Bias in False Discovery Rate Estimation in Mass-Spectrometry-Based Peptide Identification
Accurate target-decoy-based false discovery rate (FDR) control of peptide identification from tandem mass-spectrometry data relies on an important but often neglected assumption that incorrect spectrum annotations are equally likely to receive either target or decoy peptides. Here we argue that this assumption is often violated in practice, even by popular methods. Preference can be given to target peptides by biased scoring functions, which result in liberal FDR estimations, or to decoy peptides by correlated spectra, which result in conservative estimations.
Public sector performance measurement may be affected by data manipulation. This study empirically explores strategies of data manipulation used by civil servants at the regional level in Russia. 25 civil servants from three regional governments were interviewed. Two strategies were identified: “prudent” bureaucrats kept a low profile by reporting “more-normal-than-real” figures; “reckless” bureaucrats aimed at inflating figures to maximize credit. Systematic application of these strategies produced a detectable bias in the overall performance data which was estimated using a nation-wide performance dataset covering the period of 2007-2011 (with a unified list of over 300 indicators from 83 regional governments).
Imaging mass spectrometry (imaging MS) has emerged in the past decade as a label-free, spatially resolved, and multipurpose bioanalytical technique for direct analysis of biological samples from animal tissue, plant tissue, biofilms, and polymer films. Imaging MS has been successfully incorporated into many biomedical pipelines where it is usually applied in the so-called untargeted mode-capturing spatial localization of a multitude of ions from a wide mass range. An imaging MS data set usually comprises thousands of spectra and tens to hundreds of thousands of mass-to-charge (m/z) images and can be as large as several gigabytes. Unsupervised analysis of an imaging MS data set aims at finding hidden structures in the data with no a priori information used and is often exploited as the first step of imaging MS data analysis. We propose a novel, easy-to-use and easy-to-implement approach to answer one of the key questions of unsupervised analysis of imaging MS data: what do all m/z images look like? The key idea of the approach is to cluster all m/z images according to their spatial similarity so that each cluster contains spatially similar m/z images. We propose a visualization of both spatial and spectral information obtained using clustering that provides an easy way to understand what all m/z images look like. We evaluated the proposed approach on matrix-assisted laser desorption ionization imaging MS data sets of a rat brain coronal section and human larynx carcinoma and discussed several scenarios of data analysis.
Randomized controlled trials (RCTs) are considered gold standard in generating judicious evidence to support treatment decisions. Ideal-typical trials are called explanatory trials to distinguish it from trials completed under real-world conditions. The four most prevalent types of bias (selection-, performance-, attrition-, and detection-bias) can be avoided and internal validity of a study can be increased if all requested quality criteria will be met. The external validity can be neither investigated not can it be confirmed by randomized trials. But the confirmation of external validity is as important as the confirmation of internal validity because knowledge that has been generated in RCTs will be valuable only if it can be successfully applied to patients under real-world conditions. For confirmation of external validity the mentioned four types of bias have to be avoided. In addition, it has to be confirmed that the individuals from whom the evidence was derived are comparable to the individuals to whom the evidence should be applied. Violation of this simple appearing requirement is called 'sampling bias'. A two-step procedure seems to be useful to confirm internal as well as external evidence. As first step the efficacy of a therapeutic principle may be confirmed under ideal study conditions by using an explanatory trial without demanding the confirmation of external validity. In a second step the benefit for the investigated group of patients is examined under real-world conditions (pragmatic trial). The design and established methods for evaluation of these studies are discussed. The two-step approach offers three advantages: it reduces the risk to over-interpret the results of RCTs as explanatory trials can only demonstrate efficacy under ideal conditions. The benefit which is requested by our authorities can be demonstrated only by pragmatic trials which consider the external validity. Progress may possibly achieved only if controlled pragmatic trials will be used which can compare the influence of the intended (specific treatment effect) intervention with not-intended (confounder) interventions. Examples for these methods are the propensity score matching or structural equation models.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.