SCSIM: Jointly simulating correlated single-cell and bulk next-generation DNA sequencing data
Autor: | Harsh Vardhan Dubey, Shai He, Patrick Flaherty, Collin Giguere, Vishal Kumar Sarsani, Hachem Saddiki |
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Rok vydání: | 2020 |
Předmět: |
simulator
Single-cell DNA sequencing Downstream (software development) Computer science Cell Sample (statistics) lcsh:Computer applications to medicine. Medical informatics computer.software_genre Biochemistry DNA sequencing Hierarchical Dirichlet 03 medical and health sciences 0302 clinical medicine Structural Biology medicine Humans lcsh:QH301-705.5 Molecular Biology 030304 developmental biology 0303 health sciences Applied Mathematics High-Throughput Nucleotide Sequencing Sequence Analysis DNA Computer Science Applications medicine.anatomical_structure lcsh:Biology (General) lcsh:R858-859.7 Data mining Single-Cell Analysis DNA microarray computer Software 030217 neurology & neurosurgery |
Zdroj: | BMC Bioinformatics, Vol 21, Iss 1, Pp 1-10 (2020) BMC Bioinformatics |
ISSN: | 1471-2105 |
Popis: | Background Recently, it has become possible to collect next-generation DNA sequencing data sets that are composed of multiple samples from multiple biological units where each of these samples may be from a single cell or bulk tissue. Yet, there does not yet exist a tool for simulating DNA sequencing data from such a nested sampling arrangement with single-cell and bulk samples so that developers of analysis methods can assess accuracy and precision. Results We have developed a tool that simulates DNA sequencing data from hierarchically grouped (correlated) samples where each sample is designated bulk or single-cell. Our tool uses a simple configuration file to define the experimental arrangement and can be integrated into software pipelines for testing of variant callers or other genomic tools. Conclusions The DNA sequencing data generated by our simulator is representative of real data and integrates seamlessly with standard downstream analysis tools. |
Databáze: | OpenAIRE |
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