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SPARSim single cell: a count data simulator for scRNA-seq data.
Baruzzo, Giacomo; Patuzzi, Ilaria; Di Camillo, Barbara.
Affiliation
  • Baruzzo G; Department of Information Engineering, University of Padova, Padova, Italy.
  • Patuzzi I; Department of Information Engineering, University of Padova, Padova, Italy.
  • Di Camillo B; Microbial Ecology Unit, Istituto Zooprofilattico Sperimentale delle Venezie, Padova, Italy.
Bioinformatics ; 36(5): 1468-1475, 2020 03 01.
Article in En | MEDLINE | ID: mdl-31598633
ABSTRACT
MOTIVATION Single cell RNA-seq (scRNA-seq) count data show many differences compared with bulk RNA-seq count data, making the application of many RNA-seq pre-processing/analysis methods not straightforward or even inappropriate. For this reason, the development of new methods for handling scRNA-seq count data is currently one of the most active research fields in bioinformatics. To help the development of such new methods, the availability of simulated data could play a pivotal role. However, only few scRNA-seq count data simulators are available, often showing poor or not demonstrated similarity with real data.

RESULTS:

In this article we present SPARSim, a scRNA-seq count data simulator based on a Gamma-Multivariate Hypergeometric model. We demonstrate that SPARSim allows to generate count data that resemble real data in terms of count intensity, variability and sparsity, performing comparably or better than one of the most used scRNA-seq simulator, Splat. In particular, SPARSim simulated count matrices well resemble the distribution of zeros across different expression intensities observed in real count data. AVAILABILITY AND IMPLEMENTATION SPARSim R package is freely available at http//sysbiobig.dei.unipd.it/? q=SPARSim and at https//gitlab.com/sysbiobig/sparsim. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Single-Cell Analysis Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2020 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Single-Cell Analysis Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2020 Document type: Article Affiliation country:
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