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scABC specifications


Unique identifier OMICS_30487
Name scABC
Alternative name single cell Accessibility Based Clustering
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Stability Stable
Maintained Yes




No version available



  • person_outline Wing Hung Wong

Publication for single cell Accessibility Based Clustering

scABC citations


Single Cell Multi Omics Technology: Methodology and Application

PMCID: 5919954
PMID: 29732369
DOI: 10.3389/fcell.2018.00028

[…] s, concerns have been raised about the sensitivity of this strategy (Zamanighomi et al., ). Interestingly, methods designed for scATAC-seq analysis are emerging, such as chromVAR (Schep et al., ) and scABC (Zamanighomi et al., ). We believe these pipelines will also inspire the development of effective pipelines for scChIP-seq data. […]


Gene selection for cancer classification with the help of bees

BMC Med Genomics
PMCID: 4980787
PMID: 27510562
DOI: 10.1186/s12920-016-0204-7

[…] duced by Yan et al. [] to solve the premature convergence issue of ABC by increasing the number of scout and rational using of the global optimal value and chaotic Search. Again a Scaled Chaotic ABC (SCABC) method is proposed in [] based on fitness scaling strategy and chaotic theory. Based on the Rossler attractor of chaotic theory a novel Chaotic Artificial Bee Colony (CABC) is developed in [] t […]


Pathological brain detection in MRI scanning by wavelet packet Tsallis entropy and fuzzy support vector machine

PMCID: 4656268
PMID: 26636004
DOI: 10.1186/s40064-015-1523-4

[…] -ANN), were employed. Wu and Wang () followed EI-Dahshan’s method, but suggest to use a feed-forward neural network (FNN) as the classifier, which was trained by scaled chaotic artificial bee colony (SCABC). Dong et al. () proposed to employed scaled conjugate gradient (SCG) method to take place of SCABC. Zhang and Wu () suggested to utilize kernel support vector machine (KSVM). 3 kernels were pro […]


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scABC institution(s)
Department of Statistics, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA; Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA; Department of Applied Physics, Stanford University, Stanford, CA, USA
scABC funding source(s)
Supported by grants R01HG007834, P50HG007735, and R01GM109836 from the National Institutes of Health (NIH).

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