Allele-Specific Copy Number Analysis of Tumors

Description

This repository provides the ASCAT R package that can be used to infer tumour purity, ploidy and allele-specific copy number profiles.

ASCAT is described in detail in: Allele-specific copy number analysis of tumors. Van Loo P et al. PNAS (2010).

This repository also contains the code underlying additional publication: Allele-specific multi-sample copy number segmentation. Ross EM, Haase K, Van Loo P & Markowetz F. Bioinformatics (2020).

Installation

devtools::install_github('VanLoo-lab/ascat/ASCAT')

Changes since v2.5.2

Major changes:

• Default penalty for both ASPCF (ascat.aspcf) and ASmultiPCF (ascat.asmultipcf) is now 70 (was 25).
• LogR correction (ascat.GCcorrect) can now be used to correct for both GC content (standard requirement) and replication timing (optional). Also, the correction method has been updated (it now uses a linear model with splines).
• Color scheme has been changed for CNA profiles:
  • Rounded profiles: TBD1 is the major allele and TBD2 is the minor allele.
  • Unrounded profiles: TBD3 is the total CN and TBD4 is the minor allele.

Minor changes:

• ascat.plotRawData and ascat.plotSegmentedData have an extra parameter (logr.y_values) to change Y scale for the logR track. Default is: c(-2,2), whereas previous plot were: c(-1,1).

New features in v3.0:

• New set of instructions, as part of the main ascat.prepareHTS function, to derive logR and BAF from high-throughput sequencing (HTS) data (WES, WGS & targeted sequencing). Briefly, alleleCounter is used to get allele counts at specific loci on a pair of tumour/normal (either BAM or CRAM files). This information is then converted into logR and BAF values, based on a similar method than in the Battenberg package. Although this method allows running ASCAT on different HTS data:
  • WES: we recommand providing a BED file covering sequenced regions of the genome.
  • WGS: we recommend running Battenberg for accurate clonal and subclonal allele-specific copy-number alteration calling. However, ASCAT can still be used to get a fast purity/ploidy fit (~30 minutes with 12 CPUs from BAMs to CNA profiles). To this end, we provide a set of files that can be used (see ReferenceFiles/WGS).
  • Targeted sequencing: data must be preprocessed using the ascat.preprocessTargSeq function to extract loci of interest. Then, such curated loci list may be used as part of the ascat.prepareHTS function.
  • For HTS data, gamma must be set to 1 in ascat.runASCAT.
• A new function to collect metrics of interest has been added: ascat.metrics.

Testing

We provide some scripts and input data in the ExampleData folder.

Reference files for logR correction

We provide scripts to generate correction files for any platform in the LogRcorrection folder.

Supported arrays without matched germline

Custom10k, IlluminaASA, IlluminaGSAv3, Illumina109k, IlluminaCytoSNP, IlluminaCytoSNP850k, Illumina610k, Illumina660k, Illumina700k, Illumina1M, Illumina2.5M, IlluminaOmni5, Affy10k, Affy100k, Affy250k_sty, Affy250k_nsp, AffyOncoScan, AffyCytoScanHD, AffySNP6, HumanCNV370quad, HumanCore12, HumanCoreExome24, HumanOmniExpress12 and IlluminaOmniExpressExome.

Misc

For more information about ASCAT and other projects of our group, please visit our website.