VarScan2 analysis of de novo variants in monozygotic twins discordant for schizophrenia

Reble, Emma; Castellani, Christina A; Melka, Melkaye G; O’Reilly, Richard; Singh, Shiva M.

doi:10.1097/ypg.0000000000000162

Cited by 32 publications

(25 citation statements)

References 36 publications

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“…High-risk patients are usually tested for CNS disease by CSF analysis including cytology and FC. Although FC is a more sensitive test than conventional cytology 5,6 , it has some limitations 22 and some patients with no evidence of CNS disease by FC still relapse, suggesting the presence of undetected malignant cells in the CSF. We identified ctDNA in the CSF in the absence of MRI or FC detection earlier than CNS relapse.…”

Section: Discussionmentioning

confidence: 99%

“…Purity was estimated by Vall d'Hebron Hospital Lymphoma specialist pathologists. The ploidy of each gene in the 300 gene panel was estimated from the calculation of copy number alterations (CNA), through the tool CNVkit [6] with the PSCBS segmentation method [9,10]. On the other hand, the ploidy of the WES was estimated from the calculation of CNAs through Control-FREEC [12].…”

Section: Dna Sequencing and Mutation Genomic Analysismentioning

confidence: 99%

“…Cytology is highly specific but has a very limited sensitivity, showing up to 40% false negatives. In contrast, FC is a more sensitive tool, detecting malignant cells in up to 5-15% of patients with negative cytology 5,6 . Still, FC has some limitations and in a relevant fraction of patients, recurrence in the CNS is found shortly after a negative result by FC, suggesting that tumor cells were undetected.…”

Section: Introductionmentioning

confidence: 99%

“…Alignment files (BAM format) were processed using Picard (v.1.110) [3] to add read groups and remove duplicates. The resulting BAM files were processed using SAMtools (v. 1.2) [4] and the Genome Analysis ToolKit (GATK) (v. 3.2.0) [5] Variants were called by VarScan (v2.4.3)[6] with the following parameters: minimum variant allele frequency (VAF) of 5%, a minimum coverage of 8 reads and a minimum of 7 reads that confirm the mutation with a p-value below 0.05. Annotation of the vcf files was performed with ANNOVAR[7].…”

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confidence: 99%

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Cell free circulating tumor DNA in cerebrospinal fluid detects and monitors central nervous system involvement of B-cell lymphomas

Bobillo

Crespo

Escudero³

et al. 2020

haematol

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Cell free circulating tumor DNA in cerebrospinal fluid detects and monitors central nervous system involvement of B-cell lymphomas. Abstract word count: 250 Text word count: 2898 Tables and figures: 5 Supplemental files: 2Acknowlegements: The authors would to thank the patients diagnosed at the Vall d'Hebron University Hospital that were enrolled in the study, as well as the Cellex Foundation for providing research facilities and equipment. ABSTRACTThe levels of cell free circulating tumor DNA (ctDNA) in plasma correlate with treatment response and outcome in systemic lymphomas. Notably, in brain tumors, the levels of ctDNA in the cerebrospinal fluid (CSF) are higher than in plasma. Nevertheless, their role in central nervous system (CNS) lymphomas remains elusive. We evaluated the CSF and plasma from 19 patients: 6 restricted CNS lymphomas, 1 systemic and CNS lymphoma, and 12 systemic lymphomas. We performed whole exome sequencing or targeted sequencing to identify somatic mutations of the primary tumor, then variantspecific droplet digital PCR was designed for each mutation. At time of enrolment, we found ctDNA in the CSF of all patients with restricted CNS lymphoma but not in patients with systemic lymphoma without CNS involvement. Conversely, plasma ctDNA was detected in only 2 out of 6 patients with restricted CNS lymphoma with lower variant allele frequencies than CSF ctDNA. Moreover, we detected CSF ctDNA in 1 patient with CNS lymphoma in complete remission and in 1 patient with systemic lymphoma, 3 and 8 months before CNS relapse was confirmed; indicating that CSF ctDNA might detect CNS relapse earlier than conventional methods. Finally, in 2 cases with CNS lymphoma, CSF ctDNA was still detected after treatment even though no tumoral cells were observed by flow cytometry (FC), indicating that CSF ctDNA better detected residual disease than FC. In conclusion, CSF ctDNA can better detect CNS lesions than plasma ctDNA and FC. In addition, CSF ctDNA predicted CNS relapse in CNS and systemic lymphomas.

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Section: Discussionmentioning

confidence: 99%

Section: Dna Sequencing and Mutation Genomic Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Cell free circulating tumor DNA in cerebrospinal fluid detects and monitors central nervous system involvement of B-cell lymphomas

Bobillo

Crespo

Escudero³

et al. 2020

haematol

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“…Although this can be accomplished by NGS technology, the detection of copy number variants (CNVs) is complicated by: (1) biases in bait capture, 46 leading to uneven coverage across exons, (2) sparse breadth of coverage across the chromosome because only targeted genes are captured, and (3) decreased sensitivity in heterogeneous tumor samples. 47 Similar to SNVs and indels, there are many different algorithms for detecting CNVs; these include VarScan2, 48 CNVKit, 49 Control-FREEC (Control-FREE Copy number and allelic content caller), 50 and OncoCNV 46 (Table 2). OncoCNV is designed for amplicon data and includes normalization methods specific for the biases in PCR methods.…”

Section: Workflow Step 4: Identifying Copy Number Variation In Dnamentioning

confidence: 99%

Assembling and Validating Bioinformatic Pipelines for Next-Generation Sequencing Clinical Assays

SoRelle

Wachsmann

Cantarel

2020

Archives of Pathology &Amp; Laboratory Medicine

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Context.— Clinical next-generation sequencing (NGS) is being rapidly adopted, but analysis and interpretation of large data sets prompt new challenges for a clinical lab setting. Clinical NGS results rely heavily on the bioinformatics pipeline for identifying genetic variation in complex samples. The choice of bioinformatics algorithms, genome assembly, and genetic annotation databases are important for determining genetic alterations associated with disease. The analysis methods are often tuned to the assay to maximize accuracy. Once a pipeline has been developed, it must be validated to determine accuracy and reproducibility for samples similar to real-world cases. In silico proficiency testing or institutional data exchange will ensure consistency among clinical laboratories. Objective.— To provide molecular pathologists a step-by-step guide to bioinformatics analysis and validation design in order to navigate the regulatory and validation standards of implementing a bioinformatic pipelines as a part of a new clinical NGS assay. Data Sources.— This guide uses published studies on genomic analysis, bioinformatics methods, and methods comparison studies to inform the reader on what resources, including open source software tools and databases, are available for genetic variant detection and interpretation. Conclusions.— This review covers 4 key concepts: (1) bioinformatic analysis design for detecting genetic variation, (2) the resources for assessing genetic effects, (3) analysis validation assessment experiments and data sets, including a diverse set of samples to mimic real-world challenges that assess accuracy and reproducibility, and (4) if concordance between clinical laboratories will be improved by proficiency testing designed to test bioinformatic pipelines.

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Genomics of schizophrenia

Corvin

Ormond

Cole

2020

Personalized Psychiatry

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VarScan2 analysis of de novo variants in monozygotic twins discordant for schizophrenia

Cited by 32 publications

References 36 publications

Cell free circulating tumor DNA in cerebrospinal fluid detects and monitors central nervous system involvement of B-cell lymphomas

Cell free circulating tumor DNA in cerebrospinal fluid detects and monitors central nervous system involvement of B-cell lymphomas

Assembling and Validating Bioinformatic Pipelines for Next-Generation Sequencing Clinical Assays

Genomics of schizophrenia

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