ROSeq

The 'ROSeq' software tool analyzes single-cell transcriptomics data, focusing on accurate modeling of gene expression patterns. It explores the use of the discrete generalized beta distribution (DGBD) to model expression ranks as robust surrogates for transcript abundance. The tool includes a Wald-type test for comparing gene expression across two phenotypically divergent groups of single cells. A comprehensive assessment demonstrated a reasonable balance between Type I and Type II errors, robustness to expression noise, and scalability with increasing sample size.

Topic

Gene expression;Genotype and phenotype;Cell biology;RNA-Seq

Detail

  • Operation: Differential gene expression profiling;Standardisation and normalisation;Filtering;Quantification

  • Software interface: Library

  • Language: R

  • License: The GNU General Public License v3.0

  • Cost: Free

  • Version name: 1.14.0

  • Credit: The INSPIRE faculty grant by the Department of Science and Technology, Government of India, Ramalingaswami Re-entry Fellowship by the Department of Biotechnology, Government of India.

  • Input: -

  • Output: -

  • Contact: Krishan Gupta krishang@iiitd.ac.in

  • Collection: -

  • Maturity: Stable

Publications

  • ROSeq: A rank based approach to modeling gene expression in single cells
  • Kaushik A, et al. miRMOD: a tool for identification and analysis of 5' and 3' miRNA modifications in Next Generation Sequencing small RNA data. miRMOD: a tool for identification and analysis of 5' and 3' miRNA modifications in Next Generation Sequencing small RNA data. 2015; 3:e1332. doi: 10.7717/peerj.1332
  • https://doi.org/10.1101/374025
  • PMID: -
  • PMC: -
  • Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-seq data.
  • Gupta K, et al. Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-seq data. Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-seq data. 2021; 31:689-697. doi: 10.1101/gr.267070.120
  • https://doi.org/10.1101/GR.267070.120
  • PMID: 33674351
  • PMC: PMC8015842

Download and documentation

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