CODEX statistics

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Citations per year

Number of citations per year for the bioinformatics software tool CODEX
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Tool usage distribution map

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

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Popular tool citations

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Protocols

CODEX specifications

Information


Unique identifier OMICS_07305
Name CODEX
Alternative names COpy number Detection by EXome sequencing, CODEX2
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
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Maintainers


  • person_outline Nancy Zhang
  • person_outline Yuchao Jiang
  • person_outline Yuchao Jiang

Additional information


http://www.bioconductor.org/packages/devel/bioc/html/CODEX.html

Publications for COpy number Detection by EXome sequencing

CODEX citations

 (5)
library_books

WISExome: a within sample comparison approach to detect copy number variations in whole exome sequencing data

2017
Eur J Hum Genet
PMCID: 5865163
PMID: 29255179
DOI: 10.1038/s41431-017-0005-2

[…] d exons (shown in Supplementary Fig. S) compared to the total number of calls as shown in Fig. .To further zoom in on differences, Supplementary Fig. S shows the overlap between WISExome, CLAMMS, and CODEX. This figure again shows that CODEX calls significantly more genes/exons aberrated than other tools. WISExome and CLAMMS show a larger overlap, but WISExome’s unique calls are more overlapping w […]

library_books

The contribution of pathogenic variants in breast cancer susceptibility genes to familial breast cancer risk

2017
PMCID: 5466608
PMID: 28649662
DOI: 10.1038/s41523-017-0024-8

[…] Potential copy number variants (one or greater exonic deletions and duplications) were identified with the exome hidden Markov model and COpy number Detection by EXome sequencing algorithms from NGS data. Copy number variants identified by both algorithms (n = 12) were examined in the Integrated Genome Viewer to confirm the visual pres […]

library_books

Gene based comparative analysis of tools for estimating copy number alterations using whole exome sequencing data

2017
Oncotarget
PMCID: 5432334
PMID: 28460482
DOI: 10.18632/oncotarget.15932

[…] equires a control set []. CoNIFER uses singular value decomposition methodology and does not require a control set []. VarScan2 uses pairwise comparison of read depth and population-based methods []. CODEX uses Poisson likelihood-based recursive segmentation and requires normalization using normal samples []. NgCGH computes a pseudo-CGH using simple coverage counting for the tumor relative to the […]

library_books

Novel bioinformatic developments for exome sequencing

2016
Hum Genet
PMCID: 4883269
PMID: 27075447
DOI: 10.1007/s00439-016-1658-6

[…] chnical issues such as poor read mappability, GC bias, and batch effects between sequencing experiments (Teo et al. ). Many different algorithms have been devised based on read-depth methods, such as CODEX, Convex, Conifer, and XHMM (Amarasinghe et al. ; Fromer et al. ; Jiang et al. ; Krumm et al. ). Comparisons of CNV algorithms for exome data have shown that none of the algorithms performed well […]

library_books

Detection of Genomic Structural Variants from Next Generation Sequencing Data

2015
Front Bioeng Biotechnol
PMCID: 4479793
PMID: 26161383
DOI: 10.3389/fbioe.2015.00092

[…] he literature for this purpose including ExomeCNV (Sathirapongsasuti et al., ), CoNIFER (Krumm et al., ), CNV-seq (Xie and Tammi, ), XHMM (Fromer et al., ), and recently EXCAVATOR (Magi et al., ) and CODEX (Jiang et al., ). Notably, the method developed by Bansal and co-workers (Bansal et al., ) allows for the analysis of NGS data generated from small subsets of the exome, namely custom capture (C […]


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CODEX institution(s)
Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, USA; Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
CODEX funding source(s)
Supported by the National Institutes of Health (NIH) grant R01 HG006137 and P01 CA142538.

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