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GSR: Simulator - DeepSimulator
| Attribute | Value |
|---|---|
| Title | DeepSimulator |
| Short Description | The first deep learning based Nanopore simulator which can simulate the process of Nanopore sequencing |
| Long Description | DeepSimulator, to mimic the entire pipeline of Nanopore sequencing. Starting from a given reference genome or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments performed across four species show that the signals generated by our context-dependent model are more similar to the experimentally obtained signals than the ones generated by the official context-independent pore model. In terms of the simulated reads, we provide a parameter interface to users so that they can obtain the reads with different accuracies ranging from 83 to 97%. The reads generated by the default parameter have almost the same properties as the real data. Two case studies demonstrate the application of DeepSimulator to benefit the development of tools in de novo assembly and in low coverage SNP detection. |
| Keywords | Nanopore, sequencing, |
| Version | 1.5 |
| Project Started | 2019 |
| Last Release | 4 years, 10 months ago |
| Homepage | https://github.com/liyu95/DeepSimulator |
| Citations |
|
| GSR Certification |  ✔ Accessibility |
| Last evaluated | Feb. 28, 2023 (905 days ago) |
| Author verification | The basic description provided was derived from a website or publications by the GSR team and has not yet been verified by the simulation author. To modify this entry or add more information, propose changes to this simulator. |
| Attribute Category | Attribute |
|---|---|
| Target | |
| Type of Simulated Data | Haploid DNA Sequence, Sequencing Reads, |
| Variations | Single Nucleotide Variation, |
| Simulation Method | Other, |
| Input | |
| Data Type | |
| File format | |
| Output | |
| Data Type | |
| Sequencing Reads | Nanopore, |
| File Format | Fasta or Fastq, |
| Sample Type | |
| Phenotype | |
| Trait Type | |
| Determinants | |
| Evolutionary Features | |
| Demographic | |
| Population Size Changes | |
| Gene Flow | |
| Spatiality | |
| Life Cycle | |
| Mating System | |
| Fecundity | |
| Natural Selection | |
| Determinant | |
| Models | |
| Recombination | |
| Mutation Models | |
| Events Allowed | |
| Other | |
| Interface | |
| Development | |
| Tested Platforms | |
| Language | C or C++, Python, |
| License | |
| GSR Certification | Accessibility, Documentation, Application, Support, |
Number of Primary Citations: 2
Number of Non-Primary Citations: 2
The following 2 publications are selected examples of applications that used DeepSimulator.
2022
Curry KD, Wang Q, Nute MG, Tyshaieva A, Reeves E, Soriano S, Wu Q, Graeber E, Finzer P, Mendling W, et al., Emu: species-level microbial community profiling of full-length 16S rRNA Oxford Nanopore sequencing data., Nat Methods, July 1, 2022 [Abstract]
de la Rubia I, Srivastava A, Xue W, Indi JA, Carbonell-Sala S, Lagarde J, Albà MM, Eyras E, RATTLE: reference-free reconstruction and quantification of transcriptomes from Nanopore sequencing., Genome Biol, July 8, 2022 [Abstract]