p-SAGE: 基因集合的参数统计分析方法

肿瘤的发生与发展通常是由重要的细胞通路表达水平的反常导致的．尽管目前已经有很多工作利用基因表达谱数据以及一些其他的先验知识来寻找那些与肿瘤相关的基因集合,但还是没有一个恰当的基因集合的统计学方法．大多数研究都是直接将单基因的检验方法直接应用到基因集合上来．提出了基因集合的参数统计分析方法( p-SAGE ),这个方法应用到大脑肿瘤的实验中,识别了许多显著的基因集合．一些新发现的基因集合是与信号转导和免疫相关的．这个简便有效的方法可以得出有生物学意义的结果．     

Lower Statistical Support with Larger Data Sets: Insights from the Ochrophyta Radiation

It is commonly assumed that increasing the number of characters has the potential to resolve evolutionary radiations. Here, we studied photosynthetic stramenopiles (Ochrophyta) using alignments of heterogeneous origin mitochondrion, plastid, and nucleus. Surprisingly while statistical support for the relationships between the six major Ochrophyta lineages increases when comparing the mitochondrion (6,762 sites) and plastid (21,692 sites) trees, it decreases in the nuclear (209,105 sites) tree. Statistical support is not simply related to the data set size but also to the quantity of phylogenetic signal available at each position and our ability to extract it. Here, we show that this ability for current phylogenetic methods is limited, because conflicting results were obtained when varying taxon sampling. Even though the use of a better fitting model improved signal extraction and reduced the observed conflicts, the plastid data set provided higher statistical support for the ochrophyte radiation than the larger nucleus data set. We propose that the higher support observed in the plastid tree is due to an acceleration of the evolutionary rate in one short deep internal branch, implying that more phylogenetic signal per position is available to resolve the Ochrophyta radiation in the plastid than in the nuclear data set. Our work therefore suggests that, in order to resolve radiations, beyond the obvious use of data sets with more positions, we need to continue developing models of sequence evolution that better extract the phylogenetic signal and design methods to search for genes/characters that contain more signal specifically for short internal branches.     

Characterization of Regional Left Ventricular Function in Nonhuman Primates Using Magnetic Resonance Imaging Biomarkers: A Test-Retest Repeatability and Inter-Subject Variability Study

Pre-clinical animal models are important to study the fundamental biological and functional mechanisms involved in the longitudinal evolution of heart failure (HF). Particularly, large animal models, like nonhuman primates (NHPs), that possess greater physiological, biochemical, and phylogenetic similarity to humans are gaining interest. To assess the translatability of these models into human diseases, imaging biomarkers play a significant role in non-invasive phenotyping, prediction of downstream remodeling, and evaluation of novel experimental therapeutics. This paper sheds insight into NHP cardiac function through the quantification of magnetic resonance (MR) imaging biomarkers that comprehensively characterize the spatiotemporal dynamics of left ventricular (LV) systolic pumping and LV diastolic relaxation. MR tagging and phase contrast (PC) imaging were used to quantify NHP cardiac strain and flow. Temporal inter-relationships between rotational mechanics, myocardial strain and LV chamber flow are presented, and functional biomarkers are evaluated through test-retest repeatability and inter subject variability analyses. The temporal trends observed in strain and flow was similar to published data in humans. Our results indicate a dominant dimension based pumping during early systole, followed by a torsion dominant pumping action during late systole. Early diastole is characterized by close to 65% of untwist, the remainder of which likely contributes to efficient filling during atrial kick. Our data reveal that moderate to good intra-subject repeatability was observed for peak strain, strain-rates, E/circumferential strain-rate (CSR) ratio, E/longitudinal strain-rate (LSR) ratio, and deceleration time. The inter-subject variability was high for strain dyssynchrony, diastolic strain-rates, peak torsion and peak untwist rate. We have successfully characterized cardiac function in NHPs using MR imaging. Peak strain, average systolic strain-rate, diastolic E/CSR and E/LSR ratios, and deceleration time were identified as robust biomarkers that could potentially be applied to future pre-clinical drug studies.     

A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime

Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks).     

Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive

The Quantitative Imaging Network (QIN), supported by the National Cancer Institute, is designed to promote research and development of quantitative imaging methods and candidate biomarkers for the measurement of tumor response in clinical trial settings. An integral aspect of the QIN mission is to facilitate collaborative activities that seek to develop best practices for the analysis of cancer imaging data. The QIN working groups and teams are developing new algorithms for image analysis and novel biomarkers for the assessment of response to therapy. To validate these algorithms and biomarkers and translate theminto clinical practice, algorithms need to be compared and evaluated on large and diverse data sets. Analysis competitions, or “challenges,” are being conducted within the QIN as a means to accomplish this goal. The QIN has demonstrated, through its leveraging of The Cancer Imaging Archive (TCIA), that data sharing of clinical images across multiple sites is feasible and that it can enable and support these challenges. In addition to Digital Imaging and Communications in Medicine (DICOM) imaging data, many TCIA collections provide linked clinical, pathology, and “ground truth” data generated by readers that could be used for further challenges. The TCIA-QIN partnership is a successful model that provides resources for multisite sharing of clinical imaging data and the implementation of challenges to support algorithm and biomarker validation.     

Biosorption with Algae: A Statistical Review

ABSTRACT

The state of the art in the field of biosorption using algae as biomass is reviewed. The available data of maximum sorption uptake (q_max) and biomass-metal affinity (b) for Cd^{2 +}, Cu^{2 +}, Ni^{2 +}, Pb^{2 +} and Zn^{2 +} were statistically analyzed using 37 different algae (20 brown algae, 9 red algae and 8 green algae). Metal biosorption research with algae has used mainly brown algae in pursuit of treatments, which improve its sorption uptake. The information available in connection with multimetallic systems is very poor. Values of q_max were close to 1 mmol/g for copper and lead and smaller for the other metals. Metal recovery performance was worse for nickel and zinc, but the number of samples for zinc was very small. All the metals except lead present a similar affinity for brown algae. The difference in the behavior of lead may be due to a different uptake mechanism. Brown algae stand out as very good biosorbents of heavy metals. The best performer for metal biosorption is lead.     

Statistical Analysis of Nonrectangular Family Data

MINQUE (Minimum Norm Quadratic Unbiased Estimators) theory is applied to the problem of estimation of variance components in family data (siblings) with variable family size. Using this approach, the traditional iterative maximum likelihood estimators are shown to be asymptotically normal, even though the data come from non-identical parent distributions. Asymptotic expressions are also obtained for the variance of the MINQUE estimators which hold even if the data are decidedly non-normal (e.g. a mixture of normals). In the case of normal data, exact small-sample variance estimates are derived. Simulations demonstrate the fast rate of convergence to asymptotic properties as the number of families increases. These desirable qualities suggest that the easy to compute MINQUE class of estimators may provide a useful alternative method for modelling familial aggregation.     

Three-dimensional Imaging Methods for Quantitative Analysis of Facial Soft Tissues and Skeletal Morphology in Patients with Orofacial Clefts: A Systematic Review

Background

Current guidelines for evaluating cleft palate treatments are mostly based on two-dimensional (2D) evaluation, but three-dimensional (3D) imaging methods to assess treatment outcome are steadily rising.

Objective

To identify 3D imaging methods for quantitative assessment of soft tissue and skeletal morphology in patients with cleft lip and palate.

Data sources

Literature was searched using PubMed (1948–2012), EMBASE (1980–2012), Scopus (2004–2012), Web of Science (1945–2012), and the Cochrane Library. The last search was performed September 30, 2012. Reference lists were hand searched for potentially eligible studies. There was no language restriction.

Study selection

We included publications using 3D imaging techniques to assess facial soft tissue or skeletal morphology in patients older than 5 years with a cleft lip with/or without cleft palate. We reviewed studies involving the facial region when at least 10 subjects in the sample size had at least one cleft type. Only primary publications were included.

Data extraction

Independent extraction of data and quality assessments were performed by two observers.

Results

Five hundred full text publications were retrieved, 144 met the inclusion criteria, with 63 high quality studies. There were differences in study designs, topics studied, patient characteristics, and success measurements; therefore, only a systematic review could be conducted. Main 3D-techniques that are used in cleft lip and palate patients are CT, CBCT, MRI, stereophotogrammetry, and laser surface scanning. These techniques are mainly used for soft tissue analysis, evaluation of bone grafting, and changes in the craniofacial skeleton. Digital dental casts are used to evaluate treatment and changes over time.

Conclusion

Available evidence implies that 3D imaging methods can be used for documentation of CLP patients. No data are available yet showing that 3D methods are more informative than conventional 2D methods. Further research is warranted to elucidate it.

Systematic review registration

International Prospective Register of Systematic Reviews, PROSPERO CRD42012002041     

Quantitative Network Measures as Biomarkers for Classifying Prostate Cancer Disease States: A Systems Approach to Diagnostic Biomarkers

Identifying diagnostic biomarkers based on genomic features for an accurate disease classification is a problem of great importance for both, basic medical research and clinical practice. In this paper, we introduce quantitative network measures as structural biomarkers and investigate their ability for classifying disease states inferred from gene expression data from prostate cancer. We demonstrate the utility of our approach by using eigenvalue and entropy-based graph invariants and compare the results with a conventional biomarker analysis of the underlying gene expression data.     

定量蛋白质组学分析方法及应用

蛋白质组学经历了近10年的发展,现在已经初具规模。但是由于它是动态地观察生物体不断变化的所有蛋白质,所以技术难度非常之大。为使研究简化并更具针对性,人们着重进行比较蛋白质组学的研究。为了具体量化这些蛋白质的变化产生了定量蛋白质组学,近几年各种标记技术的进步使得该学科得以迅猛发展。     

A Statistical Review of Carcinoma of the Lip

Among 3166 patients with microscopically confirmed squamous cell carcinoma of the lip registered at The Ontario Cancer Treatment and Research Foundation''s Regional Clinics in 1938-1955, the five-year crude survival rate was 65%, and the five-year net survival rate 89%. Survival was influenced by age, site and size of primary lesion, local and regional invasion, long delay, and treatment method. The initial treatment appeared to control the primary lesion in 84% of cases and involved lymph nodes in 58%. The net survival rates improved over the survey period. Findings confirm the usefulness of the proposed TNM staging.     

Ectopic Pregnancy: A Statistical Review of 360 Cases

In a statistical analysis of 360 cases of ectopic pregnancy admitted to the Montreal General Hospital over a 20-year period ending December 1964, ectopic gestation occurred once in every 83 admissions to the gynecological service. This incidence has remained constant over the years. Only one out of four patients had had more than one child and 30% of the patients had absolute or relative infertility. Diagnosis was delayed or not made in 58 patients. There was evidence that neurogenic factors play a role in the etiology of ectopic gestation. Ten per cent of the patients had had a previous operation for the same condition. Symptomatology is variable and the possibility of ectopic pregnancy must never be overlooked in a woman of child-bearing age. Once the diagnosis is made the treatment is early operation. The morbidity rate in this series was 28% and there was one death.     

General Statistical Issues in the Analysis of Pedigree Data

When analysing pedigree data, it is just as important to detect deficiencies in the fitting and application of the current model as to be able to specify the model, estimate its parameters and test appropriate hypotheses. Some of the statistical issues that arise in the fitting and application of genetic models to pedigree data are discussed in this paper. A particular set of data and a non-controversial characteristic have been chosen to highlight these issues.