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Table 1 The key features of 12 methods

From: A systematic evaluation of copy number alterations detection methods on real SNP array and deep sequencing data

Method

Window size

Normalization

Segmentation

Contamination

Ploidy

BICseq

Manual

Ratio centralization (built-in)

Bayesian information criterion

No

No

CNVnorm

Manual

GC, smoothing, Ratio centralization (built-in)

Circular binary segmentation

Yes

Yes

FREEC

CV and Poisson distribution

GC, mappability, Ratio centralization (built-in)

LASSO and dynamic programming

Yes

No

CNV_seq

Gaussian Ratio and Geary-Hinkley transformation

Ratio centralization (manual)

Consecutive Overlapping windows

No

No

rSWseq

No need

Ratio centralization (manual)

Smith-Waterman

No

No

Varscan

Fixed length broke by the gap and significant change

Ratio centralization (manual)

Circular binary segmentation

No

No

CNVnator

Manual

GC

Mean shift algorithm

No

No

ReadDepth

Negative binomial

GC, mappability

Circular binary segmentation

No

No

RDXplorer

Manual

GC

Event wise testing

No

No

GPHMM

–

–

HMM

Yes

Yesa

GAP

–

–

Circular binary segmentation

Yes

Yes

OncoSNP

–

–

HMM

Yes

Yesa

  1. aThey don’t directly give the ploidy estimation in the output file, but through baseline shift and exact copy number results the ploidy is indirectly known