Summary: CGHcall achieves high calling accuracy for array CGH data by effective use of breakpoint information from segmentation and by inclusion of several biological concepts that are ignored by existing algorithms. The algorithm is validated for simulated and verified real array CGH data. By incorporating more than three classes, CGHcall improves detection of single copy gains and amplifications. Moreover, it allows effective inclusion of chromosome arm information
International audienceAlthough Next Generation Sequencing technologies are becoming the new referenc...
Background: Array comparative genomic hybridization (aCGH) is a popular technique for detection of g...
In cancer research, prediction of time to death or relapse is important for a meaningful tumor clas...
CGHcall achieves high calling accuracy for array CGH data by effective use of breakpoint information...
Summary: CGHcall achieves high calling accuracy for array CGH data by effective use of breakpoint in...
Motivation: Many high-resolution array comparative genomic hybridization tumor profiles contain a wa...
Motivation: Genomic DNA regions are frequently lost or gained during tumor progression. Array Compar...
Developing effective methods for analyzing array-CGH data to detect chromosomal aberrations is very ...
In cancer research, prediction of time to death or relapse is important for a meaningful tumor class...
The aim of the study is comparative analysis of algorithms for identifying copy number variation in ...
Motivation: Genomic instability is one of the fundamental factors in tumorigenesis and tumor progres...
An algorithm to reduce multi-sample array CGH data from thousands of clones to tens or hundreds of c...
Abstract. The development of cancer is largely driven by the gain or loss of sub-sets of the genome,...
BACKGROUND: Array CGH (Comparative Genomic Hybridisation) is a molecular cytogenetic technique for t...
Abstract: An algorithm to reduce multi-sample array CGH data from thousands of clones to tens or hun...
International audienceAlthough Next Generation Sequencing technologies are becoming the new referenc...
Background: Array comparative genomic hybridization (aCGH) is a popular technique for detection of g...
In cancer research, prediction of time to death or relapse is important for a meaningful tumor clas...
CGHcall achieves high calling accuracy for array CGH data by effective use of breakpoint information...
Summary: CGHcall achieves high calling accuracy for array CGH data by effective use of breakpoint in...
Motivation: Many high-resolution array comparative genomic hybridization tumor profiles contain a wa...
Motivation: Genomic DNA regions are frequently lost or gained during tumor progression. Array Compar...
Developing effective methods for analyzing array-CGH data to detect chromosomal aberrations is very ...
In cancer research, prediction of time to death or relapse is important for a meaningful tumor class...
The aim of the study is comparative analysis of algorithms for identifying copy number variation in ...
Motivation: Genomic instability is one of the fundamental factors in tumorigenesis and tumor progres...
An algorithm to reduce multi-sample array CGH data from thousands of clones to tens or hundreds of c...
Abstract. The development of cancer is largely driven by the gain or loss of sub-sets of the genome,...
BACKGROUND: Array CGH (Comparative Genomic Hybridisation) is a molecular cytogenetic technique for t...
Abstract: An algorithm to reduce multi-sample array CGH data from thousands of clones to tens or hun...
International audienceAlthough Next Generation Sequencing technologies are becoming the new referenc...
Background: Array comparative genomic hybridization (aCGH) is a popular technique for detection of g...
In cancer research, prediction of time to death or relapse is important for a meaningful tumor clas...