Randomization in Laboratory Procedure Is Key to Obtaining Reproducible Microarray Results

The quality of gene expression microarray data has improved dramatically since the first arrays were introduced in the late 1990s. However, the reproducibility of data generated at multiple laboratory sites remains a matter of concern, especially for scientists who are attempting to combine and analyze data from public repositories. We have carried out a study in which a common set of RNA samples was assayed five times in four different laboratories using Affymetrix GeneChip arrays. We observed dramatic differences in the results across laboratories and identified batch effects in array processing as one of the primary causes for these differences. When batch processing of samples is confounded with experimental factors of interest it is not possible to separate their effects, and lists of differentially expressed genes may include many artifacts. This study demonstrates the substantial impact of sample processing on microarray analysis results and underscores the need for randomization in the laboratory as a means to avoid confounding of biological factors with procedural effects.     

Randomization Analysis of Incomplete Data in Some Basic Designs

The first two randomization moments of W = Tt.S.S./(Tt.S.S. + Error S.S.) are derived in case of (a) a completely randomized design with one observation missing using (I) Yates method of fitting constants and (II) the available observations only and in case of (b) a randomized block design in which one treatment is tested twice by mistake in a block and another treatment is not tested at all in that block using (I) all the available observations and (II) the data after deleting the observation due to the treatment tested by mistake in place of another treatment in a block. It is concluded that in each of the two cases for a completely randomized design, the F-test is unbiased whereas in each of the two cases for a randomized block design the F-test is in general not unbiased. However, if one treatment is tested twice by mistake in randomly chosen plots of some block, the F-test is unbiased in both cases for a randomized block design. For a completely randomized design the F-test is found to be a good approximation to the corresponding randomized test if N ≧ 80 in case (I) whereas in case (II) this approximation is of the same accuracy as that of case (I) if N ≧ 90. For a randomized block design it is seen that in case (I), the F-test provides a good approximation to the corresponding randomization test if v≧r≧7 and in case (II) this approximation is of the same accuracy if r≧6 and r(v-1)≧45. The analysis of several uniformity trial data shows that for values of “N” in the neighbourhood of 50 the agreement of the first two moments of “W” under the randomization theory and normal theory are reasonably close in all the four cases considered.     

Computer-Intensive Randomization in Systematics

There has been a sort of cottage industry in the development of randomization routines in systematics beginning with the bootstrap and the jackknife and, in a sense, culminating with various Monte Carlo routines that have been used to assess the performance of phylogenetic methods in limiting circumstances. These methods can be segregated into three basic areas of interest: measures of support such as bootstrap, jackknife, Permutation Tail Probability, T‐PTP, and MoJo; measures of how well independent data are correlated in a phylogenetic framework like PCP for coevolution and Manhattan Stratigraphic Measure (MSM) for stratigraphy; and simulation‐based Monte‐Carlo methods for ascertaining relative performance of optimality criteria or coding methods. Although one approach to assessing cospeciation questions has been the randomization of, for example, hosts and parasite trees, it is well established that in questions that are of a correlative type, the association themselves are what should be permuted. This has been applied to Brooks' parsimony analysis previously and here to the recent reconciled tree approach to these questions. Although it is debatable whether the extrinsic temporal position of a fossil can stand as refutation of intrinsic morphological character‐based cladograms, one can, nonetheless, determine the strength and significance of fit of stratigraphic data to a cladogram. The only method available in this regard that has been shown to not be biased by tree shape is the MSM and modifications of that. Another similar approach that is new is applied to evaluating the historical informativeness of base composition biases. Incongruence length difference tests too are essentially correlative in nature and comparing the behavior of “perceived” partitions to randomly determined partitions of the same size has become the standard for interpreting the relative conflict between differently acquired data. Unlike the foregoing, which make full use of the observed structure of the data, Monte Carlo methods require the input of parameters or of models and in that sense the results tend to be lacking in verisimilitude. Nonetheless, these kinds of questions seem to have been those most widely promulgated in our field. The well‐established theoretical proposition that parsimony has problems with adjacent long‐branches was of course illustrated through such methods, much to the concern and angst of systematists. That likelihood later was shown to perform worse than parsimony when those long branches might repel each other has generated less concern and angst. But then many such circumstances can be divined, like the “short‐branch‐mess” problem wherein likelihood has difficulty placing just a single long branch. Overall, then, in the interpretation of these or any other Monte Carlo issues it will be important to critically examine the structure of the modeled process and the scope of inferences that can be drawn therefrom. Modeling situations that are bound to yield results favorable to only one approach (such as unrealistic even splitting of ancestral populations at unrealistically predictable times in examination of the coding of polymorphic data) should be viewed with great caution. More to the point, since history is singular and not repeatable, the utility of statistical approaches may itself be dubious except in very special circumstances—most of the requirements for stochasticity and independence can never be met.     

参数连锁分析方法

通过拟合的数据资料,对目前最常用的参数型连锁分析方法进行了比较,为有针对性地选择连锁分析方法提供了依据。 Abstract：We present here two parametric statistics for linkage analysis ( linkage and genehunter).Using the simulated pedigrees, we introduced the usage of the two methods.     

非参数连锁分析

非参数连锁分析是进行复杂疾病连锁分析的有效手段,本文通过拟合的数据资料,对目前广泛使用的非参数型连锁分析方法进行了探讨,为今后有针对性的选择连锁分析方法提供依据。 Abstract:We present here four non- parametric statistics for linkage analysis (APM,SIBPAL,MAPMAKER-SIB and GENEHUNTER-NPL).Using the simulated pedigrees,we introduced the usage of these methods.     

非参数连锁分析

非参数连锁分析是进行复杂疾病连锁分析的有效手段,本通过拟合的数据资料,对目前广泛使用的非参数连锁分析方法进行了探讨,为今后有针对性的选择性连锁分析方法提供依据。     

一个DMD家系的Bayes分析和RFLP连锁分析

本文对一个DMD家系中先证者之妹的致病基因携带者风险用3种方法进行估计。单纯根据系谱分析,其风险为50%;以CPK值为条件概率作Bayes分析,其风险为25%;用RFLP连锁分析,推断其风险仅为5%。将RFLP连锁分析的结果作为又一个条件概率进行Bayes分析,其风险估计又进一步准确到不超过2%。三者结合,得到了最佳的结果。     

The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis

Background

The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.

Methods and Findings

We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).

Conclusions

We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes. Please see later in the article for the Editors'' Summary     

大豆遗传图谱的构建和分析

利用大豆栽培品种科丰1号和南农1138－2杂交得到的重组近交系NJRIKY,通过RFLP,SSR,RAPD和AFLP4种分子标记的遗传连锁分析,构建了包含24个连锁群,由792个遗传标记组成的大豆较高密度连锁图谱,该图谱覆盖2320．7cM,平均图距2．9cM,SSR标记的多态性较高,在基因组中的位置相对稳定,可以作为锚定标记,有利于连锁群的归并和不同图谱的比较整合;而AFLP标记对于增加图谱密度效率较高,但其容易出现聚集现象,从而造成连锁群上有很大的空隙（gap),另外,在连锁群中有21．7％的分子标记出现偏分离,该图谱为基因定位,比较基因组学和重要农艺性状的QTL定位等研究打下了基础。     

微卫星标记对资源猪群的遗传分析和连锁图谱构建

在猪数量性状位点的定位研究中,标记的使用和图谱的构建是很重要的。本研究从猪的第4、6、7、8和13染色体上选取39个微卫星标记,在来源于约克夏和梅山214头猪组成的资源群中,分析了遗传特征并构建了图谱。研究表明,平均等位基因数、平均观察杂合度(Ho)和平均多态信息含量(PIC)在F1和F2代中分别为:3.2,0.528,0.463和3.2,0.496,0.447。结果表明大多数微卫星标记位点表现为中高度杂合性。在资源群体中,平均有信息减数分裂数是217.4(44-316),而各染色体上两性平均图谱的长度分别是:172.3cM(SSC4),168.7cM(SSC6),191.7cM(SSC7),197.3cM(SSC8),178.3cM(SSC13)。与USDA-MARC的参考图谱相比,标记位点的顺序相同,但长度均较长。雌雄两性图谱相比,第4和第6染色体上雌性图谱长于雄性图谱;而在另外3条染色体上,则雄性图谱长于雌性图谱。结果显示了标记位点在资源猪群的遗传特征和遗传关系,其连锁图谱可用于今后的QTL定位。     

Genome-Wide Linkage Analysis of Cardiovascular Disease Biomarkers in a Large,Multigenerational Family

Given the importance of cardiovascular disease (CVD) to public health and the demonstrated heritability of both disease status and its related risk factors, identifying the genetic variation underlying these susceptibilities is a critical step in understanding the pathogenesis of CVD and informing prevention and treatment strategies. Although one can look for genetic variation underlying susceptibility to CVD per se, it can be difficult to define the disease phenotype for such a qualitative analysis and CVD itself represents a convergence of diverse etiologic pathways. Alternatively, one can study the genetics of intermediate traits that are known risk factors for CVD, which can be measured quantitatively. Using the latter strategy, we have measured 21 cardiovascular-related biomarkers in an extended multigenerational pedigree, the CARRIAGE family (Carolinas Region Interaction of Aging, Genes, and Environment). These biomarkers belong to inflammatory and immune, connective tissue, lipid, and hemostasis pathways. Of these, 18 met our quality control standards. Using the pedigree and biomarker data, we have estimated the broad sense heritability (H2) of each biomarker (ranging from 0.09–0.56). A genome-wide panel of 6,015 SNPs was used subsequently to map these biomarkers as quantitative traits. Four showed noteworthy evidence for linkage in multipoint analysis (LOD score ≥ 2.6): paraoxonase (chromosome 8p11, 21), the chemokine RANTES (22q13.33), matrix metalloproteinase 3 (MMP3, 17p13.3), and granulocyte colony stimulating factor (GCSF, 8q22.1). Identifying the causal variation underlying each linkage score will help to unravel the genetic architecture of these quantitative traits and, by extension, the genetic architecture of cardiovascular risk.     

两种常用数量性状连锁分析方法的原理和进展

在复杂性状疾病的家系连锁研究中,Haseman-Elston回归分析和方差组成模型是常用的两种数量性状连锁分析方法。前者主要针对同胞对的性状值差或和的平方进行回归分析;后者引用方差组成模型,将数量性状分解为遗传方差和环境方差,可估计二者对表型的影响。两种方法可应用于同胞对、核心家系或扩展家系,定位数量性状基因座。本文对这两种模型的原理、算法及其进展进行了综述,并给出了常用的统计软件包。 Abstract：In this article, we discussed two model-free methods for detecting genetic linkage for quantitative traits, Haseman-Elston regression approach and variance components approach. The former is a regression approach for detecting linkage based on the squared difference or squared sums in quantitative trait values of sib-pairs and their estimated marker IBD scores. The latter can jointly model covariate effects along with variance components, including genetic component and non-genetic sources of variability. We have outlined the model assumption, the algorithm and the extensions for the both methods.     

遗传标记与数量性状基因间连锁关系的分析

本文讨论标记基因与数量性状主基因连锁关系的一般分析方法,包括重组值的估计和有关遗传假设的测验。并以我们水稻遗传试验中两个具有互补和重叠作用的卷叶基因和一个矮秆基因试验结果的分析为例作了较详细的示范。     

Randomization and efficiency in Zelen's single-consent design

The "single-consent design" was devised by Zelen to circumvent the reluctance of some patients and physicians to participate in certain types of randomized clinical trials. Crucial to the validity of Zelen's design is randomized allocation of patients. Randomization theory is therefore the key theoretical base of the approach taken in this paper to an examination of the efficiency of this design.     

Genomewide Linkage Analysis of Celiac Disease in Finnish Families

Celiac disease (CD), or gluten-sensitive enteropathy, is a common multifactorial disorder resulting from intolerance to cereal prolamins. The only established genetic susceptibility factor is HLA-DQ, which appears to explain only part of the overall genetic risk. We performed a genomewide scan of CD in 60 Finnish families. In addition to strong evidence for linkage to the HLA region at 6p21.3 (Z(max)>5), suggestive evidence for linkage was found for six other chromosomal regions--1p36, 4p15, 5q31, 7q21, 9p21-23, and 16q12. We further analyzed the three most convincing regions--4p15, 5q31, and 7q21--by evaluation of dense marker arrays across each region and by analysis of an additional 38 families. Although multipoint analysis with dense markers provided supportive evidence (multipoint LOD scores 3.25 at 4p15, 1.49 at 5q31, and 1.04 at 7q21) for the initial findings, the additional 38 families did not strengthen evidence for linkage. The role that HLA-DQ plays was studied in more detail by analysis of DQB1 alleles in all 98 families. All but one patient carried one or two HLA-DQ risk alleles, and 65% of HLA-DQ2 carriers were affected. Our study indicates that the HLA region harbors a predominant CD-susceptibility locus in these Finnish families.     

基于贝叶斯统计的遗传连锁分析方法

贝叶斯学派是不同于经典数理统计的一个重要学派, 其发展的贝叶斯统计方法在现代科学的许多领域已有着广泛的应用。探讨了贝叶斯统计在遗传连锁分析中的应用, 包括遗传重组率的贝叶斯估计、遗传连锁的贝叶斯因子检验和基于马尔可夫链蒙特卡罗理论的遗传连锁图谱构建。用编制的SAS/IML程序进行了模拟研究和实例分析, 验证了贝叶斯方法在遗传连锁分析中的有效性和实用性。