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Mutational signatures in colon cancer.
ObjectiveRecently, many tumor sequencing studies have inferred and reported on mutational signatures, short nucleotide patterns at which particular somatic base substitutions appear more often. A number of signatures reflect biological processes in the patient and factors associated with cancer risk. Our goal is to infer mutational signatures appearing in colon cancer, a cancer for which environmental risk factors vary by cancer subtype, and compare the signatures to those in adult stem cells from normal colon. We also compare the mutational signatures to others in the literature.ResultsWe apply a probabilistic mutation signature model to somatic mutations previously reported for six adult normal colon stem cells and 431 colon adenocarcinomas. We infer six mutational signatures in colon cancer, four being specific to tumors with hypermutation. Just two signatures explained the majority of mutations in the small number of normal aging colon samples. All six signatures are independently identified in a series of 295 Chinese colorectal cancers
Linearized Asymptotic Stability for Fractional Differential Equations
We prove the theorem of linearized asymptotic stability for fractional
differential equations. More precisely, we show that an equilibrium of a
nonlinear Caputo fractional differential equation is asymptotically stable if
its linearization at the equilibrium is asymptotically stable. As a consequence
we extend Lyapunov's first method to fractional differential equations by
proving that if the spectrum of the linearization is contained in the sector
\{\lambda \in \C : |\arg \lambda| > \frac{\alpha \pi}{2}\} where
denotes the order of the fractional differential equation, then the equilibrium
of the nonlinear fractional differential equation is asymptotically stable
Non-specific filtering of beta-distributed data.
BackgroundNon-specific feature selection is a dimension reduction procedure performed prior to cluster analysis of high dimensional molecular data. Not all measured features are expected to show biological variation, so only the most varying are selected for analysis. In DNA methylation studies, DNA methylation is measured as a proportion, bounded between 0 and 1, with variance a function of the mean. Filtering on standard deviation biases the selection of probes to those with mean values near 0.5. We explore the effect this has on clustering, and develop alternate filter methods that utilize a variance stabilizing transformation for Beta distributed data and do not share this bias.ResultsWe compared results for 11 different non-specific filters on eight Infinium HumanMethylation data sets, selected to span a variety of biological conditions. We found that for data sets having a small fraction of samples showing abnormal methylation of a subset of normally unmethylated CpGs, a characteristic of the CpG island methylator phenotype in cancer, a novel filter statistic that utilized a variance-stabilizing transformation for Beta distributed data outperformed the common filter of using standard deviation of the DNA methylation proportion, or its log-transformed M-value, in its ability to detect the cancer subtype in a cluster analysis. However, the standard deviation filter always performed among the best for distinguishing subgroups of normal tissue. The novel filter and standard deviation filter tended to favour features in different genome contexts; for the same data set, the novel filter always selected more features from CpG island promoters and the standard deviation filter always selected more features from non-CpG island intergenic regions. Interestingly, despite selecting largely non-overlapping sets of features, the two filters did find sample subsets that overlapped for some real data sets.ConclusionsWe found two different filter statistics that tended to prioritize features with different characteristics, each performed well for identifying clusters of cancer and non-cancer tissue, and identifying a cancer CpG island hypermethylation phenotype. Since cluster analysis is for discovery, we would suggest trying both filters on any new data sets, evaluating the overlap of features selected and clusters discovered
A total production index for Washington, D.C.
A heavy concentration of services characterizes the economy of the District of Columbia. Growth in the D.C. economy, although usually heavily insulated from the swings of the U.S. business cycle, varies in intensity and, sometimes, in direction. Now, a new monthly index of total production provides a timely measure of services and goods production in Washington, D.C.Industrial production index ; Federal Reserve District, 5th
An evaluation of processing methods for HumanMethylation450 BeadChip data
BackgroundIllumina's HumanMethylation450 arrays provide the most cost-effective means of high-throughput DNA methylation analysis. As with other types of microarray platforms, technical artifacts are a concern, including background fluorescence, dye-bias from the use of two color channels, bias caused by type I/II probe design, and batch effects. Several approaches and pipelines have been developed, either targeting a single issue or designed to address multiple biases through a combination of methods. We evaluate the effect of combining separate approaches to improve signal processing.ResultsIn this study nine processing methods, including both within- and between- array methods, are applied and compared in four datasets. For technical replicates, we found both within- and between-array methods did a comparable job in reducing variance across replicates. For evaluating biological differences, within-array processing always improved differential DNA methylation signal detection over no processing, and always benefitted from performing background correction first. Combinations of within-array procedures were always among the best performing methods, with a slight advantage appearing for the between-array method Funnorm when batch effects explained more variation in the data than the methylation alterations between cases and controls. However, when this occurred, RUVm, a new batch correction method noticeably improved reproducibility of differential methylation results over any of the signal-processing methods alone.ConclusionsThe comparisons in our study provide valuable insights in preprocessing HumanMethylation450 BeadChip data. We found the within-array combination of Noobâ+âBMIQ always improved signal sensitivity, and when combined with the RUVm batch-correction method, outperformed all other approaches in performing differential DNA methylation analysis. The effect of the data processing method, in any given data set, was a function of both the signal and noise
The ARGUS Vertex Trigger
A fast second level trigger has been developed for the ARGUS experiment which
recognizes tracks originating from the interaction region. The processor
compares the hits in the ARGUS Micro Vertex Drift Chamber to 245760 masks
stored in random access memories. The masks which are fully defined in three
dimensions are able to reject tracks originating in the wall of the narrow
beampipe of 10.5\,mm radius.Comment: gzipped Postscript, 27 page
Celiac Disease: Role of the Epithelial Barrier
In celiac disease (CD) a T-cellâmediated response to gluten is mounted in
genetically predisposed individuals, resulting in a malabsorptive enteropathy
histologically highlighted by villous atrophy and crypt hyperplasia. Recent
data point to the epithelial layer as an under-rated hot spot in celiac
pathophysiology to date. This overview summarizes current functional and
genetic evidence on the role of the epithelial barrier in CD, consisting of
the cell membranes and the apical junctional complex comprising sealing as
well as ion and water channel-forming tight junction proteins and the adherens
junction. Moreover, the underlying mechanisms are discussed, including
apoptosis of intestinal epithelial cells, biology of intestinal stem cells,
alterations in the apical junctional complex, transcytotic uptake of gluten
peptides, and possible implications of a defective epithelial polarity.
Current research is directed toward new treatment options for CD that are
alternatives or complementary therapeutics to a gluten-free diet. Thus,
strategies to target an altered epithelial barrier therapeutically also are
discussed
Optimal sequential fingerprinting: Wald vs. Tardos
We study sequential collusion-resistant fingerprinting, where the
fingerprinting code is generated in advance but accusations may be made between
rounds, and show that in this setting both the dynamic Tardos scheme and
schemes building upon Wald's sequential probability ratio test (SPRT) are
asymptotically optimal. We further compare these two approaches to sequential
fingerprinting, highlighting differences between the two schemes. Based on
these differences, we argue that Wald's scheme should in general be preferred
over the dynamic Tardos scheme, even though both schemes have their merits. As
a side result, we derive an optimal sequential group testing method for the
classical model, which can easily be generalized to different group testing
models.Comment: 12 pages, 10 figure
Using DNA Methylation Patterns to Infer Tumor Ancestry
Background: Exactly how human tumors grow is uncertain because serial observations are impractical. One approach to reconstruct the histories of individual human cancers is to analyze the current genomic variation between its cells. The greater the variations, on average, the greater the time since the last clonal evolution cycle (ââa molecular clock hypothesisââ). Here we analyze passenger DNA methylation patterns from opposite sides of 12 primary human colorectal cancers (CRCs) to evaluate whether the variation (pairwise distances between epialleles) is consistent with a single clonal expansion after transformation. Methodology/Principal Findings: Data from 12 primary CRCs are compared to epigenomic data simulated under a single clonal expansion for a variety of possible growth scenarios. We find that for many different growth rates, a single clonal expansion can explain the population variation in 11 out of 12 CRCs. In eight CRCs, the cells from different glands are all equally distantly related, and cells sampled from the same tumor half appear no more closely related than cells sampled from opposite tumor halves. In these tumors, growth appears consistent with a single ââsymmetricâ â clonal expansion. In three CRCs, the variation in epigenetic distances was different between sides, but this asymmetry could be explained by a single clonal expansion with one region of a tumor having undergone more cell division than the other. The variation in one CRC was complex and inconsistent with a simple single clonal expansion
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