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public:clonet [2015/01/14 11:10]
public:clonet [2017/10/30 09:44] (current)
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-===== ASEQ fast allele-specific studies from next-generation sequencing data =====+ 
 + <span style="color:gray;font-size:200%;">CLONET: CLONality Estimate in Tumors</span> 
 ---- ----
-Single base level information from next-generation sequencing (NGSpotentially allow for the quantitative assessment of biological phenomena such as mosaicism or allele-specific features in healthy and diseased cells that have remained unexploredSuch studies often present with computationally challenging burdens that might hinder genome-wide investigations across large datasets that are now publicly available such as the 1,000 Genomes Project data and The Cancer Genome Atlas (TCGA). We present ASEQ, a tool to perform gene-level allele-specific expression (ASEanalysis from paired genomic and transcriptomic NGS data without requiring information from the paternal or maternal genome. ASEQ offers an easy-to-use set of functionalities that take full advantage of a fast computational engine by combining multi-threaded computation and high performing samtools APIs. ASEQ can be used to rapidly and reliably screen large NGS datasets for the identification of allele specific featuresIt can be integrated in any NGS pipeline and runs on computer systems with multiple CPUsCPUs with multiple coresor across clusters of machines and cloud computing platforms.+Cancer arises from initiating cells (clonesthat undergo intense evolutionary selection during disease progression and can be widely altered during treatment. The tumor cell evolutionary process may lead to subclonal divergence resulting in genetic and molecular heterogeneity. Computational approaches to establish maps of cancer evolution would assist in determining the progression status of each patient tumor and possibly inform treatment strategies. Technical challenges related to tumor DNA purity and cancer cell ploidy have been addressed but critical aspects remain for minimally aberrant or highly heterogeneous tumors.\\ 
 +Available tools all apply a global use of the genome data to infer tumor DNA purity and tumor ploidy. Global approaches are well-suited for tumor samples with fairly homogenous genomic aberrations (high ratio of clonal versus subclonal lesions). In the clinical setting where tumor samples might exhibit heterogeneity due to progression or subsequent to multiple lines of treatment and/or for tumor types that undergo complex structural changes, global approaches may prove sub-optimal as they undermine the genomic diversity.\\ 
 +CLONET belongs to a second generation of tools based on local (in contrast to globaloptimization where estimates of purity and ploidy are derived from few clonal events. CLONET exploits individuals’ genetic background by using the abundant germline heterozygous SNP (called //informative SNPs//) genotype data provided by whole genome sequence coverage to quantify the percentage of reads supporting the considered aberration. A closed-form solution relates aberrant reads with clonality status and allows propagating uncertainty due to sequencing. CLONET computes the clonality of somatic copy number changes, point mutations, and rearrangements in a coherent mathematical model enabling comparison across tumor types of the same aberration class and across different aberrations within the same tumor typeFinally, the temporal path along which the somatic aberrations originated is inferred from the composite frequencies at which they are observed to be clonal or subclonal in a single sample. CLONET allows harnessing NGS dataincluding whole genomewhole exome, and targeted sequencing, to determine the percentage of tumor cells harboring each mutation and to draft evolution charts.
-==== DOWNLOADS ==== 
-== Current version 1.1.==+{{ public:clonet_schema.png?750 |  CLONET Pipeline }}  
 +=== REFERENCES === 
 +Prandi et al.: **Unraveling the clonal hierarchy of somatic genomic aberrations**. //Genome Biology// 2014, **15**:439. 
 +=== BASIC USAGE === 
 +CLONET is a collection of R scripts that allows: 
 +  * computing global DNA admixture (1-purity) and ploidy of tumor DNA samples (each with matched normal sample) from sequencing data (WGS, WES, targeted) 
 +  * computing clonality of each somatic aberration, including somatic copy number aberrations, point mutations, and structural rearrangements 
 +  * nominatig the temporal relation among somatic aberrations and building evolution maps \\ 
 +CLONET scripts have the following common syntaxt: \\ 
 +  CLONET.scriptName.R <ConfigurationFile.R> 
 +Folders are organized as follows:\\ 
 +   -> CLONET.R  
 +   -> Docs 
 +   -> Examples 
 +   -> Functions 
 +   -> Tools 
 +CLONET.R is the main R script required to compute global DNA admixture, ploidy and clonality of segmented data.\\ 
 +The Docs folder contains this document.\\ 
 +The Examples folder contains a folder Small that includes a complete run of all the CLONET scripts.\\ 
 +The Functions folder contains all the functions used by CLONET.\\ 
 +The Tools folder contains R scripts to perform point mutations (PM) analysis, structural rearrangement (RR) analysis and tumor evolution path analysis.\\ 
 +CLONET requires Linux kernel >= 2.6.15. 
 +CLONET requires R >= 2.7 and the following packages, parallel, dgof, sets, and pso, igraph, reshape2. 
 +CLONET requires global folder names. 
 +CLONET recommends ASEQ tool to generate initial pileup analysis (binaries provided). 
 +=== COPYRIGHT  === 
 +Code by Davide Prandi\\ 
 +Laboratory of Computational Oncology (F. Demichelis)\\ 
 +Centre for Integrative Biology, University of Trento, Italy\\ 
 +email contacts: davide.prandi@unitn.it; demichelis@science.unitn.\\ 
 +CLONET is distributed under the MIT Licence. 
 +=== DOWNLOADS ===
-  * {{:aseq-v1.1.8-linux64.tar.gz|Linux 64 bit binary}} +  * {{:CLONET_20140806.zip|CLONET (for backward compatibility}} 
-  * {{:aseq-v1.1.8-win32.tar.gz|Windows 32 bit binary}} +  * {{:CLONET.v2.20171016.zip|CLONET v2 (version suggested)}} 
-  * {{:aseq-v1.1.8-source.tar.gz|Source files}} +  * {{:aseq-v1.1.7-linux32.tar.gz|ASEQ binaries (linux 32bit)}} 
-  * {{:aseq-examples.tar.gz|Examples}} +  * {{:aseq-v1.1.7-linux64.tar.gz|ASEQ binaries (linux 64bit)}}
-  * {{:aseq-annotation-files.tar.gz|Annotation Files}} +
-  * {{:Manual.pdf|Manual}}+