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.     

Solid Organ Transplantation in Patients with Inflammatory Bowel Diseases (IBD): Analysis of Transplantation Outcome and IBD Activity in a Large Single Center Cohort

Background

Currently, limited data of the outcome of inflammatory bowel disease (IBD) in patients after solid organ transplantation (SOT) are available. We aimed to analyze effects of SOT on the IBD course in a large IBD patient cohort.

Methods

Clinical data from 1537 IBD patients were analyzed for patients who underwent SOT (n = 31) between July 2002 and May 2014. Sub-analyses included SOT outcome parameters, IBD activity before and after SOT, and efficacy of IBD treatment.

Results

4.74% of patients with ulcerative colitis (UC) and 0.84% of patients with Crohn’s disease (CD) underwent SOT (p = 2.69 x 10⁻⁶, UC vs. CD). 77.4% of patients with SOT underwent liver transplantation (LTx) with tacrolimus-based immunosuppressive therapy after SOT. All LTx were due to primary sclerosing cholangitis (PSC) or PSC overlap syndromes. Six patients (19.4%) required renal transplantation and one patient (3.2%) heart transplantation. A survival rate of 83.9% after a median follow-up period of 103 months was observed. Before SOT, 65.0% of patients were in clinical remission and 5 patients received immunosuppressive therapy (16.1%). After SOT, 61.0% of patients were in remission (p = 1.00 vs. before SOT) and 29.0% required IBD-specific immunosuppressive or anti-TNF therapy (p = 0.54 vs. before SOT). 42.9% of patients with worsening of IBD after SOT were at higher risk of needing steroid therapy for increased IBD activity (p = 0.03; relative risk (RR): 10.29; 95% CI 1.26–84.06). Four patients (13.0%) needed anti-TNF therapy after SOT (response rate 75%).

Conclusions

SOT was more common in UC patients due to the higher prevalence of PSC-related liver cirrhosis in UC. Despite mainly tacrolimus-based immunosuppressive regimens, outcome of SOT and IBD was excellent in this cohort. In this SOT cohort, concomitant immunosuppressive therapy due to IBD was well tolerated.     

Exact distribution of a pattern in a set of random sequences generated by a Markov source: applications to biological data

Background  

In bioinformatics it is common to search for a pattern of interest in a potentially large set of rather short sequences (upstream gene regions, proteins, exons, etc.). Although many methodological approaches allow practitioners to compute the distribution of a pattern count in a random sequence generated by a Markov source, no specific developments have taken into account the counting of occurrences in a set of independent sequences. We aim to address this problem by deriving efficient approaches and algorithms to perform these computations both for low and high complexity patterns in the framework of homogeneous or heterogeneous Markov models.     

Statistics of the mouse bone-marrow micronucleus test: counting, distribution and evaluation of results

The distribution of historical control results from male mice tested in the bone-marrow micronucleus test was used to optimize counting procedures and to develop decision rules for evaluating test results. The ratio of normochromatic to polychromatic erythrocytes followed a normal distribution, while the incidence of micronucleated polychromatic and normochromatic erythrocytes followed a binomial distribution. Recommendations for the number of cells to be scored per animal and for the evaluation of results are based on these distributions and the two-hypothesis multiple-decision approach of Selby and Olsen (1981).     

Sphagnophyta of Europe and Macaronesia: a checklist with distribution data

Abstract

We give the distribution of Sphagnum L. in Europe and Macaronesia, mainly at a country level. The world distribution is also given, though less detailed. We include notes on doubtful and erroneous reports and provide a list of taxa excluded from Europe and Macaronesia. We recognize 52 species from the area and additionally some subspecies and varieties. The country with the largest number of species is Norway while there are no records from nine areas.     

Eight (and a half) deadly sins of spatial analysis

Biogeography is spatial by nature. Over the past 20 years, the literature related to the analysis of spatially structured data has exploded, much of it focused on a perceived problem of spatial autocorrelation and ways to deal with it. However, there are a number of other issues that permeate the biogeographical and macroecological literature that have become entangled in the spatial autocorrelation web. In this piece I discuss some of the assumptions that are often made in the analysis of spatially structured data that can lead to misunderstandings about the nature of spatial data, the methods used to analyse them, and how results can be interpreted.     

Raveniola niedermeyeri from Iran: redescription and new data on distribution (Araneae, Nemesiidae)

Raveniola niedermeyeri (Brignoli, 1972), a poorly known species, is rediagnosed and redescribed from the types and from recently collected material from northern and central regions of Iran. This species differs from its congeners in having the male embolus curved distally, as well as in the unique conformation of the spermathecae. New data on the distribution of Raveniola niedermeyeri in Iran are also provided.     

Methods for the detection of multiple linked QTL applied to a mixture of full and half sib families

A new multiple trait strategy based on discriminant analysis was studied for efficient detection of linked QTL in outbred sib families, in comparison with a multivariate likelihood technique. The discriminant analysis technique describes the segregation of a linear combination of the traits in a univariate likelihood. This combination is calculated for each pair of positions depending on the inheritance of the pairs of QTL haplotypes in the progeny. The gains in power and accuracy for position estimations of multiple trait methods in grid searches were evaluated in reference to single trait detections of linked QTL. The methods were applied to simulated designs with two correlated traits submitted to various effects from the linked QTL. Multiple trait strategies were generally more powerful and accurate than the single trait technique. Linked QTL were distinguished when they were separated enough to identify informative recombinations: at least two genetic markers and 25 cM between the QTL under the simulated conditions. Except in a particular case, discriminant analysis was at least as powerful as the multivariate technique and its implementation was five times faster. Combining the advantages from both methodologies, we finally propose a complete strategy for rapid and efficient systematic multivariate detections in outbred populations.     

A tool for analyzing information from data storage tags: the continuous wavelet transform (CWT)

Electronic Data Storage Tags (DSTs) have the potential of providing long term, high-resolution observation data of individual fish in the ecosystem. However, traditional time series analysis methods are limited in extracting the required information from DSTs. The continuous wavelet transform (CWT) is a tool for decomposing a time series into instantaneous frequency versus time characteristics. This allows data signals, which are restricted to specific frequencies (localized frequencies), or frequency components, which are restricted to specific time intervals (time localized) to be extracted and displayed in a highly intuitive way. The aim of this short communication is to present the CWT as a tool for extracting information from DST data. In the first case, synthetically generated data is used to demonstrate how the methodology captures different time–frequency dependent patterns in the time series data. The relevance of the methodology to real field data is demonstrated by an analysis of DST depth data from tagged Barents Sea coastal cod. This work has also enjoyed partial funding from the EU-FP5-Q5RS200200813 CODYSSEY project.     

Power to detect linkage based on multiple sets of data in the presence of locus heterogeneity: comparative evaluation of model-based linkage methods for affected sib pair data

The development of rigorous methods for evaluating the overall strength of evidence for genetic linkage based on multiple sets of data is becoming increasingly important in connection with genomic screens for complex disorders. We consider here what happens when we attempt to increase power to detect linkage by pooling multiple independently collected sets of families under conditions of variable levels of locus heterogeneity across samples. We show that power can be substantially reduced in pooled samples when compared to the most informative constituent subsamples considered alone, in spite of the increased sample size afforded by pooling. We demonstrate that for affected sib pair data, a simple adaptation of the lod score (which we call the compound lod), which allows for intersample admixture differences can afford appreciably higher power than the ordinary heterogeneity lod; and also, that a statistic we have proposed elsewhere, the posterior probability of linkage, performs at least as well as the compound lod while having considerable computational advantages. The companion paper (this issue, pp 217-225) shows further that in application to multiple data sets, familiar model-free methods are in some sense equivalent to ordinary lod scores based on data pooling, and that they therefore will also suffer dramatic losses in power for pooled data in the presence of locus heterogeneity and other complicating factors.     

Considerations on influence of charge distribution on determination of biomolecules and microorganisms and tailoring the monolithic (continuous bed) materials for bioseparations

The importance of continuous beds (monoliths) as separation materials is connected with their better chromatographic properties and easier preparation in comparison to particulate-packed columns. Moreover the tuning of porosity as well as surface chemistry can lead to obtaining of highly selective materials, especially useful in separation of biologically important compounds or even microorganisms. To obtain high selectivity for such analytes as e.g. proteins, it is often important to have a knowledge about their shape, size, charge and finally charge distribution. This article presents our considerations on the charge distribution on the monolithic stationary phase and surface of such species as proteins or microorganisms as well as its eventual influence on the separation or sample preparation processes and tuning of their selectivity.