci 6, no. 2 (2023): 424–32. https://doi.org/10.5281/zenodo.8219249.

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<strong>Background and aims</strong>. Identifying of variants related to genetic diseases has become affordable with the advances in whole genome sequencing (WGS) enabled by the enhancements of next-generation sequencing technology. Germline and somatic variants are discovered with the help of bioinformatics pipelines utilizing specialized tools. However, the performance and workflow of these tools are subject to evaluation. The aim of this study is to investigate the pipeline of the Genome Analysis Toolkit (GATK) tool in discovering and annotating germline short variants. In particular, this

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Sun, Ruobai, Pablo Cingolani, Angeliki Pantazi, et al. "Germline and somatic SNVS calling in NGS panel tumor samples: Approaches to optimize tumor only genomic analysis for cancer precision medicine." Journal of Clinical Oncology 35, no. 15_suppl (2017): e13011-e13011. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e13011.

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e13011 Background: Clinical NGS is often limited by tumor only profiling. Discrimination between somatic and likely germline mutations when calling from tumor patient samples is a critical step for clinical genotyping. Many algorithms have been developed for somatic single nucleotide variant (SNV) detection in matched tumor-normal whole genome and whole exome sequencing. Here, we demonstrate approaches of how a cost-effective large gene panel sequencing can be used to call somatic and germline SNVs for tumor only samples. Methods: Tumor, adjacent normal, and matched normal samples are collecte

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Martín, Rodrigo, Nicolás Gaitán, and David Torrents. "Protocol for the assessment, improvement, and harmonization of somatic variant calling using ONCOLINER." STAR Protocols 6, no. 1 (2025): 103533. https://doi.org/10.1016/j.xpro.2024.103533.

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Cooke, Daniel P., David C. Wedge, and Gerton Lunter. "Benchmarking small-variant genotyping in polyploids." Genome Research 32, no. 2 (2021): 403–8. http://dx.doi.org/10.1101/gr.275579.121.

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Genotyping from sequencing is the basis of emerging strategies in the molecular breeding of polyploid plants. However, compared with the situation for diploids, in which genotyping accuracies are confidently determined with comprehensive benchmarks, polyploids have been neglected; there are no benchmarks measuring genotyping error rates for small variants using real sequencing reads. We previously introduced a variant calling method, Octopus, that accurately calls germline variants in diploids and somatic mutations in tumors. Here, we evaluate Octopus and other popular tools on whole-genome te

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Rescheneder, Philipp, Phill James, Sean McKenzie, et al. "Abstract 6218: Haplotype-resolved analysis of cancer genomes and epigenomes using Oxford Nanopore sequencing." Cancer Research 84, no. 6_Supplement (2024): 6218. http://dx.doi.org/10.1158/1538-7445.am2024-6218.

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Abstract Cancer is a complex and dynamic disease driven by somatic genomic and epigenomic alterations that accumulate over time. These changes give rise to heterogeneous collections of cells or clones, each with distinct (epi)genomic profiles within a single tumour. Accurate characterisation of these changes is crucial for understanding the mechanisms driving the disease, identifying potential therapeutic targets, and personalising treatment strategies. Due to the technological constraints of short-read and array-based approaches, cancer research has historically had a strong focus on detectin

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Ji, Shuangxi, Tong Zhu, Ankit Sethia, Matthew D. Montierth, and Wenyi Wang. "Abstract 2070: Accelerated somatic mutation calling tool for whole-genome and whole-exome sequencing data from heterogenous tumor samples." Cancer Research 83, no. 7_Supplement (2023): 2070. http://dx.doi.org/10.1158/1538-7445.am2023-2070.

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Abstract As constantly improving in capacity and reducing in price, genomic sequencing is becoming a routine part of medical practice for cancer patients. Variant calling in sequencing data is a fundamental prerequisite for any downstream analysis, thus playing a critical role in both basic research and clinical care of cancers. However, it remains notably time-consuming for most available tools (e.g., ~2 days for MuSE 1.0 and MuTect2 to complete running on one tumor-normal pair of whole-genome sequencing (WGS) data). Here, we launch MuSE 2.0, which maintains the same input and output as our p

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Chen, Lixin, Pingfang Liu, Thomas C. Evans, and Laurence M. Ettwiller. "Response to Comment on “DNA damage is a pervasive cause of sequencing errors, directly confounding variant identification”." Science 361, no. 6409 (2018): eaat0958. http://dx.doi.org/10.1126/science.aat0958.

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Following the Comment of Stewart et al., we repeated our analysis on sequencing runs from The Cancer Genome Atlas (TCGA) using their suggested parameters. We found signs of oxidative damage in all sequence contexts and irrespective of the sequencing date, reaffirming that DNA damage affects mutation-calling pipelines in their ability to accurately identify somatic variations.

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Lal, Jessica Castrillon, Shuangxi Ji, Ruonan Li, Scott Kopetz, and Wenyi Wang. "Abstract 5037: Accelerated somatic mutation calling for whole-exome sequencing of tumor samples." Cancer Research 85, no. 8_Supplement_1 (2025): 5037. https://doi.org/10.1158/1538-7445.am2025-5037.

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Abstract Background: Integrating next-generation sequencing (NGS) data into clinical practice faces several challenges. High-throughput sequencing generates massive amounts of data that need to be processed quickly to deliver timely clinical insights. Additionally, formalin-fixed paraffin embedded (FFPE) tissue is the primary resource for tumor molecular profiling in clinical settings. However, nucleic acids extracted from FFPE are prone to chemical alterations and technical artifacts during sequencing. Therefore, distinguishing tumor-specific variants from artifacts and germline variation wit

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Xu, Chang. "A review of somatic single nucleotide variant calling algorithms for next-generation sequencing data." Computational and Structural Biotechnology Journal 16 (2018): 15–24. http://dx.doi.org/10.1016/j.csbj.2018.01.003.

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Stetson, Daniel, Ambar Ahmed, Xing Xu, et al. "Orthogonal Comparison of Four Plasma NGS Tests With Tumor Suggests Technical Factors are a Major Source of Assay Discordance." JCO Precision Oncology, no. 3 (December 2019): 1–9. http://dx.doi.org/10.1200/po.18.00191.

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PURPOSE Discordance between plasma and tumor variant calling has been attributed primarily to tumor heterogeneity, whereas technical variables remain largely unexplored. MATERIALS AND METHODS To measure these variables, we tested four next-generation sequencing (NGS) gene panel assays for mutations in circulating tumor DNA (ctDNA) using replicate sets of 24 plasma samples and compared the results with matched tumor-normal tissue pairs. RESULTS Our orthogonal approach identified false-negative (FN) and false-positive (FP) variants with high confidence and revealed substantial variability among

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Liu, Tong, Michael Bocek, Patrick Cherry, et al. "Abstract 6608: High-sensitivity detection of specific ultra low-frequency somatic mutations for minimal residual disease monitoring." Cancer Research 83, no. 7_Supplement (2023): 6608. http://dx.doi.org/10.1158/1538-7445.am2023-6608.

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Abstract Minimal/Molecular residual disease (MRD) refers to the small number of tumor cells which may remain within a patient after therapeutic intervention. The detection of these remnants and monitoring of their abundance is a promising prognostic marker to identify individuals at risk of recurrence or in need of adjuvant therapy. Due to the low abundance of ctDNA present in samples obtained during remission, MRD assays need to be highly sensitive. In addition, each individual will have a different set of somatic variants, requiring personalized solutions for detection. Therefore, personaliz

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Raghu, Aarthy, Meenakumari Balaiah, Sridevi Veluswami, Shirley Sundersingh, Rajkumar Thangarajan, and Samson Mani. "Identification of novel somatic cell-free DNA variants by next-generation sequencing in breast cancer patients." International Journal of Molecular & Immuno Oncology 6 (January 8, 2021): 16–26. http://dx.doi.org/10.25259/ijmio_25_2020.

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Objectives: Breast cancer is a heterogeneous disease affecting women worldwide and is one of the leading causes of mortality in India. Sampling bias due to tumor heterogeneity and invasive nature of biopsies necessitate noninvasive methods for comprehensive tumor profiling. Circulating cell-free DNA presents a complete mutation profile of the tumor, enabling the non-invasive monitoring of disease in real-time. This study aimed to identify tumor-specific variants in cfDNA with potential applications in the liquid-biopsy based testing of breast cancer. Material and Methods: Next-generation seque

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Shumilova, Maria, Danil Stupichev, Gleb Khegai, et al. "Abstract 5047: Enhancing germline variant calling: Adjustment with tumor samples to filter low-confidence variants from clonal hematopoiesis." Cancer Research 85, no. 8_Supplement_1 (2025): 5047. https://doi.org/10.1158/1538-7445.am2025-5047.

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Abstract Background: High-quality germline variant calling is crucial for accurate genetic reports; yet, certain factors can lead to false identifications. Clonal hematopoiesis (CH), caused by somatic mutations in blood cells, can mimic germline variants, while pseudogenes and mosaic mutations generate low variant allele frequency (VAF) signals that can be misinterpreted. Current methods for addressing these artifacts use only non-tumor samples, limiting their use in clinical settings for generating genetic reports for tumor samples. To expand the capability of germline variant calling, we dev

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Wang, Junmei, Wanshu He, Lisha Zhu, et al. "Abstract 5895: Development and analytical validation of a highly sensitive tumor fraction estimation method using blood samples without matched normal controls." Cancer Research 85, no. 8_Supplement_1 (2025): 5895. https://doi.org/10.1158/1538-7445.am2025-5895.

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Abstract Background: Tumor fraction (TF) in cell-free DNA (cfDNA) is a quantitative indicator of circulating tumor DNA (ctDNA) and has become an important biomarker for disease monitoring and tracking therapeutic responses. We developed a longitudinal TF estimation method that does not require matched normal control samples and analytically validated its ability to accurately estimate TF when longitudinal blood samples are available. Methods: Both reference materials and clinical blood samples were used in the analytical validation. We first determined the limit of detection (LoD) of TF for ou

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Chua, Khi Pin, Ian McLaughlin, Oliver Hofmann, et al. "Abstract 2934: Somatic variant workflow with HiFi sequencing provides new insights in highly challenging cancer cases." Cancer Research 84, no. 6_Supplement (2024): 2934. http://dx.doi.org/10.1158/1538-7445.am2024-2934.

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Abstract Tumor evolution is a highly heterogeneous process where multiple oncogenic pathways can lead to host defense evasion. Advancements in genome sequencing are allowing us to better understand these processes and their impact. However, critical genomic variations that could be pivotal to the development of tumors may have remained undetected due to technological constraints of short-read sequencing. PacBio HiFi sequencing generates accurate (&gt;99.9%) long reads (&gt;15 kb) with native 5-methylcytosine information that can comprehensively delineate many variations, including ones

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Ainscough, Benjamin J., Erica K. Barnell, Peter Ronning, et al. "A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data." Nature Genetics 50, no. 12 (2018): 1735–43. http://dx.doi.org/10.1038/s41588-018-0257-y.

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Schnidrig, Desiree, Andrea Garofoli, Andrej Benjak, et al. "PipeIT2: A tumor-only somatic variant calling workflow for molecular diagnostic Ion Torrent sequencing data." Genomics 115, no. 2 (2023): 110587. http://dx.doi.org/10.1016/j.ygeno.2023.110587.

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Lin, Yixin, Mads Heilskov Rasmussen, Mikkel Hovden Christensen, et al. "Evaluating Bioinformatics Processing of Somatic Variant Detection in cfDNA Using Targeted Sequencing with UMIs." International Journal of Molecular Sciences 25, no. 21 (2024): 11439. http://dx.doi.org/10.3390/ijms252111439.

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Circulating tumor DNA (ctDNA) is a promising cancer biomarker, but accurately detecting tumor mutations in cell-free DNA (cfDNA) is challenging due to their low frequency and sequencing errors. Our study benchmarked Mutect2, VarScan2, shearwater, and DREAMS-vc using deep targeted sequencing of cfDNA with Unique Molecular Identifiers (UMIs) from 111 colorectal cancer patients. Performance was assessed at both the mutation level (distinguish tumor variants from errors) and the sample level (detect if an individual has cancer). Additionally, we investigated the effects of various UMI grouping and

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Patel, Ravi, Elise Buser, Nafei Xu, et al. "Abstract 6641: Inclusion of INDEL somatic variants in MRD panels improves confidence in ctDNA residual disease detection." Cancer Research 85, no. 8_Supplement_1 (2025): 6641. https://doi.org/10.1158/1538-7445.am2025-6641.

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Abstract Molecular residual disease (MRD) tests detect residual tumor in a patient by identifying the presence of circulating tumor DNA (ctDNA) in cell free DNA (cfDNA). We have developed a highly sensitive MRD test that utilizes panels of hybridization probes targeting somatic variants specific to each patient’s tumor. Our tumor-informed MRD assay utilizes whole genome sequencing (WGS) of tumor and normal tissue followed by a somatic calling pipeline to identify tumor variants and generate a panel targeting these variants. The sensitivity of bespoke MRD tests, like ours, is a function of each

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Decap, Dries, Louise de Schaetzen van Brienen, Maarten Larmuseau, et al. "Halvade somatic: Somatic variant calling with Apache Spark." GigaScience 11 (2022). http://dx.doi.org/10.1093/gigascience/giab094.

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Abstract Background The accurate detection of somatic variants from sequencing data is of key importance for cancer treatment and research. Somatic variant calling requires a high sequencing depth of the tumor sample, especially when the detection of low-frequency variants is also desired. In turn, this leads to large volumes of raw sequencing data to process and hence, large computational requirements. For example, calling the somatic variants according to the GATK best practices guidelines requires days of computing time for a typical whole-genome sequencing sample. Findings We introduce Hal

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Garcia-Prieto, Carlos A., Francisco Martínez-Jiménez, Alfonso Valencia, and Eduard Porta-Pardo. "Detection of oncogenic and clinically actionable mutations in cancer genomes critically depends on variant calling tools." Bioinformatics, May 5, 2022. http://dx.doi.org/10.1093/bioinformatics/btac306.

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Abstract Motivation The analysis of cancer genomes provides fundamental information about its aetiology, the processes driving cell transformation or potential treatments. While researchers and clinicians are often only interested in the identification of oncogenic mutations, actionable variants or mutational signatures, the first crucial step in the analysis of any tumor genome is the identification of somatic variants in cancer cells (i.e., those that have been acquired during their evolution). For that purpose, a wide range of computational tools have been developed in recent years to detec

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Hawari, Marwan A., Celine S. Hong, and Leslie G. Biesecker. "SomatoSim: precision simulation of somatic single nucleotide variants." BMC Bioinformatics 22, no. 1 (2021). http://dx.doi.org/10.1186/s12859-021-04024-8.

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Abstract Background Somatic single nucleotide variants have gained increased attention because of their role in cancer development and the widespread use of high-throughput sequencing techniques. The necessity to accurately identify these variants in sequencing data has led to a proliferation of somatic variant calling tools. Additionally, the use of simulated data to assess the performance of these tools has become common practice, as there is no gold standard dataset for benchmarking performance. However, many existing somatic variant simulation tools are limited because they rely on generat

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Zhao, Xiaofei, Allison C. Hu, Sizhen Wang, and Xiaoyue Wang. "Calling small variants using universality with Bayes-factor-adjusted odds ratios." Briefings in Bioinformatics 23, no. 1 (2021). http://dx.doi.org/10.1093/bib/bbab458.

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Abstract The application of next-generation sequencing in research and particularly in clinical routine requires highly accurate variant calling. Here we describe UVC, a method for calling small variants of germline or somatic origin. By unifying opposite assumptions with sublation, we discovered the following two empirical laws to improve variant calling: allele fraction at high sequencing depth is inversely proportional to the cubic root of variant-calling error rate, and odds ratios adjusted with Bayes factors can model various sequencing biases. UVC outperformed other variant callers on th

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Roberts, Hannah E., Maria Lopopolo, Alistair T. Pagnamenta, et al. "Short and long-read genome sequencing methodologies for somatic variant detection; genomic analysis of a patient with diffuse large B-cell lymphoma." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-021-85354-8.

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AbstractRecent advances in throughput and accuracy mean that the Oxford Nanopore Technologies PromethION platform is a now a viable solution for genome sequencing. Much of the validation of bioinformatic tools for this long-read data has focussed on calling germline variants (including structural variants). Somatic variants are outnumbered many-fold by germline variants and their detection is further complicated by the effects of tumour purity/subclonality. Here, we evaluate the extent to which Nanopore sequencing enables detection and analysis of somatic variation. We do this through sequenci

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Little, Paul, Heejoon Jo, Alan Hoyle, et al. "UNMASC: tumor-only variant calling with unmatched normal controls." NAR Cancer 3, no. 4 (2021). http://dx.doi.org/10.1093/narcan/zcab040.

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Abstract Despite years of progress, mutation detection in cancer samples continues to require significant manual review as a final step. Expert review is particularly challenging in cases where tumors are sequenced without matched normal control DNA. Attempts have been made to call somatic point mutations without a matched normal sample by removing well-known germline variants, utilizing unmatched normal controls, and constructing decision rules to classify sequencing errors and private germline variants. With budgetary constraints related to computational and sequencing costs, finding the app

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Lu, Jinfeng, Camilo Toro, David R. Adams, et al. "LUSTR: a new customizable tool for calling genome-wide germline and somatic short tandem repeat variants." BMC Genomics 25, no. 1 (2024). http://dx.doi.org/10.1186/s12864-023-09935-9.

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Abstract Background Short tandem repeats (STRs) are widely distributed across the human genome and are associated with numerous neurological disorders. However, the extent that STRs contribute to disease is likely under-estimated because of the challenges calling these variants in short read next generation sequencing data. Several computational tools have been developed for STR variant calling, but none fully address all of the complexities associated with this variant class. Results Here we introduce LUSTR which is designed to address some of the challenges associated with STR variant callin

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