Resource profile and user guide of the Polygenic Index Repository.
Ontology highlight
ABSTRACT:
SUBMITTER: Becker J
PROVIDER: S-EPMC8678380 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: Not available
| S-EPMC8165881 | biostudies-literature
Project description:Fluorescent Proteins (FPs) have revolutionized cell biology. The value of labeling and visualizing proteins in living cells is evident from the thousands of publications since the cloning of Green Fluorescent Protein (GFP). Biologists have been flooded with a cornucopia of FPs; however, the FP toolbox has not necessarily been optimized for cell biologists. Common FP plasmids are suboptimal for the construction of proteins fused to FP. More problematic are commercial and investigator-constructed FP-fusion proteins that disrupt important cellular targeting information. Even when cell biologists correctly construct FP-fusion proteins, it is rarely self-evident which FP should be used. Important FP information, such as oligomer formation or photostability, is often obscure or anecdotal. This brief guide is offered to assist the biologist to exploit FPs in the analysis of cellular processes.
| S-EPMC2784028 | biostudies-literature
Project description:Single-cell RNA-seq and TCR-seq were conducted using coding RNA of single cells isolated from mouse lung MNCs with or without 7DW8-5 according to the manufacturer’s instructions. In brief, single cells from the mouse lung MNCs were incubated with mouse Fc block and then stained by anti-mouse CD45+ antibody and DAPI. Sorted viable CD45+DAPI- single cells were loaded into 10x genomics ChromiumTM controller (samples were split into 4 lanes, Saline1 and Saline2 without 7DW8-5 treatment, and 7DW1 and 7DW2 with 7DW8-5 treatment) to make nanoliter-scale droplets with uniquely barcoded 5’ gel beads called GEMs. After GEM-RT and the following some cDNA amplification steps, cDNAs derived from cellular mRNA were pooled for downstream processing and library preparation according to the manufacturer’s instructions. The 5’ transcript library and TCR library were sequenced with Illumina Novaseq. Fastq files from RNA-seq and TCR-seq can be processed through cellranger and vdjranger by 10xgenomics. The datasets include the data of the samples Saline1, Saline2, 7DW1, and 7DW2.
2023-06-06 | E-MTAB-11770 | biostudies-arrayexpress
Project description:ProteomeScout (https://proteomescout.wustl.edu) is a resource for the study of proteins and their post-translational modifications (PTMs) consisting of a database of PTMs, a repository for experimental data, an analysis suite for PTM experiments, and a tool for visualizing the relationships between complex protein annotations. The PTM database is a compendium of public PTM data, coupled with user-uploaded experimental data. ProteomeScout provides analysis tools for experimental datasets, including summary views and subset selection, which can identify relationships within subsets of data by testing for statistically significant enrichment of protein annotations. Protein annotations are incorporated in the ProteomeScout database from external resources and include terms such as Gene Ontology annotations, domains, secondary structure and non-synonymous polymorphisms. These annotations are available in the database download, in the analysis tools and in the protein viewer. The protein viewer allows for the simultaneous visualization of annotations in an interactive web graphic, which can be exported in Scalable Vector Graphics (SVG) format. Finally, quantitative data measurements associated with public experiments are also easily viewable within protein records, allowing researchers to see how PTMs change across different contexts. ProteomeScout should prove useful for protein researchers and should benefit the proteomics community by providing a stable repository for PTM experiments.
| S-EPMC4383955 | biostudies-literature
Project description:The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation.
| S-EPMC7340791 | biostudies-literature
Project description:Body condition is an important concept in behaviour, evolution and conservation, commonly used as a proxy of an individual's performance, for example in the assessment of environmental impacts. Although body condition potentially encompasses a wide range of health state dimensions (nutritional, immune or hormonal status), in practice most studies operationalize body condition using a single (univariate) measure, such as fat storage. One reason for excluding additional axes of variation may be that multivariate descriptors of body condition impose statistical and analytical challenges. Structural equation modelling (SEM) is used in many fields to study questions relating multidimensional concepts, and we here explain how SEM is a useful analytical tool to describe the multivariate nature of body condition. In this 'Research Methods Guide' paper, we show how SEM can be used to resolve different challenges in analysing the multivariate nature of body condition, such as (a) variable reduction and conceptualization, (b) specifying the relationship of condition to performance metrics, (c) comparing competing causal hypothesis and (d) including many pathways in a single model to avoid stepwise modelling approaches. We illustrated the use of SEM on a real-world case study and provided R-code of worked examples as a learning tool. We compared the predictive power of SEM with conventional statistical approaches that integrate multiple variables into one condition variable: multiple regression and principal component analyses. We show that model performance on our dataset is higher when using SEM and led to more accurate and precise estimates compared to conventional approaches. We encourage researchers to consider SEM as a flexible framework to describe the multivariate nature of body condition and thus understand how it affects biological processes, thereby improving the value of body condition proxies for predicting organismal performance. Finally, we highlight that it can be useful for other multidimensional ecological concepts as well, such as immunocompetence, oxidative stress and environmental conditions.
| S-EPMC9291099 | biostudies-literature
Project description:The Mass Genome Annotation (MGA) repository is a resource designed to store published next generation sequencing data and other genome annotation data (such as gene start sites, SNPs, etc.) in a completely standardised format. Each sample has undergone local processing in order the meet the strict MGA format requirements. The original data source, the reformatting procedure and the biological characteristics of the samples are described in an accompanying documentation file manually edited by data curators. 10 model organisms are currently represented: Homo sapiens, Mus musculus, Danio rerio, Drosophila melanogaster, Apis mellifera, Caenorhabditis elegans, Arabidopsis thaliana, Zea mays, Saccharomyces cerevisiae and Schizosaccharomyces pombe. As of today, the resource contains over 24 000 samples. In conjunction with other tools developed by our group (the ChIP-Seq and SSA servers), it allows users to carry out a great variety of analysis task with MGA samples, such as making aggregation plots and heat maps for selected genomic regions, finding peak regions, generating custom tracks for visualizing genomic features in a UCSC genome browser window, or downloading chromatin data in a table format suitable for local processing with more advanced statistical analysis software such as R. Home page: http://ccg.vital-it.ch/mga/.
| S-EPMC5753388 | biostudies-literature
Project description:Current pharmacogenetic studies have obtained many genetic models that can predict the therapeutic efficacy of anticancer drugs. Although some of these models are of crucial importance and have been used in clinical practice, these very valuable models have not been well adopted into cancer research to promote the development of cancer therapies due to the lack of integration and standards for the existing data of the pharmacogenetic studies. For this purpose, we built a resource investigating genetic model of drug response (iGMDR), which integrates the models from in vitro and in vivo pharmacogenetic studies with different omics data from a variety of technical systems. In this study, we introduced a standardized process for all integrations, and described how users can utilize these models to gain insights into cancer. iGMDR is freely accessible at https://igmdr.modellab.cn.
| S-EPMC7646137 | biostudies-literature
Project description:PurposeExertional rhabdomyolysis can occur in individuals performing various types of exercise but it is unclear why some individuals develop this condition while others do not. Previous investigations have determined the role of several single nucleotide polymorphisms (SNPs) to explain inter-individual variability of serum creatine kinase (CK) concentrations after exertional muscle damage. However, there has been no research about the interrelationship among these SNPs. The purpose of this investigation was to analyze seven SNPs that are candidates for explaining individual variations of CK response after a marathon competition (ACE = 287bp Ins/Del, ACTN3 = p.R577X, CKMM = NcoI, IGF2 = C13790G, IL6 = 174G>C, MLCK = C37885A, TNFα = 308G>A).MethodsUsing Williams and Folland's model, we determined the total genotype score from the accumulated combination of these seven SNPs for marathoners with a low CK response (n = 36; serum CK <400 U·L-1) vs. marathoners with a high CK response (n = 31; serum CK ≥400 U·L-1).ResultsAt the end of the race, low CK responders had lower serum CK (290±65 vs. 733±405 U·L-1; P<0.01) and myoglobin concentrations (443±328 vs. 1009±971 ng·mL-1, P<0.01) than high CK responders. Although the groups were similar in age, anthropometric characteristics, running experience and training habits, total genotype score was higher in low CK responders than in high CK responders (5.2±1.4 vs. 4.4±1.7 point, P = 0.02).ConclusionMarathoners with a lower CK response after the race had a more favorable polygenic profile than runners with high serum CK concentrations. This might suggest a significant role of genetic polymorphisms in the levels of exertional muscle damage and rhabdomyolysis. Yet other SNPs, in addition to exercise training, might also play a role in the values of CK after damaging exercise.
| S-EPMC5336235 | biostudies-literature
Project description:People interact with systems and applications through several devices and are willing to share information about preferences, interests and characteristics. Social networking profiles, data from advanced sensors attached to personal gadgets, and semantic web technologies such as FOAF and microformats are valuable sources of personal information that could provide a fair understanding of the user, but profile information is scattered over different user models. Some researchers in the ubiquitous user modeling community envision the need to share user model's information from heterogeneous sources. In this paper, we address the syntactic and semantic heterogeneity of user models in order to enable user modeling interoperability. We present a dynamic user profile structure based in Simple Knowledge Organization for the Web (SKOS) to provide knowledge representation for ubiquitous user model. We propose a two-tier matching strategy for concept schemas alignment to enable user modeling interoperability. Our proposal is proved in the application scenario of sharing and reusing data in order to deal with overweight and obesity.
| S-EPMC3545566 | biostudies-literature