Martin Morgan

Fred Hutchinson Cancer Research Center, Seattle, Washington, United States

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Publications (13)53.25 Total impact

  • Michael Lawrence, Martin Morgan
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    ABSTRACT: This paper reviews strategies for solving problems encountered when analyzing large genomic data sets and describes the implementation of those strategies in R by packages from the Bioconductor project. We treat the scalable processing, summarization and visualization of big genomic data. The general ideas are well established and include restrictive queries, compression, iteration and parallel computing. We demonstrate the strategies by applying Bioconductor packages to the detection and analysis of genetic variants from a whole genome sequencing experiment.
    09/2014;
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    ABSTRACT: VariantAnnotation is an R / Bioconductor (Gentleman et al., 2004) package for the exploration and annotation of genetic variants. Capabilities exist for reading, writing and filtering Variant Call Format (VCF) files. VariantAnnotation allows ready access to additional R / Bioconductor facilities for advanced statistical analysis, data transformation, visualization, and integration with diverse genomic resources. This package is implemented in R and available for download at the Bioconductor(1) web site. The package contains extensive help pages for individual functions, and a 'vignette' outlining typical work flows; it is made available under the open source 'Artistic-2.0' license. Version 1.9.38 was used in this manuscript. vobencha@fhcrc.org.
    Bioinformatics 03/2014; · 5.47 Impact Factor
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    ABSTRACT: Adipose tissue plays a role in obesity-related cancers via increased production of inflammatory factors, steroid hormones, and altered adipokines. The impact of weight loss on adipose-tissue gene expression may provide insights into pathways linking obesity with cancer risk. We conducted an ancillary study within a randomized trial of diet, exercise, or combined diet+exercise vs. control among overweight/obese postmenopausal women. In 45 women, subcutaneous adipose-tissue biopsies were performed at baseline and after 6 months and changes in adipose-tissue gene expression were determined by microarray with an emphasis on pre-specified candidate pathways, as well as by unsupervised clustering of >37,000 transcripts (Illumina). Analyses were conducted first by randomization group, and then by degree of weight change at 6-months in all women combined. At 6 months, diet, exercise and diet+exercise participants lost a mean of 8.8 kg, 2.5 kg, and 7.9 kg (all p<0.05 vs. no change in controls). There was no significant change in candidate-gene expression by intervention group. In analysis by weight-change category, greater weight loss was associated a decrease in 17β-hydroxysteroid dehydrogenase-1 (HSD17B1, p-trend<0.01) and leptin (LEP, p-trend<0.01) expression, and marginally significant increased expression of estrogen receptor-1 (ESR1, p-trend=0.08) and insulin-like growth factor binding protein-3 (IGFBP3, p-trend=0.08). Unsupervised clustering revealed 83 transcripts with statistically significant changes. Multiple gene-expression changes correlated with changes in associated serum biomarkers. Weight-loss was associated with changes in adipose-tissue gene expression after 6 months, particularly in two pathways postulated to link obesity and cancer, i.e., steroid-hormone metabolism and IGF signaling.
    Cancer Prevention Research 01/2013; · 4.89 Impact Factor
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    ABSTRACT: MYC-induced DNA damage is exacerbated in WRN-deficient cells, leading to replication stress and accelerated cellular senescence. To determine whether WRN deficiency impairs MYC-driven tumor development, we used both xenograft and autochthonous tumor models. Conditional silencing of WRN expression in c-MYC overexpressing non-small cell lung cancer xenografts impaired both tumor establishment and tumor growth. This inhibitory effect of WRN knockdown was accompanied by increased DNA damage, decreased proliferation, and tumor necrosis. In the Eμ-Myc mouse model of B-cell lymphoma, a germline mutation in the helicase domain of Wrn (Wrn(Δhel/Δhel)) resulted in a significant delay in emergence of lethal lymphomas, extending tumor-free survival by more than 30%. Analysis of preneoplastic B cells from Eμ-Myc Wrn mutant mice revealed increased DNA damage, elevation of senescence markers, and decreased proliferation in comparison with cells from age-matched Eμ-Myc mice. Immunohistochemical and global gene expression analysis of overt Eμ-Myc Wrn(Δhel/Δhel) lymphomas showed a marked increase in expression of the CDK inhibitor, p16(Ink4a), as well as elevation of TAp63, a known mediator of senescence. Collectively, these studies show that in the context of Myc-associated tumorigenesis, loss of Wrn amplifies the DNA damage response, both in preneoplastic and neoplastic tissue, engaging activation of tumor suppressor pathways. This leads to inhibition of tumor growth and prolonged tumor-free survival. Targeting WRN or its enzymatic function could prove to be an effective strategy in the treatment of MYC-associated cancers.
    Molecular Cancer Research 02/2012; 10(4):535-45. · 4.35 Impact Factor
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    ABSTRACT: Estrogen receptor (ER) remains one of the most important biomarkers for breast cancer subtyping and prognosis, and comparative genome hybridization has greatly contributed to the understanding of global genetic imbalance. The authors used single-nucleotide polymorphism (SNP) arrays to compare overall copy number aberrations (CNAs) as well as loss of heterozygosity (LOH) of the entire human genome in ER-positive and ER-negative breast carcinomas. DNA was extracted from frozen tumor sections of 21 breast carcinoma specimens and analyzed with a proprietary 50K XbaI SNP array. Copy number and LOH probability values were derived for each sample. Data were analyzed using bioinformatics and computational software, and permutation tests were used to estimate the significance of these values. There was a global increase in CNAs and LOH in ER-negative relative to ER-positive cancers. Gain of the long arm of chromosome 1 (1q) and 8q were the most obvious changes common in both subtypes: An increase in the chromosome 1 short arm (1p)/1q ratio was observed in ER-negative samples, and an increased 16p/16q ratio was observed in ER-positive samples. Significant CNAs (adjusted P<.05) in ER-negative relative to ER-positive tumors included 5q deletion, loss of 15q, and gain of 2p and 21q. Copy-neutral LOH (cnLOH) common to both ER-positive and ER-negative samples included 9p21, the p16 tumor suppressor locus, and 4q13, the RCHY1 (ring finger and CHY zinc finger domain-containing 1) oncogene locus. Of particular interest was an enrichment of 17q LOH among the ER-negative tumors, potentially suggesting breast cancer 1 gene (BRCA1) mutations. SNP array detected both genetic imbalances and cnLOH and was capable of discriminating ER-negative breast cancer from ER-positive breast cancer.
    Cancer 05/2011; 117(10):2024-34. · 5.20 Impact Factor
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    ABSTRACT: ShortRead is a package for input, quality assessment, manipulation and output of high-throughput sequencing data. ShortRead is provided in the R and Bioconductor environments, allowing ready access to additional facilities for advanced statistical analysis, data transformation, visualization and integration with diverse genomic resources. AVAILABILITY AND IMPLEMENTATION: This package is implemented in R and available at the Bioconductor web site; the package contains a 'vignette' outlining typical work flows.
    Bioinformatics 09/2009; 25(19):2607-8. · 5.47 Impact Factor
  • The American Journal of Human Genetics 08/2008; 83(1):135-9. · 11.20 Impact Factor
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    ABSTRACT: Recent studies have used dense markers to examine the human genome in ancestrally homogeneous populations for hallmarks of selection. No genomewide studies have focused on recently admixed groups--populations that have experienced admixing among continentally divided ancestral populations within the past 200-500 years. New World admixed populations are unique in that they represent the sudden confluence of geographically diverged genomes with novel environmental challenges. Here, we present a novel approach for studying selection by examining the genomewide distribution of ancestry in the genetically admixed Puerto Ricans. We find strong statistical evidence of recent selection in three chromosomal regions, including the human leukocyte antigen region on chromosome 6p, chromosome 8q, and chromosome 11q. Two of these regions harbor genes for olfactory receptors. Interestingly, all three regions exhibit deficiencies in the European-ancestry proportion.
    The American Journal of Human Genetics 10/2007; 81(3):626-33. · 11.20 Impact Factor
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    ABSTRACT: This paper reviews the central concepts and implementation of data structures and methods for studying genetics of gene expression with the GGtools package of Bioconductor. Illustration with a HapMap+expression dataset is provided. Availability: Package GGtools is part of Bioconductor 1.9 (http://bioconductor.org). Open source with Artistic License.
    Bioinformatics 03/2007; 23(4):522-3. · 5.47 Impact Factor
  • Seth Falcon, Martin Morgan, Robert Gentleman
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    Martin Morgan, Chao-Jen Wong
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    ABSTRACT: 1 Structures for genomic data: ExpressionSet Genomic data can be very complex, usually consisting of a number of different bits and pieces. In Bioconductor we have taken the approach that these pieces should be stored in a single structure to easily manage the data. The package Biobase contains standardized data structures to represent genomic data. The ExpressionSet class is designed to combine several different sources of informa-tion into a single convenient structure. An ExpressionSet can be manipulated (e.g., subsetted, copied), and is the input to or output of many Bioconductor functions. The data in an ExpressionSet consist of • assayData: Expression data from microarray experiments (assayData is used to hint at the methods used to access different data components, as we show below). • metadata: A description of the samples in the experiment (phenoData), metadata about the features on the chip or technology used for the experi-ment (featureData), and further annotations for the features, for example gene annotations from biomedical databases (annotation). • experimentData: A flexible structure to describe the experiment. The ExpressionSet class coordinates all of these data, so that you do not usually have to worry about the details. However, an ExpressionSet needs to be created in the first place, because it will be the starting point for many of the analyses using Bioconductor software. ExpressionSet instances are created in one of two ways. Often, an Expres-sionSet is the output of an R function. For instance, justRMA in the affy Biocon-ductor package reads in manufacturer CEL files and outputs an ExpressionSet.