Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,186 bioRxiv papers from 306,470 authors.

CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer

By Thomas D Sherman, Luciane Tsukamoto Kagohara, Raymon Cao, Raymond Cheng, Matthew Satriano, Michael Considine, Gabriel Krigsfeld, Ruchira Ranaweera, Yong Tang, Sandra A Jablonski, Genevieve Stein-O’Brien, Daria A Gaykalova, Louis M Weiner, Christine H Chung, Elana J Fertig

Posted 23 May 2018
bioRxiv DOI: 10.1101/328807 (published DOI: 10.1371/journal.pcbi.1006935)

Bioinformatics techniques to analyze time course bulk and single cell omics data are advancing. The absence of a known ground truth of the dynamics of molecular changes challenges benchmarking their performance on real data. Realistic simulated time-course datasets are essential to assess the performance of time course bioinformatics algorithms. We develop an R/Bioconductor package, CancerInSilico, to simulate bulk and single cell transcriptional data from a known ground truth obtained from mathematical models of cellular systems. This package contains a general R infrastructure for running cell-based models and simulating gene expression data based on the model states. We show how to use this package to simulate a gene expression data set and consequently benchmark analysis methods on this data set with a known ground truth. The package is freely available via Bioconductor: http://bioconductor.org/packages/CancerInSilico/

Download data

  • Downloaded 1,116 times
  • Download rankings, all-time:
    • Site-wide: 6,851 out of 70,186
    • In systems biology: 197 out of 1,933
  • Year to date:
    • Site-wide: 21,386 out of 70,186
  • Since beginning of last month:
    • Site-wide: 16,274 out of 70,186

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)