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@article{Ha2012,
	Abstract = {Loss of heterozygosity (LOH) and copy number alteration (CNA) feature prominently in the somatic genomic landscape of tumours.  As such, karyotypic aberrations in cancer genomes have been studied extensively to discover novel oncogenes and tumour suppressor genes.   Advances in sequencing technology have enabled the cost-effective detection of tumour genome and transcriptome mutation events at single base pair resolution; however, computational methods for predicting segmental regions of LOH in this context are not yet fully explored.  Consequently, whole transcriptome, nucleotide-level resolution analysis of mono-allelic expression patterns associated with LOH has not yet been undertaken in cancer.  We developed a novel approach for inference of LOH from paired tumour/normal sequence data and applied it to a cohort of 23 triple negative breast cancer (TNBC) genomes.  Following extensive benchmarking experiments, we describe the nucleotide-resolution landscape of LOH in TNBC and assess the consequent effect of LOH on the transcriptomes of these tumours using RNA-seq derived measurements of allele-specific expression.  We show that the majority of mono-allelic expression in the transcriptomes of triple negative breast cancer can be explained by genomic regions of LOH, and establish a upper bound for mono-allelic expression that may be explained by other tumour-specific modifications such as epigenetics or mutations.  Mono-allelically expressed genes associated with LOH reveals that cell-cycle, homologous recombination and actin-cytoskeletal functions are putatively disrupted by LOH in TNBC.  Finally, we show how inference of LOH can be used to interpret allele frequencies of somatic mutations and postulate on temporal ordering of mutations in the evolutionary history of these tumours.  Together, this contribution provides robust methodology and data to support the inclusion of LOH in the comprehensive characterization and interpretation of cancer genomes from sequencing data.},
	Author = {Ha, Gavin and Roth, Andrew and Lai, Daniel and Bashashati, Ali and Ding, Jiarui and Goya, Rodrigo and Giuliany, Ryan and Rosner, Jamie and Oloumi, Arusha and Shumansky, Karey and Chin, Suet-Feung and Turashvili, Gulisa and Hirst, Martin and Caldas, Carlos and Marra, Marco A and Aparicio, Samuel and Shah, Sohrab P},
	Date-Added = {2012-08-28 16:13:50 -0700},
	Date-Modified = {2012-08-28 16:14:35 -0700},
	Doi = {10.1101/gr.137570.112},
	Eprint = {http://genome.cshlp.org/content/early/2012/05/21/gr.137570.112.full.pdf+html},
	Journal = {Genome Research},
	Month = {May},
	Number = {advanced online publication},
	Title = {Integrative analysis of genome-wide loss of heterozygosity and mono-allelic expression at nucleotide resolution reveals disrupted pathways in triple negative breast cancer},
	Url = {http://genome.cshlp.org/content/early/2012/05/21/gr.137570.112.abstract},
	Year = {2012},
	Bdsk-Url-1 = {http://genome.cshlp.org/content/early/2012/05/21/gr.137570.112.abstract},
	Bdsk-Url-2 = {http://dx.doi.org/10.1101/gr.137570.112}}

@article{Shah2012,
	Abstract = {Primary triple-negative breast cancers (TNBCs), a tumour type defined by lack of oestrogen receptor, progesterone receptor and ERBB2 gene amplification, represent approximately 16% of all breast cancers. Here we show in 104 TNBC cases that at the time of diagnosis these cancers exhibit a wide and continuous spectrum of genomic evolution, with some having only a handful of coding somatic aberrations in a few pathways, whereas others contain hundreds of coding somatic mutations. High-throughput RNA sequencing (RNA-seq) revealed that only approximately 36% of mutations are expressed. Using deep re-sequencing measurements of allelic abundance for 2,414 somatic mutations, we determine for the first time-to our knowledge-in an epithelial tumour subtype, the relative abundance of clonal frequencies among cases representative of the population. We show that TNBCs vary widely in their clonal frequencies at the time of diagnosis, with the basal subtype of TNBC showing more variation than non-basal TNBC. Although p53 (also known as TP53), PIK3CA and PTEN somatic mutations seem to be clonally dominant compared to other genes, in some tumours their clonal frequencies are incompatible with founder status. Mutations in cytoskeletal, cell shape and motility proteins occurred at lower clonal frequencies, suggesting that they occurred later during tumour progression. Taken together, our results show that understanding the biology and therapeutic responses of patients with TNBC will require the determination of individual tumour clonal genotypes.},
	Author = {Shah, S P and Roth, A and Goya, R and Oloumi, A and Ha, G and Zhao, Y and Turashvili, G and Ding, J and Tse, K and Haffari, G and Bashashati, A and Prentice, L M and Khattra, J and Burleigh, A and Yap, D and Bernard, V and McPherson, A and Shumansky, K and Crisan, A and Giuliany, R and Heravi-Moussavi, A and Rosner, J and Lai, D and Birol, I and Varhol, R and Tam, A and Dhalla, N and Zeng, T and Ma, K and Chan, S K and Griffith, M and Moradian, A and Cheng, S W and Morin, G B and Watson, P and Gelmon, K and Chia, S and Chin, S F and Curtis, C and Rueda, O M and Pharoah, P D and Damaraju, S and Mackey, J and Hoon, K and Harkins, T and Tadigotla, V and Sigaroudinia, M and Gascard, P and Tlsty, T and Costello, J F and Meyer, I M and Eaves, C J and Wasserman, W W and Jones, S and Huntsman, D and Hirst, M and Caldas, C and Marra, M A and Aparicio, S},
	Date-Added = {2012-08-28 14:39:56 -0700},
	Date-Modified = {2012-08-28 14:39:56 -0700},
	Doi = {10.1038/nature10933},
	Journal = {Nature},
	Month = {Jun},
	Number = {7403},
	Pages = {395-399},
	Pmid = {22495314},
	Title = {The clonal and mutational evolution spectrum of primary triple-negative breast cancers},
	Volume = {486},
	Year = {2012},
	Bdsk-Url-1 = {http://www.hubmed.org/display.cgi?uids=22495314},
	Bdsk-Url-2 = {http://dx.doi.org/10.1038/nature10933}}

@article{Benjamini,
	Abstract = {GC content bias describes the dependence between fragment count (read coverage) and GC content found in Illumina sequencing data. This bias can dominate the signal of interest for analyses that focus on measuring fragment abundance within a genome, such as copy number estimation (DNA-seq). The bias is not consistent between samples; and there is no consensus as to the best methods to remove it in a single sample. We analyze regularities in the GC bias patterns, and find a compact description for this unimodal curve family. It is the GC content of the full DNA fragment, not only the sequenced read, that most influences fragment count. This GC effect is unimodal: both GC-rich fragments and AT-rich fragments are underrepresented in the sequencing results. This empirical evidence strengthens the hypothesis that PCR is the most important cause of the GC bias. We propose a model that produces predictions at the base pair level, allowing strand-specific GC-effect correction regardless of the downstream smoothing or binning. These GC modeling considerations can inform other high-throughput sequencing analyses such as ChIP-seq and RNA-seq.},
	Author = {Benjamini, Yuval and Speed, Terence P},
	Date-Added = {2012-06-18 16:21:56 -0700},
	Date-Modified = {2012-06-18 16:21:56 -0700},
	Doi = {10.1093/nar/gks001},
	Journal = {Nucleic Acids Res},
	Journal-Full = {Nucleic acids research},
	Month = {May},
	Number = {10},
	Pages = {e72},
	Pmid = {22323520},
	Pst = {ppublish},
	Title = {Summarizing and correcting the GC content bias in high-throughput sequencing},
	Volume = {40},
	Year = {2012},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gks001}}

@article{Shah,
	Abstract = {MOTIVATION: Array comparative genomic hybridization (aCGH) is a pervasive
	technique used to identify chromosomal aberrations in human diseases,
	including cancer. Aberrations are defined as regions of increased
	or decreased DNA copy number, relative to a normal sample. Accurately
	identifying the locations of these aberrations has many important
	medical applications. Unfortunately, the observed copy number changes
	are often corrupted by various sources of noise, making the boundaries
	hard to detect. One popular current technique uses hidden Markov
	models (HMMs) to divide the signal into regions of constant copy
	number called segments; a subsequent classification phase labels
	each segment as a gain, a loss or neutral. Unfortunately, standard
	HMMs are sensitive to outliers, causing over-segmentation, where
	segments erroneously span very short regions. RESULTS: We propose
	a simple modification that makes the HMM robust to such outliers.
	More importantly, this modification allows us to exploit prior knowledge
	about the likely location of "outliers", which are often due to copy
	number polymorphisms (CNPs). By "explaining away" these outliers
	with prior knowledge about the locations of CNPs, we can focus attention
	on the more clinically relevant aberrated regions. We show significant
	improvements over the current state of the art technique (DNAcopy
	with MergeLevels) on previously published data from mantle cell lymphoma
	cell lines, and on published benchmark synthetic data augmented with
	outliers. AVAILABILITY: Source code written in Matlab is available
	from http://www.cs.ubc.ca/~sshah/acgh.},
	Author = {Shah, Sohrab P and Xuan, Xiang and DeLeeuw, Ron J and Khojasteh, Mehrnoush and Lam, Wan L and Ng, Raymond and Murphy, Kevin P},
	Date-Added = {2010-04-04 17:06:29 -0700},
	Date-Modified = {2011-07-26 10:26:53 -0700},
	Journal = {Bioinformatics},
	Journal-Full = {Bioinformatics (Oxford, England)},
	Mesh = {Artificial Intelligence; Chromosome Mapping; Computer Simulation; Gene Dosage; In Situ Hybridization, Fluorescence; Markov Chains; Models, Genetic; Models, Statistical; Oligonucleotide Array Sequence Analysis; Pattern Recognition, Automated; Polymorphism, Genetic; Sequence Alignment; Sequence Analysis, DNA; Systems Integration},
	Month = {Jul},
	Number = {14},
	Pages = {e431-9},
	Pmid = {16873504},
	Pst = {ppublish},
	Title = {Integrating copy number polymorphisms into array CGH analysis using a robust HMM},
	Volume = {22},
	Year = {2006}}
