Control-FREEC enables automatic calculation of copy number and allelic content profiles from next generation sequencing data, and consequently predicts regions of genomic alteration such as gains, losses, and loss of heterozygosity (LOH).
Taking as input aligned reads, Control-FREEC constructs copy number and B-allele frequency profiles. The profiles are then normalized, segmented and analyzed in order to assign genotype status (copy number and allelic content) to each genomic region. When a matched normal sample is provided, Control-FREEC discriminates somatic from germline events.
Control-FREEC is able to analyze over-diploid tumor samples and samples contaminated by normal cells.
Low mappability regions can be excluded from the analysis using provided mappability tracks.
Publications:
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] PMID: 22155870.
Input for detection of copy number alterations (CNAs):
Aligned single-end, paired-end or mate-pair data in SAM, BAM, SAMtools pileup, Eland, BED, SOAP, arachne, psl (BLAT) and Bowtie formats. Control-FREEC accepts .GZ files.
Input for CNA+LOH detection:
Aligned reads in SAMtools pileup format. The file can be GZipped.
Output:
Regions of gains, lossed and LOH, copy number and BAF profiles.
Availability:
http://bioinfo.curie.fr/projects/freec/
Taking as input aligned reads, Control-FREEC constructs copy number and B-allele frequency profiles. The profiles are then normalized, segmented and analyzed in order to assign genotype status (copy number and allelic content) to each genomic region. When a matched normal sample is provided, Control-FREEC discriminates somatic from germline events.
Control-FREEC is able to analyze over-diploid tumor samples and samples contaminated by normal cells.
Low mappability regions can be excluded from the analysis using provided mappability tracks.
Publications:
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] PMID: 22155870.
Input for detection of copy number alterations (CNAs):
Aligned single-end, paired-end or mate-pair data in SAM, BAM, SAMtools pileup, Eland, BED, SOAP, arachne, psl (BLAT) and Bowtie formats. Control-FREEC accepts .GZ files.
Input for CNA+LOH detection:
Aligned reads in SAMtools pileup format. The file can be GZipped.
Output:
Regions of gains, lossed and LOH, copy number and BAF profiles.
Availability:
http://bioinfo.curie.fr/projects/freec/
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