GSR: Editing - SERGIO Simulator

You may request changes to this simulator by navigating to the Basic, Details, and Citations/Applications tabs. When you are finished, open the Submit tab. To return back to the simulator view, click SERGIO. Finally, please take note of the GSR simulator privacy policy.
SERGIO
Sergio is a simulator for single-cell gene expression data that models the stochastic nature of the transcription and regulation of genes via transcription factors according to a user-provided gene regulatory network.
Sergio is a simulator for single-cell gene expression data that models the stochastic nature of the transcription and regulation of genes via transcription factors according to a user-provided gene regulatory network. The package can simulate cell types in steady states or cells differentiating to multiple fates. The datasets generated by SERGIO are statistically comparable to experimental data generated by Illumina HiSeq200, Drop-Seq, Illumina 10x chromium and Smart-seq
v1.1.0
July 29, 2020
July 29, 2020
https://github.com/PayamDiba/SERGIO
dibaein2@illinois.edu

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: 32871105], Dibaeinia P, Sinha S, SERGIO: A Single-Cell Expression Simulator Guided by Gene Regulatory Networks., Cell Syst, 09-23-2020, https://www.ncbi.nlm.nih.gov/pubmed/?term=32871105,Primary Citation
      [Pubmed ID: 37079737], Li L, Sun L, Chen G, Wong CW, Ching WK, Liu ZP, LogBTF: gene regulatory network inference using Boolean threshold network model from single-cell gene expression data., Bioinformatics, 05-04-2023, https://www.ncbi.nlm.nih.gov/pubmed/?term=37079737,, Application
      [Pubmed ID: 37246643], Yang Y, Li G, Zhong Y, Xu Q, Chen BJ, Lin YT, Chapkin RS, Cai JJ, Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks., Nucleic Acids Res, 07-21-2023, https://www.ncbi.nlm.nih.gov/pubmed/?term=37246643,, Application
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      Please inform the GSR team here if you would like to see an attribute added to the attribute tree (or any other changes to the simulator description system as it exists).