Prediction of copy numbers and allelic content using deep-sequencing data


Control-FREEC is a tool for detection of copy-number changes and allelic imbalances (including LOH) using deep-sequencing data developed by the Bioinformatics Laboratory of Institut Curie (Paris).

Control-FREEC automatically computes, normalizes, segments copy number and beta allele frequency (BAF) profiles, then calls copy number alterations and LOH. The control (matched normal) sample is optional for whole genome sequencing data but mandatory for whole exome or targeted sequencing data. For whole genome sequencing data analysis, the program can also use mappability data (files created by GEM).

Starting from version 8.0, we provide a possibility to detect subclonal gains and losses and evaluate the likeliest average ploidy of the sample. Also, the evaluation procedure for the level of contamination by normal cells has been improved.

Input for CNA detection: aligned single-end, paired-end or mate-pair data in SAM, BAM, SAMtools pileup.
Control-FREEC accepts .GZ files. Support of Eland, BED, SOAP, arachne, psl (BLAT) and Bowtie formats has been discontinued starting from version 8.0.
Input for CNA+LOH detection: There are two options: (a) provide aligned reads in SAMtools pileup format. Files can be GZipped; (b) provide BAM files together with options "makePileup" and "fastaFile" (see How to create a config file?)
Output: Regions of gains, losses and LOH, copy number and BAF profiles.

Starting from Control-FREEC v5.0, the program can be used on exome-sequencing data. Starting from version 8.0, read counts is calculate be exon and not per window (set "window=0").

Starting from Control-FREEC v6.0, the user can use multiple threads to run Control-FREEC. 30x coverage data with a control (i.e., two pileup.gz files) will be fully processed (CNA and LOH info) in one hour using 6 threads.

Read about CNA detection part of Control-FREEC (simply FREEC) in Bioinformatics! (PDF, abstract)

Read about LOH detection part of Control-FREEC also in Bioinformatics! (PDF, abstract)

To cite please use:

Boeva V, Zinovyev A, Bleakley K, Vert JP, Janoueix-Lerosey I, Delattre O, Barillot E. (2011) Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization. Bioinformatics 2011; 27(2):268-9. PMID: 21081509.

Boeva V, Popova T, Bleakley K, Chiche P, Cappo J, Schleiermacher G, Janoueix-Lerosey I, Delattre O, Barillot E. (2011) Control-FREEC: a tool for assessing copy number and allelic content using next generation sequencing data. Bioinformatics. 2011 Dec 6. [Epub ahead of print] PubMed PMID: 22155870.

More information is available:


Download FREEC for Linux or Win32:

  1. Linux 32-bit: Download and unpack the archive (Linux). Build the programe (make).
  2. Linux 64-bit: Download and unpack the archive (Linux 64bit). Contains a binary version of FREEC.
  3. Starting from Control-FREEC v5.7 Windows is no longer supported. But you can still download Control-FREEC v5.6 for Windows 32-bit ( archive with a binary version (Win32) ) or contact me for support.

Download a test dataset for HCC1143 and HCC1143-BL (from Chiang et al., 2009) to test CNA predictions: (143M)

Download a test dataset (cancer, unpublished) to test LOH predictions: (1334 M)

Download mappability tracks up to 2 mismatches if you want to include mappability information for: hg19 (read length 35-76bp), hg19 (read length 100bp), hg18, hg17. You can also generate a mappability track for other genomes using GEM.

 Links to documentation and source code

 FREEC working group


The following members of the Control-FREEC working group are pleased to answer any question or address any concerns you may have with the Control-FREEC software:


This work was supported by grants from the Institut National de la Sante et de la Recherche Medicale, the Institut Curie, the Ligue Nationale contre le Cancer (Equipe labellisee and CIT program). We thank Joern Toedling for valuable discussion.

Last modified: Sep 2, 2011