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Genome-wide association studies (GWAS) have revolutionized our understanding of the genetic architecture of complex traits and diseases. GWAS summary statistics have become essential tools for various genetic analyses, including meta-analysis, fine-mapping, and risk prediction. However, the increasing number of GWAS summary statistics and the diversity of software tools available for their analysis can make it challenging for researchers to select the most appropriate tools for their specific needs. This systematic review aims to provide a comprehensive overview of the currently available software tools and databases for GWAS summary statistics analysis. We conducted a comprehensive literature search to identify relevant software tools and databases. We categorized the tools and databases by their functionality, including data management, quality control, single-trait analysis, and multiple-trait analysis. We also compared the tools and databases based on their features, limitations, and user-friendliness. Our review identified a total of 305 functioning software tools and databases dedicated to GWAS summary statistics, each with unique strengths and limitations. We provide descriptions of the key features of each tool and database, including their input/output formats, data types, and computational requirements. We also discuss the overall usability and applicability of each tool for different research scenarios. This comprehensive review will serve as a valuable resource for researchers who are interested in using GWAS summary statistics to investigate the genetic basis of complex traits and diseases. By providing a detailed overview of the available tools and databases, we aim to facilitate informed tool selection and maximize the effectiveness of GWAS summary statistics analysis. [ABSTRACT FROM AUTHOR]

Objectives: This article introduces the Climate-related Financial Policies Database and provides statistics on its main indicators. The database records many aspects of green financial policymaking for 74 nations for the period 2000–2020 by financial (central banks, financial regulators, supervisors) and non-financial (ministries, banking organizations, governments, and others) entities. The database is crucial for identifying and evaluating present and future trends in green financial policies, as well as the role played by central banks and regulators in raising green financing and taming financial instability caused by climate change. Data description: The database captures various aspects of financial (central banks and financial regulators and supervisors) and non-financial institutions' (ministries, banking associations, governments, and others) green financial policymaking in the period 2000–2020. Information is collected for the following variables: country/jurisdiction, economic development level (as defined by the World Bank Indicators), year of policy adoption, measure adopted and its bindingness, and authority/ies responsible for its implementation The database includes 74 countries, of which 39 are advanced economies, 20 are emerging, and 15 are developing economies. Open knowledge and data sharing encouraged by this article can support research in the developing field of financial policymaking related to climate change. [ABSTRACT FROM AUTHOR]

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The expediency of forming the specialized database about industry and the system of their automated collection and usage were justified in this paper. This system allows to provide the information needs of the analysts and the scientists about the problems of industrial development. It provides the automated collection of the information for many countries of the world using any number of sources available as client-server resources on the Internet. The usage of modern data integration algorithms provides a diverse presentation of information, formats for its provision and frequency of updates. In addition, the advanced users of the system are provided with a wide range of options for creating search criteria and data acquisition format. The system is built as a client-server technology and is available for seamless integration with similar systems as a source and storage of information. In order to build a system, the analysis of existing in the world and popular in use statistical databases was carried out, their features, advantages and disadvantages were deafined. It has been established that most of the existing statistical systems do not provide statistical data for Ukraine, and where they are, there is no detail data by type of economic activity and industry, and especially in industry. In addition, there are certain technical difficulties in working with data for users, the personalization of access is almost non-existent. The possibilities of the integrating existing databases with the systems that use information for modeling and forecasting both in query mode and especially in real time are rather limited. The structure of the statistical database about the development of industry has been formed, the indicators have been selected for its filling. The indicators were distributed by the sectors of the economy (the raw material production sector, the processing sector, the macrostatistics, other sectors). The sectors were disclosed by the key types of economic activity in accordance with the classification of economic activities in 2010 (CEA-2010), providing the predominant part of the creation of the added value of the economy of Ukraine. Each specific type of economic activity is disclosed by groups of industries and industries. In addition, the formation of the statistical database was carried out on the basis of assigning to each of the indicators other characteristics necessary for the automation: code, units of measurement, period, base (distribution of the indicators into the separate groups for the possibility of modeling), source (the statistical bases and sources from which the indicators and the data were collected). The modern relational database was used to store information, which allows solving optimization issues for working with the most powerful, but not yet large data, taking into account the features of wide data, allows horizontal and vertical scaling, including in the PostgreSQL open source database system. The methodology for the formation and the technology for filling the statistical database automatically from a large number of sources, the access mode to which is set by the system configuration parameters has been created. The technology has been developed for data migrations available in flexible formats, including text, in particular Excel. The implementation of the developed automated information system integration of industrial statistics allows you to select the necessary indicators for the analysis of economic processes in industry, use the statistical data collected in a single information space for 130 countries of the world (including Ukraine) for conducting scientific researches, building economic and mathematical models and making managerial decisions. [ABSTRACT FROM AUTHOR]

Most of the forensic DNA laboratories have migrated to new generation STR kits of 6 dye chemistry with more than 20 autosomal STRs. The population-specific databases of such STR markers are lacking in many regions. To evaluate the effect of the inter-population database in 100 paternity trios with no inconsistencies at 23 STRs. 100 paternity trios were evaluated considering inter-population allelic frequency values for calculation of Combined Paternity Index (CPI) and Probability of Paternity (POP). No significant variation (p < 0.05) among the allele frequencies at the interpopulation level was observed. The number of obligate alleles and the likelihood of transferring obligate alleles from the putative father showed a positive correlation (p < 0.005) with Power of Discrimination (PD), Polymorphic Information Content (PIC), Power of Exclusion (PE), Paternity Index (PI), Observed and Expected Heterozygosity (Ho and He), and a statistically significant negative correlation (p < 0.005) with Matching Probability (Pm). The average Combined Paternity Index (CPI) and Probability of Paternity (POP) did not show any statistically significant difference (p < 0.05) at the interpopulation level. The allelic database showed no effect on the CPI and POP in 100 paternity trios. This suggests no urgent need for using population-specific databases for statistical evaluation of paternity trios without inconsistencies. [ABSTRACT FROM AUTHOR]

We present the Codon Statistics Database, an online database that contains codon usage statistics for all the species with reference or representative genomes in RefSeq (over 15,000). The user can search for any species and access two sets of tables. One set lists, for each codon, the frequency, the Relative Synonymous Codon Usage, and whether the codon is preferred. Another set of tables lists, for each gene, its GC content, Effective Number of Codons, Codon Adaptation Index, and frequency of optimal codons. Equivalent tables can be accessed for (1) all nuclear genes, (2) nuclear genes encoding ribosomal proteins, (3) mitochondrial genes, and (4) chloroplast genes (if available in the relevant assembly). The user can also search for any taxonomic group (e.g. "primates") and obtain a table comparing all the species in the group. The database is free to access without registration at http://codonstatsdb.unr.edu. [ABSTRACT FROM AUTHOR]

• POLEMAD is the first relational database containing multimodal speech data for Polish language obtained from electromagnetic articulograph, multichannel audio recorder and stereoscopic vision system. • Containing speech samples from 20 subjects, the database is one of the largest datasets of this type in the world. • A new type of images obtained from an acoustic camera is stored in the POLEMAD database. • The database can facilitate experiments on speech inversion including dynamic Bayesian networks. The structure and functionality of the POLEMAD database constructed on the basis of a study using Electromagnetic Articulograph AG 500, an acoustic camera, and 3 video cameras are described in the paper. The article describes also data types stored in the database including speaker data, EMA data, video and sound recordings, phonetic information, and dynamic Bayesian network (DBN) models. The database allows for selective extraction of various types of samples for further analysis, which is performed by SQL queries generated in MATLAB® using Database Toolbox™. The possibilities of potential future application of the database in statistical analysis and automation of experiments on speech inversion using DBN are described in the paper as well. Image, graphical abstract [ABSTRACT FROM AUTHOR]

The Universal Protein Resource (https://www.uniprot.org/, UniProt) is a well-known protein database, which consists of the UniProt knowledgebase (UniProtKB), the UniProt unique protein identifier archive (UniParc). and ihc I niProI reference sequence clusters (I nilJel ). Aparl from protein sequence dala. the UniProtKB has comprehensive annotations and is the eore of the database. UniProtKB/Swiss-Prot has more than 500 thousand entries and is a manually reviewed and annotated subset of UniProtKB, while the UniProtKB/TrEMBL contains more than 140 million un-reviewed sequences which are translated from the coding sequences in the nucleotide database EMBL and computationally annotated based on certain rules. UniParc merges the same sequence stored in UniProtKB and other available protein sequence databases into a single record to avoid redundancy and gives each record a permanent and unique identifier. UniRef clusters the UniProtKB and the selected UniParc sequences into three different sets, i.e., UniRef 100, UniRef90, and UniRef50, according to their sequence identity. The UniProt website provides users with an easy-to-use and highly efficient interface for advanced search and various help documents. The UniProt database releases statistics published online along with the update of the database every four weeks, which lists useful information such as the number of newly added and updated entries, the sequence types and their taxonomio sources, as well as general annotations, sequence features, and database cross-references. UniProt has been serving the user community of life sciences as the most-comprehensive, well-annotated, non-redundant, and freely-accessible resource of protein sequence and function since it was established at the beginning of this century. [ABSTRACT FROM AUTHOR]

The Statistical Database on the Great East Japan Earthquake (SDJE) has been developed as an information resource to assist in research and preparations for future disasters in Japan and other countries. The SDJE was initiated in January 2016 by the International Research Institute of Disaster Science (IRIDeS) of Tohoku University. As a university in the affected area of the Great East Japan Earthquake (GEJE), Tohoku University acknowledges with gratitude the participation in GEJE relief and recovery activities of organizations and people from elsewhere in the country and abroad, and in response has undertaken a number of initiatives to provide scientific information and the lessons from the GEJE. For example, IRIDeS hosts and acts as the secretariat of the Global Centre for Disaster Statistics and has now developed this new database. The SDJE provides comprehensive data on the GEJE in both English and Japanese, drawing widely on data originally provided by the national and local governments and private organizations, including considerable contents taken from the white papers of Japan's Cabinet Office and other national ministries. The data coverage extends from the time of the GEJE to currently produced materials. In addition, a "Link Collection" of Japanese statistics related to disasters is provided to support statistical analysis of the social and economic effect of the GEJE, for example through correlation analysis, and to assist researchers to better understand the context of the disaster and the disaster statistics. It is hoped that many people worldwide will find the content of the database useful for disaster risk reduction activities. [ABSTRACT FROM AUTHOR]

The article presents a survey on the performance of information available in digital libraries sourcing scientific information, commonly known as academic databases or scientific search engines, undertaken by Italian Society of Clinical Biochemistry and Laboratory Medicine (SIBioC). It also discusses the survey module, most preferred databases, and the number people or organizations dependent on research databases for scientific information.

Purpose: To create a computerized tracking software specific to glaucoma for the purpose of optaining instant statistical data, performing a standardized ophthalmic examination and establishing a follow-up protocol in glaucoma centers. Materials and Methods: The software with multi-user support connected to the central database was prepared to be specific for glaucoma patients. The Delphi program was used as the desktop application. Firebird was preferred as the database. The medical data of 7500 glaucoma patients were uploaded to the glaucoma follow up program. Results: Data-base analysis of registered patients data consisting of the diagnosis, visual acuity, intraocular pressure, visual fields, optic nerve and nerve fiber layer analysis, gonioscopy, central corneal thickness, drugs, surgery, and concomitant systemic disease were easily obtained. The important benefits of the glaucoma follow-up program were easy and safe digital archiving, detection of diagnosis and treatment group datasets, observing the efficiency of the applied treatment algorithms, observing and checking the practice pattern of the residents, easy data collection for research, and the preparation of referral information in chronological order. Conclusion: We believe that glaucoma specific-computerized patient follow-up programs are useful in glaucoma centers for standardized diagnosis, follow-up and treatment protocols, and instant statistical database access. [ABSTRACT FROM AUTHOR]

This paper presents the experimental database and corresponding statistical analysis (Part I), which serves as a basis to perform the corresponding parametric analysis and machine learning modelling (Part II) of a comprehensive study on organic soil strength and stiffness, stabilized via the wet soil mixing method. The experimental database includes unconfined compression tests performed under laboratory-controlled conditions to investigate the impact of soil type, the soil's organic content, the soil's initial natural water content, binder type, binder quantity, grout to soil ratio, water to binder ratio, curing time, temperature, curing relative humidity and carbon dioxide content on the stabilized organic specimens' stiffness and strength. A descriptive statistical analysis complements the description of the experimental database, along with a qualitative study on the stabilization hydration process via scanning electron microscopy images. Results confirmed findings on the use of Portland cement alone and a mix of Portland cement with ground granulated blast furnace slag as suitable binders for soil stabilization. Findings on mixes including lime and magnesium oxide cements demonstrated minimal stabilization. Specimen size affected stiffness, but not the strength for mixes of peat and Portland cement. The experimental database, along with all produced data analyses, are available at the Texas Data Repository as indicated in the Data Availability Statement below, to allow for data reproducibility and promote the use of artificial intelligence and machine learning competing modelling techniques as the ones presented in Part II of this paper. [ABSTRACT FROM AUTHOR]