CIDR statistics

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Citations per year

Number of citations per year for the bioinformatics software tool CIDR

Tool usage distribution map

This map represents all the scientific publications referring to CIDR per scientific context
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Associated diseases


Popular tool citations

chevron_left Clustering Single-cell imputation Dimensionality reduction chevron_right
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CIDR specifications


Unique identifier OMICS_12590
Alternative name Clustering through Imputation and Dimensionality Reduction
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 0.1.0
Stability Stable
Maintained Yes


No version available



  • person_outline Peijie Lin

Publication for Clustering through Imputation and Dimensionality Reduction

CIDR citations


Light focusing human micro lenses generated from pluripotent stem cells model lens development and drug induced cataract in vitro

PMCID: 5825866
PMID: 29217756
DOI: 10.1242/dev.155838

[…] rwise dissimilarity matrix using the binary distance function in R. The dissimilarity matrix was then used as the input to the principal component analysis (PCoA) function implemented in an R package CIDR (). Results were visualised using the first two principal components (PC1 and PC2). For gene-set analysis against published gene expression data, a large compendium of tissue-specific gene expres […]


Impact of sequencing depth and read length on single cell RNA sequencing data of T cells

Sci Rep
PMCID: 5630586
PMID: 28986563
DOI: 10.1038/s41598-017-12989-x

[…] Dropout analysis, principal coordinates analysis and clustering were performed using CIDR, which requires raw read counts as input data. The tool featureCounts was used to obtain the read counts, with the–primary option to allow only primary alignments. The dropoutCandidates Boolean m […]


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

Genome Biol
PMCID: 5371246
PMID: 28351406
DOI: 10.1186/s13059-017-1188-0
call_split See protocol

[…] To determine the dropout candidate threshold that separates the first two modes in the distribution of tags (logTPM) of a library, CIDR finds the minimum point between the two modes in the density curve of the distribution. The R function density is used for kernel density estimation, and the Epanechnikov kernel is used as the sm […]

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CIDR institution(s)
Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia; St Vincent’s Clinical School, University of New South Wales, Darlinghurst, NSW, Australia

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