CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data

Most existing dimensionality reduction and clustering packages for single-cell RNA-seq (scRNA-seq) data deal with dropouts by heavy modeling and computational machinery. Here, we introduce CIDR (Clustering through Imputation and Dimensionality Reduction), an ultrafast algorithm that uses a novel yet very simple implicit imputation approach to alleviate the impact of dropouts in scRNA-seq data in a principled manner. Using a range of simulated and real data, we show that CIDR improves the standard principal component analysis and outperforms the state-of-the-art methods, namely t-SNE, ZIFA, and RaceID, in terms of clustering accuracy. CIDR typically completes within seconds when processing a data set of…

• AW
  Amazon Web Services
• NH
  National Heart Foundation of Australia
• NM
  NSW Ministry of Health
• MR
  Medical Research Council
• NH
  National Health and Medical Research Council

  Award: 1105271