Nonparametric analysis of replicated microarray experiments

Microarrays are part of a new class of biotechnologies, which allow the monitoring of expression levels of thousands of genes simultaneously. In microarray data analysis, the comparison of gene expression profiles with respect to different conditions and the selection of biologically interesting genes are crucial tasks. Multivariate statistical methods have been applied to analyze these large data sets. To identify genes with altered expression under two experimental conditions, we propose a nonparametric statistical approach. Specifically, we propose estimating the distributions of a t-type statistic and its null statistic, using kernel methods. A comparison of these two distributions by means of a likelihood ratio test can identify genes with significantly changed expressions. A new method to provide more stable estimates of tail probabilities is proposed, as well as a method for the calculation of the cut-off point and the acceptance region. The methodology is applied to a leukaemia data set containing expression levels of 7129 genes, and is compared with normal mixture model and the traditional t-test.

Occupational risk factors for prostate cancer in an area of former coal, iron, and steel industries in Germany. Part 1: Results from a study performed in the 1980s

Prostate cancer is the most frequent occurring malignancy in men in many Western countries. Unfortunately, only a few studies on occupational risk factors have been published. Thus, the aim of this study was to investigate possible occupational risk factors in a former center of coal, iron, and steel industries the greater Dortmund area, located in the western part of Germany. In three local departments of urology, a total of 238 prostate cancer cases and 414 patients with benign prostatic hyperplasia as controls were requested to provide information for all jobs ever performed for 6 mo or longer. Jobs performed less than 10 yr prior to diagnosis were excluded from the analysis due to the latency of prostate cancer. In addition, data on smoking habits and age were obtained. Analysis of data was performed by means of logistic regression. Hard coal miners and, based on fewer cases, painters, stratified by age, showed a significantly elevated prostate cancer risk. Smoking history did not influence prostate cancer risk. The causes of the observed increased prostate cancer risk in hard coal miners cannot be explained by merely the risk factor "male sexual hormones." In former decades, underground hard coal miners were exposed to high concentrations of dust and different xenobiotics such as hydraulic oils. Surprisingly, in a study performed about a decade later in the same area, prostate cancer risk in underground hard coal miners was found to be reduced. However, exposure to colorants was associated with an increased prostate cancer risk.

Retention time alignment algorithms for LC/MS data must consider non-linear shifts

MOTIVATION

Proteomics has particularly evolved to become of high interest for the field of biomarker discovery and drug development. Especially the combination of liquid chromatography and mass spectrometry (LC/MS) has proven to be a powerful technique for analyzing protein mixtures. Clinically orientated proteomic studies will have to compare hundreds of LC/MS runs at a time. In order to compare different runs, sophisticated preprocessing steps have to be performed. An important step is the retention time (rt) alignment of LC/MS runs. Especially non-linear shifts in the rt between pairs of LC/MS runs make this a crucial and non-trivial problem.

RESULTS

For the purpose of demonstrating the particular importance of correcting non-linear rt shifts, we evaluate and compare different alignment algorithms. We present and analyze two versions of a new algorithm that is based on regression techniques, once assuming and estimating only linear shifts and once also allowing for the estimation of non-linear shifts. As an example for another type of alignment method we use an established alignment algorithm based on shifting vectors that we adapted to allow for correcting non-linear shifts also. In a simulation study, we show that rt alignment procedures that can estimate non-linear shifts yield clearly better alignments. This is even true under mild non-linear deviations.

AVAILABILITY

R code for the regression-based alignment methods and simulated datasets are available at http://www.statistik.tu-dortmund.de/genetik-publikationen-alignment.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Bladder cancer and occupational exposures in North Rhine-Westphalia, Germany

The relationship between exposure to carcinogenic substances and development of bladder cancer was assessed from a case-control study conducted in North Rhine-Westphalia, Germany. The study consisted of 156 cases with bladder cancer and 336 controls with prostate cancer. The primary focus was the role of polycyclic aromatic hydrocarbons (PAHs), since most individuals were considered exposed mainly to substances in this group. Data were collected from male patients who had applied for cancer rehabilitation treatment. Nominally significant smoking-adjusted odds ratio (OR) estimates were obtained for frequent exposures to bitumen (OR = 2.92, 95% CI 1.32-6.48) and tar (OR = 2.09, 95% CI 1.04-4.21) and an ever exposure to paints (OR = 1.69, 95% CI 1.10-2.61). A frequent exposure to pitch showed a non-significant elevated risk (OR = 3.06, 95% CI 0.77-12.10).

Pilot study of the Human Proteome Organisation Brain Proteome Project: Applying different 2-DE techniques to monitor proteomic changes during murine brain development

The Human Proteome Organisation Brain Proteome Project aims at coordinating neuroproteomic activities with respect to analysis of development, aging, and evolution in human and mice and at analysing normal aging processes as well as neurodegenerative diseases. Our group participated in the mouse pilot study of this project using two different 2-DE systems, to find out the optimal conditions for comprehensive gel-based differential proteome analysis. Besides the assessment of the best methodical conditions the question of "How many biological replicate analyses have to be performed to get reliable statistically validated results?" was addressed. In total 420 differences were detected in all analyses. Both 2-DE methods were found to be suitable for comprehensive differential proteome analysis. Nevertheless, each of the methods showed substantial advantages and disadvantages resulting in the fact that modification of both systems is essential. From our results we can draw the conclusions that for the future optimal quantitative differential gel-based brain proteome analyses the sample preparation has to be slightly changed, the resolution of the first as well as the second dimension has to be advanced, the number of experiments has to be increased and that the 2D-DIGE system should be applied.

Statistics for Proteomics: A Review of Tools for Analyzing Experimental Data

Most proteomics experiments make use of 'high throughput' technologies such as 2-DE, MS or protein arrays to measure simultaneously the expression levels of thousands of proteins. Such experiments yield large, high-dimensional data sets which usually reflect not only the biological but also technical and experimental factors. Statistical tools are essential for evaluating these data and preventing false conclusions. Here, an overview is given of some typical statistical tools for proteomics experiments. In particular, we present methods for data preprocessing (e.g. calibration, missing values estimation and outlier detection), comparison of protein expression in different groups (e.g. detection of differentially expressed proteins or classification of new observations) as well as the detection of dependencies between proteins (e.g. protein clusters or networks). We also discuss questions of sample size planning for some of these methods.

A Renewed Approach to the Nonparametric Analysis of Replicated Microarray Experiments

DNA-microarrays find broad employment in biochemical research. This technology allows the monitoring of the expression levels of thousands of genes at the same time. Often, the goal of a microarray study is to find differentially expressed genes in two different types of tissue, for example normal and cancerous. Multiple hypothesis testing is a useful statistical tool for such studies. One approach using multiple hypothesis testing is nonparametric analysis for replicated microarray experiments. In this paper we present an improved version of this method. We also show how p-values are calculated for all significant genes detected with this testing procedure. All algorithms were implemented in an R-package, and instructions on it's use are included. The package can be downloaded at http://www.statistik.unidortmund.de/de/content/einrichtungen/lehrstuehle/personen/jung.html

Non-invasive detection of colorectal tumours by the combined application of molecular diagnosis and the faecal occult blood test

The treatment of early-stage tumours decreases the overall mortality of colorectal tumour patients. In this retrospective study we determined the sensitivity and the specificity of the faecal occult blood test (FOBT) and the molecular diagnosis (MD). We analysed 57 stool samples from patients with colorectal carcinomas for the presence of occult blood using a standard FOBT and for alterations in the three different tumour relevant markers APC, BAT26 and L-DNA. Stool samples from 44 control donors were analysed to determine the specificity of the applied methods. Twenty-nine (51%; 95% confidence interval (CI): 38-63%) stool samples of the cancer patients gave positive FOBT results. Thirty-seven (65%; CI: 52-76%) samples showed alterations in at least one DNA marker. Sixteen (28%) samples were positive only in the FOBT, and 24 (42%) samples showed a positive result exclusively in MD. The combined application of both methods resulted in a sensitivity of 93% (CI: 83-97%) and an overall specificity of 89% (CI: 76-95%). The combined application of FOBT and MD resulted in an overall sensitivity, which could not be achieved by any of the methods alone and which is in the range of invasive diagnostic methods.

[Occupational risk factors for bladder carcinoma. A case control study]

Aim of this case-control study, performed on 412 male bladder cancer cases and 414 controls with benign prostatic hyperplasia in a former area of coal, iron and steel industries in Germany, was to identify occupations with an increased bladder cancer risk. In bladder cancer cases, smokers were overrepresented (58.3%) compared to controls (35.2%). The percentage of patients who had stopped smoking for at least 10 years did not differ in cases (10.2%) and controls (9.7%). Significantly elevated smoking-adjusted bladder cancer odds ratios (MH) were observed in painters and lacquers (MH 2.24, 95% CI 1.07-5.13), chemistry-related occupations (MH 2.44, 95% CI 1.05-5.67), coke plant workers (MH 2.89, 95% CI 1.16-7.16) and hard coal miners (MH 2.33, 95% CI 1.52-3.58). Significantly decreased smoking-adjusted bladder cancer odds ratios (MH) were observed in businessmen (MH 0.64, 95% CI 0.45-0.92) and office personnel (MH 0.58, 95% CI 0.41-0.81). In these two groups a relevant exposure to occupational bladder carcinogens is not likely.

Urothelial cancer of the bladder in an area of former coal, iron, and steel industries in Germany: a case-control study

In a case-control study performed in an area of former coal, iron, and steel industries, the professional and lifestyle histories of 412 male urothelial bladder cancer inpatients (cases) and 414 inpatients with benign prostatic hyperplasia (controls) were investigated. Smoking habits were identified as the main confounder for occupational bladder cancer risk. Two hundred and forty (58.3%) of the bladder cancer inpatients and 146 (35.3%) of the inpatients with benign prostatic hyperplasia were smokers. The percentage of ex-smokers in the bladder cancer cases was 10.2%; the percentage of ex-smokers in the controls was 9.7%. Smoking-adjusted Mantel-Haenszel estimates of the odds ratios (OR&infMH;) for bladder cancer were elevated in underground hard-coal miners (OR&infMH; =2. 54, 95% CI =[1.64; 3.93]), chemical workers (OR&infMH; =2.16, 95% CI =[0.87; 5.38]), painters/varnishers (OR&infMH; = 2.42, 95% CI =[1. 05; 5.57]), technicians (OR&infMH; = 1.99, 95% CI =[0.95; 4.16]), and foundry workers (OR&infMH; = 2.22, 95% CI = [0.53; 9.08]). Administrative officers had significantly lower smoking-adjusted odds ratios (OR&infMH; = 0.61, 95% CI = [0.42; 0.88]). Although statistically not significant, the results of the Breslow-Day test of homogeneity of the odds ratios over the strata are compatible with interactions between tobacco smoking and the occupations of underground hard-coal miners (chi(2)&infBD; = 4.91, p=0.07) and chemical workers (chi(2)&infBR; = 3.32, p=0.06).