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. 2016 Dec 8:56:15.9.1-15.9.17.
doi: 10.1002/cpbi.17.

ascatNgs: Identifying Somatically Acquired Copy-Number Alterations from Whole-Genome Sequencing Data

Affiliations

ascatNgs: Identifying Somatically Acquired Copy-Number Alterations from Whole-Genome Sequencing Data

Keiran M Raine et al. Curr Protoc Bioinformatics. .

Abstract

We have developed ascatNgs to aid researchers in carrying out Allele-Specific Copy number Analysis of Tumours (ASCAT). ASCAT is capable of detecting DNA copy number changes affecting a tumor genome when comparing to a matched normal sample. Additionally, the algorithm estimates the amount of tumor DNA in the sample, known as Aberrant Cell Fraction (ACF). ASCAT itself is an R-package which requires the generation of many file types. Here, we present a suite of tools to help handle this for the user. Our code is available on our GitHub site (https://github.com/cancerit). This unit describes both 'one-shot' execution and approaches more suitable for large-scale compute farms. © 2016 by John Wiley & Sons, Inc.

Keywords: cancer; copy-number; sequencing; somatic.

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Figures

Figure 15.9.1
Figure 15.9.1
ascatNgs processing workflow. Individual components are executed automatically when run without the -p/-i options. The workflow automatically recovers to the last successful point on restart if killed for any reason. Please see Alternate Protocol 2 for further detail.
Figure 15.9.2
Figure 15.9.2
A cancer sample pair with very few copy number aberrations and an overall ploidy of close to 2. Sunrise plots (A) tend to have banding of the decreasing intensity blue ‘good’ solution regions around multiples of the correct ploidy.
Figure 15.9.3
Figure 15.9.3
A cancer sample pair with an overall ploidy of 4. Here we see that the sunrise plot (A) only offers one solution in the expected window of purity/ploidy.
Figure 15.9.4
Figure 15.9.4
A cancer sample pair with an overall copy loss. Note the banding of multiples of the ploidy in the sunrise plot (A).
Figure 15.9.5
Figure 15.9.5
A poorly resolved ‘sunrise’ plot with incorrect selection of ACF/Ploidy. Note multiple dark blue regions of similar color depth. In this situation, the correct solution is generally the region with the lower ploidy.
Figure 15.9.6
Figure 15.9.6
Repeat of data presented in Fig. 15.9.5 after refitting with purity = 0.4 and ploidy = 2.
Figure 15.9.7
Figure 15.9.7
A ‘sunrise’ plot where it has not been possible to select a best solution. Note the absence of the green cross.

References

Literature Cited

    1. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, McVean G, et al. The variant call format and VCFtools. Bioinformatics. 2011;27:2156–2158. doi: 10.1093/bioinformatics/btr330. - DOI - PMC - PubMed
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Internet Resources

    1. https://github.com/cancerit

      Repository for Wellcome Trust Sanger Institute Cancer Genome Project public projects.

    1. http://cancerit.github.io/ascatNgs/

      ascatNgs Web site, linking to repository.

    1. https://www.crick.ac.uk/research/a-z-researchers/researchers-v-y/peter-van-loo/software/

      ASCAT Web site.

    1. https://github.com/Crick-CancerGenomics/ascat

      Repository for the core ASCAT algorithm.