Dataset Information

HLA-EMMA: A user-friendly tool to analyse HLA class I and class II compatibility on the amino acid level.

ABSTRACT: In renal transplantation, polymorphic amino acids on mismatched donor HLA molecules can lead to the induction of de novo donor-specific antibodies (DSA), which are associated with inferior graft survival. To ultimately prevent de novo DSA formation without unnecessarily precluding transplants it is essential to define which polymorphic amino acid mismatches can actually induce an antibody response. To facilitate this, we developed a user-friendly software program that establishes HLA class I and class II compatibility between donor and recipient on the amino acid level. HLA epitope mismatch algorithm (HLA-EMMA) is a software program that compares simultaneously the HLA class I and class II amino acid sequences of the donor with the HLA amino acid sequences of the recipient and determines the polymorphic solvent accessible amino acid mismatches that are likely to be accessible to B cell receptors. Analysis can be performed for a large number of donor-recipient pairs at once. As proof of principle, a previously described study cohort of 191 lymphocyte immunotherapy recipients was analysed with HLA-EMMA and showed a higher frequency of DSA formation with higher number of solvent accessible amino acids mismatches. Overall, HLA-EMMA can be used to analyse compatibility on amino acid level between donor and recipient HLA class I and class II simultaneously for large cohorts to ultimately determine the most immunogenic amino acid mismatches.

SUBMITTER: Kramer CSM

PROVIDER: S-EPMC7317360 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

HLA-EMMA: A user-friendly tool to analyse HLA class I and class II compatibility on the amino acid level.

Kramer Cynthia S M CSM Koster Johan J Haasnoot Geert W GW Roelen Dave L DL Claas Frans H J FHJ Heidt Sebastiaan S

HLA 20200413 1

In renal transplantation, polymorphic amino acids on mismatched donor HLA molecules can lead to the induction of de novo donor-specific antibodies (DSA), which are associated with inferior graft survival. To ultimately prevent de novo DSA formation without unnecessarily precluding transplants it is essential to define which polymorphic amino acid mismatches can actually induce an antibody response. To facilitate this, we developed a user-friendly software program that establishes HLA class I and ...[more]

PMID: 32227681

Similar Datasets

Project description:BackgroundNowadays, microarray gene expression analysis is a widely used technology that scientists handle but whose final interpretation usually requires the participation of a specialist. The need for this participation is due to the requirement of some background in statistics that most users lack or have a very vague notion of. Moreover, programming skills could also be essential to analyse these data. An interactive, easy to use application seems therefore necessary to help researchers to extract full information from data and analyse them in a simple, powerful and confident way.ResultsPreP+07 is a standalone Windows XP application that presents a friendly interface for spot filtration, inter- and intra-slide normalization, duplicate resolution, dye-swapping, error removal and statistical analyses. Additionally, it contains two unique implementation of the procedures - double scan and Supervised Lowess-, a complete set of graphical representations - MA plot, RG plot, QQ plot, PP plot, PN plot - and can deal with many data formats, such as tabulated text, GenePix GPR and ArrayPRO. PreP+07 performance has been compared with the equivalent functions in Bioconductor using a tomato chip with 13056 spots. The number of differentially expressed genes considering p-values coming from the PreP+07 and Bioconductor Limma packages were statistically identical when the data set was only normalized; however, a slight variability was appreciated when the data was both normalized and scaled.ConclusionPreP+07 implementation provides a high degree of freedom in selecting and organizing a small set of widely used data processing protocols, and can handle many data formats. Its reliability has been proven so that a laboratory researcher can afford a statistical pre-processing of his/her microarray results and obtain a list of differentially expressed genes using PreP+07 without any programming skills. All of this gives support to scientists that have been using previous PreP releases since its first version in 2003.

Project description:BackgroundIn the United States, the tuberculosis (TB) disease burden and associated factors vary substantially across states. While public health agencies must choose how to deploy resources to combat TB and latent tuberculosis infection (LTBI), state-level modeling analyses to inform policy decisions have not been widely available.MethodsWe developed a mathematical model of TB epidemiology linked to a web-based user interface - Tabby2. The model is calibrated to epidemiological and demographic data for the United States, each U.S. state, and the District of Columbia. Users can simulate pre-defined scenarios describing approaches to TB prevention and treatment or create their own intervention scenarios. Location-specific results for epidemiological outcomes, service utilization, costs, and cost-effectiveness are reported as downloadable tables and customizable visualizations. To demonstrate the tool's functionality, we projected trends in TB outcomes without additional intervention for all 50 states and the District of Columbia. We further undertook a case study of expanded treatment of LTBI among non-U.S.-born individuals in Massachusetts, covering 10% of the target population annually over 2025-2029.ResultsBetween 2022 and 2050, TB incidence rates were projected to decline in all states and the District of Columbia. Incidence projections for the year 2050 ranged from 0.03 to 3.8 cases (median 0.95) per 100,000 persons. By 2050, we project that majority (> 50%) of TB will be diagnosed among non-U.S.-born persons in 46 states and the District of Columbia; per state percentages range from 17.4% to 96.7% (median 83.0%). In Massachusetts, expanded testing and treatment for LTBI in this population was projected to reduce cumulative TB cases between 2025 and 2050 by 6.3% and TB-related deaths by 8.4%, relative to base case projections. This intervention had an incremental cost-effectiveness ratio of $180,951 (2020 USD) per quality-adjusted life year gained from the societal perspective.ConclusionsTabby2 allows users to estimate the costs, impact, and cost-effectiveness of different TB prevention approaches for multiple geographic areas in the United States. Expanded testing and treatment for LTBI could accelerate declines in TB incidence in the United States, as demonstrated in the Massachusetts case study.

Project description:BackgroundWith the increasing pace of new Genetically Modified Organisms (GMOs) authorized or in pipeline for commercialization worldwide, the task of the laboratories in charge to test the compliance of food, feed or seed samples with their relevant regulations became difficult and costly. Many of them have already adopted the so called "matrix approach" to rationalize the resources and efforts used to increase their efficiency within a limited budget. Most of the time, the "matrix approach" is implemented using limited information and some proprietary (if any) computational tool to efficiently use the available data.ResultsThe developed GMOseek software is designed to support decision making in all the phases of routine GMO laboratory testing, including the interpretation of wet-lab results. The tool makes use of a tabulated matrix of GM events and their genetic elements, of the laboratory analysis history and the available information about the sample at hand. The tool uses an optimization approach to suggest the most suited screening assays for the given sample. The practical GMOseek user interface allows the user to customize the search for a cost-efficient combination of screening assays to be employed on a given sample. It further guides the user to select appropriate analyses to determine the presence of individual GM events in the analyzed sample, and it helps taking a final decision regarding the GMO composition in the sample. GMOseek can also be used to evaluate new, previously unused GMO screening targets and to estimate the profitability of developing new GMO screening methods.ConclusionThe presented freely available software tool offers the GMO testing laboratories the possibility to select combinations of assays (e.g. quantitative real-time PCR tests) needed for their task, by allowing the expert to express his/her preferences in terms of multiplexing and cost. The utility of GMOseek is exemplified by analyzing selected food, feed and seed samples from a national reference laboratory for GMO testing and by comparing its performance to existing tools which use the matrix approach. GMOseek proves superior when tested on real samples in terms of GMO coverage and cost efficiency of its screening strategies, including its capacity of simple interpretation of the testing results.

Project description:BackgroundThe evolution of bacteria is shaped by different mechanisms such as mutation, gene deletion, duplication, or insertion of foreign DNA among others. These genetic changes can accumulate in the descendants as a result of natural selection. Using phylogeny and genome comparisons, evolutionary paths can be somehow retraced, with recent events being much easier to detect than older ones. For this reason, multiple tools are available to study the evolutionary events within genomes of single species, such as gene composition alterations, or subtler mutations such as SNPs. However, these tools are generally designed to compare similar genomes and require advanced skills in bioinformatics. We present CAPRIB, a unique tool developed in Java that allows to determine the amino acid changes, at the genus level, that correlate with phenotypic differences between two groups of organisms.ResultsCAPRIB has a user-friendly graphical interface and uses databases in SQL, making it easy to compare several genomes without the need for programming or thorough knowledge in bioinformatics. This intuitive software narrows down a list of amino acid changes that are concomitant with a given phenotypic divergence at the genus scale. Each permutation found by our software is associated with two already described statistical values that indicate its potential impact on the protein's function, helping the user decide which promising candidates to further investigate. We show that CAPRIB is able to detect already known mutations and uncovers many more, and that this tool can be used to question molecular phylogeny. Finally, we exemplify the utility of CAPRIB by pinpointing amino acid changes that coincided with the emergence of slow-growing mycobacteria from their fast-growing counterparts. The software is freely available at https://github.com/BactSymEvol/Caprib .ConclusionsCAPRIB is a new bioinformatics software aiming to make genus-scale comparisons accessible to all. With its intuitive graphical interface, this tool identifies key amino acid changes concomitant with a phenotypic divergence. By comparing fast and slow-growing mycobacteria, we shed light on evolutionary hotspots, such as the cytokinin pathway, that are interesting candidates for further experimentations.

Dataset Information

HLA-EMMA: A user-friendly tool to analyse HLA class I and class II compatibility on the amino acid level.

Publications

HLA-EMMA: A user-friendly tool to analyse HLA class I and class II compatibility on the amino acid level.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets