Monovar statistics

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Monovar specifications

Information


Unique identifier OMICS_12091
Name Monovar
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data A list of BAM files
Output data VCF file containing the detected SNVs
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Stability Stable
Requirements
SAMtools, Numpy, Scipy, PySam
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Ken Chen

Publication for Monovar

Monovar citations

 (3)
library_books

Sensitivity to sequencing depth in single cell cancer genomics

2018
Genome Med
PMCID: 5901877
PMID: 29661213
DOI: 10.1186/s13073-018-0537-2

[…] hnical replicates were generated for statistical validation, resulting in a total of 6280 BAM files. Single-cell SNV calls were obtained from the original and down-sampled single-cell BAM files using Monovar [], a variant caller specifically designed for single-cell data, under default settings. Single-cell variant-calling performance was evaluated by estimating the proportion of “gold-standard” g […]

library_books

The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: summary and innovation in genomics

2017
BMC Genomics
PMCID: 5629612
PMID: 28984207
DOI: 10.1186/s12864-017-4018-6

[…] ncer Center. Dr. Chen talked about how he overcame some of the computational challenges by developing a suite of new algorithms for single-cell DNA sequencing technology in cancer research, including Monovar, SiFit, and novoBreak.“Functional proteomics as a major approach for precision cancer medicine” by Dr. Han Liang, Associate Professor at the Department of Bioinformatics and Computational Biol […]

library_books

Current Progresses of Single Cell DNA Sequencing in Breast Cancer Research

2017
PMCID: 5599901
PMID: 28924377
DOI: 10.7150/ijbs.19627

[…] ariant callers basically do not include allelic dropout (ADO), allelic imbalance, coverage non-uniformity and false-positive errors, so they are not exactly applicable for single cell DNA sequencing. Monovar is a novel method designed for detecting and genotyping SNVs in single cell data, which outperforms standard methods commonly used to identify driver mutations and delineating clonal substruct […]

Citations

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Monovar institution(s)
Department of Computer Science, Rice University, Houston, TX, USA; Department of Bioinformatics and Computational Biology, the University of Texas M.D. Anderson Cancer Center, Houston, TX, USA; Department of Genetics, the University of Texas M.D. Anderson Cancer Center, Houston, TX, USA

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