GSR: Editing - Synggen Simulator

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Synggen
Fast and data-driven generation of synthetic heterogeneous NGS cancer data
Synggen is a tool written in C programming language to generate synthetic NGS files, in the form of whole-exome or targeted sequencing experiments, representing heterogeneous cancer genomes and matched controls. The tool provides two execution modes which allow to (i) exploit a set of control (non-cancer) NGS sequencing files (BAM format) to generate reference models capturing a collection of data summary statistics; and (ii) combine these reference models and a set of user-specified germline and somatic genomic profiles to create synthetic sequencing files (FASTQ format). Synggen allows to input specific lists of germline variants and somatic genomic events, including phased germline SNPs and somatic allele-specific CNAs and SNVs, together with local and global parameters including the clonality of somatic events and the overall sample tumor content, allowing for the emulation of varied and realistic cancer- and patient-specific data across the different multi-subclones composition, tumor purity, aneuploidy and tumor evolution scenarios.
SNV, INDELs, copy number, allele-specific, ploidy, tumor content, simulation, NGS, whole-exome sequencing, targeted sequencing
1.6
Dec. 9, 2022
Dec. 3, 2023
https://bcglab.cibio.unitn.it/synggen
alessandro.romanel@unitn.it

Attribute Tree Control

Step 1: Use the attribute tree to add new attributes or remove pre-selected attributes to describe the simulator.
Every sub-attribute is selected
Not all sub-attributes are selected
  • Target
    • Type of Simulated Data
      • Genotype at Genetic Markers
      • Diploid DNA Sequence
      • Haploid DNA Sequence
      • RNA
      • Gene Expression
      • Sex Chromosomes
      • Mitochondrial DNA
      • Protein Sequence
      • Sequencing Reads
      • Phenotype
      • Single-Cell Sequencing
      • Bulk Sequencing
      • Proteomics
      • Chromatin Conformation
    • Variations
      • Biallelic Marker
      • Multiallelic Marker
      • Single Nucleotide Variation
      • Amino acid variation
      • Microsatellite
      • Insertion and Deletion
      • CNV
      • Inversion and Rearrangement
      • Alternative Splicing
      • Missing Genotypes
      • Genotype or Sequencing Error
      • Ionization
      • Other
  • Simulation Method
    • Standard Coalescent
    • Exact Coalescent
    • Machine Learning
    • Forward-time
    • Resample Existing Data
    • Phylogenetic
    • Gene dropping
    • Neural network
    • Other
  • Input
    • Data Type
      • Allele Frequencies
      • Empirical
      • Ancestral Sequence
      • Saved simulation
      • Reference genome
      • Other
    • File format
      • Arlequin
      • CREATE
      • Fstat
      • GDA
      • Genepop
      • MIGRATE
      • MS
      • SAM or BAM
      • NEXUS
      • Phylip
      • STRUCTURE
      • XML
      • Tree Sequence
      • Program Specific
      • Other
  • Output
    • Data Type
      • Genotype or Sequence
      • Phenotypic Trait
      • Individual Relationship
      • Phylogenetic Tree
      • Demographic
      • Mutation
      • Methylation
      • Gene Expression
      • Protein Expression
      • Linkage Disequilibrium
      • Diversity Measures
      • Fitness
      • Sequencing Reads
        • Illumina
        • Roche 454
        • SOLiD
        • IonTorrent
        • PacBio
        • Nanopore
        • Other
      • Other
    • File Format
      • Arlequin
      • Fasta or Fastq
      • Fstat
      • Genepop
      • Linkage
      • MIGRATE
      • MS
      • PED
      • Phylip
      • NEXUS
      • STRUCTURE
      • VCF
      • SAM or BAM
      • Tree Sequence
      • Program Specific
      • Other
    • Sample Type
      • Random or Independent
      • Sibpairs, Trios and Nuclear Families
      • Extended or Complete Pedigrees
      • Case-control
      • Longitudinal
      • Other
  • Phenotype
    • Trait Type
      • Binary or Qualitative
      • Quantitative
      • Multiple
    • Determinants
      • Single Genetic Marker
      • Multiple Genetic Markers
      • Sex-linked
      • Gene-Gene Interaction
      • Environmental Factors
      • Gene-Environment Interaction
  • Evolutionary Features
    • Demographic
      • Population Size Changes
        • Constant Size
        • Exponential Growth or Decline
        • Logistic Growth
        • Bottleneck
        • Carrying Capacity
        • User Defined
      • Gene Flow
        • Stepping Stone Models
        • Island Models
        • Continent-Island Models
        • Sex or Age-Specific Migration Rates
        • Influenced by Environmental Factors
        • Admixed Population
        • User-defined Matrix
        • Other
      • Spatiality
        • Discrete Models
        • Continuous Models
        • Landscape Factors
    • Life Cycle
      • Discrete Generation Model
      • Age structured
      • Overlapping Generation
      • User-Defined transition matrices
    • Mating System
      • Random Mating
      • Monogamous
      • Polygamous
      • Haplodiploid
      • Selfing
      • Age- or Stage-Specific
      • Assortative or Disassortative
      • Other
    • Fecundity
      • Constant Number
      • Randomly Distributed
      • Individually Determined
      • Influenced by Environment
      • Other
    • Natural Selection
      • Determinant
        • Single-locus
        • Multi-locus
        • Codon-based
        • Fitness of Offspring
        • Phenotypic Trait
        • Environmental Factors
      • Models
        • Directional Selection
        • Balancing Selection
        • Multi-locus models
        • Epistasis
        • Random Fitness Effects
        • Disruptive
        • Phenotype Threshold
        • Frequency-Dependent
        • Other
    • Recombination
      • Uniform
      • Varying Recombination Rates
      • Gene Conversion Allowed
    • Mutation Models
      • Two-allele Mutation Model
      • Markov DNA Evolution Models
      • k-Allele Model
      • Infinite-allele Model
      • Infinite-sites Model
      • Stepwise Mutation Model
      • Codon and Amino Acid Models
      • Indels and Others
      • Heterogeneity among Sites
      • Others
    • Events Allowed
      • Population Merge and Split
      • Varying Demographic Features
      • Population Events
      • Varying Genetic Features
      • Change of Mating Systems
      • Other
    • Other
      • Phenogenetic
      • Polygenic background
  • Interface
    • Command-line
    • Graphical User Interface
    • Integrated Development Environment
    • Script-based
    • Web-based
  • Development
    • Tested Platforms
      • Windows
      • Mac OS X
      • Linux and Unix
      • Solaris
      • Others
    • Language
      • C or C++
      • Java
      • R
      • Python
      • Perl
      • Visual Basic
      • Other
    • License
      • GNU Public License
      • BSD
      • Creative Commons
      • MIT
      • Other
  • GSR Certification
    • Accessibility
    • Documentation
    • Application
    • Support

Summary of Proposed Changes

Step 2: Review list of proposed attribute addition(s) and subtraction(s).

To Add

    To Remove

      Can't Find the Attribute You Are Looking For?

      If you would like to propose an attribute that you cannot find in the tree above, or if you would like to add a clarification to one or more attributes for this simulator (e.g. a specific file format for attribute /Output/File Format/Other), please list them in the Additional Comment box of the Submit tab.

      You may add citations by pmid, add citations by direct entry, remove citations (using the recycling bin icon), and edit citations (using the rarely seen edit icon) that were originally entered by direct entry.

      Summary of Proposed Changes

      To Add

      To Remove

      Current Citations/Applications

      [Pubmed ID: 36484701], Scandino R, Calabrese F, Romanel A, Synggen: fast and data-driven generation of synthetic heterogeneous NGS cancer data., Bioinformatics, 01-01-2023, https://www.ncbi.nlm.nih.gov/pubmed/?term=36484701,Primary Citation
      [Pubmed ID: 37478715], Lazebnik T, Simon-Keren L, Cancer-inspired genomics mapper model for the generation of synthetic DNA sequences with desired genomics signatures., Comput Biol Med, 09-01-2023, https://www.ncbi.nlm.nih.gov/pubmed/?term=37478715,, Application
      [Pubmed ID: 38971967], Jurczak S, Druchok M, Cancer Immunotherapies Ignited by a Thorough Machine Learning-Based Selection of Neoantigens., Adv Biol (Weinh), 07-06-2024, https://www.ncbi.nlm.nih.gov/pubmed/?term=38971967,, Application
      [Pubmed ID: 40057527], Scandino R, Nardone A, Casiraghi N, Galardi F, Genovese M, Romagnoli D, Paoli M, Biagioni C, Tonina A, Migliaccio I, et al., Enabling sensitive and precise detection of ctDNA through somatic copy number aberrations in breast cancer., NPJ Breast Cancer, 03-08-2025, https://www.ncbi.nlm.nih.gov/pubmed/?term=40057527,, Application
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