Isabl Platform, a digital biobank for processing multimodal patient data

Abstract Background The widespread adoption of high throughput technologies has democratized data generation. However, data processing in accordance with best practices remains challenging and the data capital often becomes siloed. This presents an opportunity to consolidate data assets into digital biobanks—ecosystems of readily accessible, structured, and annotated datasets that can be dynamically queried and analysed. Results We present Isabl, a customizable plug-and-play platform for the processing of multimodal patient-centric data. Isabl's architecture consists of a relational database (Isabl DB), a command line client (Isabl CLI), a RESTful API (Isabl API) and a frontend web application (Isabl Web). Isabl supports automated deployment of user-validated pipelines across the entire data capital. A full audit trail is maintained to secure data provenance, governance and ensuring reproducibility of findings. Conclusions As a digital biobank, Isabl supports continuous data utilization and automated meta analyses at scale, and serves as a catalyst for research innovation, new discoveries, and clinical translation.

Download Full-text

Proof-of-PUF Enabled Blockchain: Concurrent Data and Device Security for Internet-of-Energy

Sensors ◽

10.3390/s21010028 ◽

2020 ◽

Vol 21 (1) ◽

pp. 28

Author(s):

Rameez Asif ◽

Kinan Ghanem ◽

James Irvine

Keyword(s):

Hybrid Approach ◽

Future Research ◽

Data Provenance ◽

Data Generation ◽

Cyber Attack ◽

Design Development ◽

Seamless Integration ◽

Device Identification ◽

Physical Unclonable Functions ◽

History Of

A detailed review on the technological aspects of Blockchain and Physical Unclonable Functions (PUFs) is presented in this article. It stipulates an emerging concept of Blockchain that integrates hardware security primitives via PUFs to solve bandwidth, integration, scalability, latency, and energy requirements for the Internet-of-Energy (IoE) systems. This hybrid approach, hereinafter termed as PUFChain, provides device and data provenance which records data origins, history of data generation and processing, and clone-proof device identification and authentication, thus possible to track the sources and reasons of any cyber attack. In addition to this, we review the key areas of design, development, and implementation, which will give us the insight on seamless integration with legacy IoE systems, reliability, cyber resilience, and future research challenges.

Download Full-text

Attrition Diagrams for Clinical Trials and Meta-analyses in Stata

The Stata Journal Promoting communications on statistics and Stata ◽

10.1177/1536867x1801800206 ◽

2018 ◽

Vol 18 (2) ◽

pp. 387-394

Author(s):

Christiaan H. Righolt ◽

Salaheddin M. Mahmud

Keyword(s):

Clinical Trials ◽

Command Line ◽

Exclusion Criteria ◽

Meta Analyses

In this article, we present attrition, a suite of commands to simplify the maintenance and documentation of implemented exclusion criteria and attrition conditions using standard Stata facilities and to generate an attrition diagram. attrition can be used, both from the command line and in do-files, to keep the diagram up to date with the analysis it documents. Six subcommands (set, exclude, count, tab, list, graph) allow the diagram to be constructed in a versatile way.

Download Full-text

ESIS ON THE WORLD WIDE WEB

International Journal of Modern Physics C ◽

10.1142/s0129183194000921 ◽

1994 ◽

Vol 05 (05) ◽

pp. 805-809 ◽

Cited By ~ 1

Author(s):

SALIM G. ANSARI ◽

PAOLO GIOMMI ◽

ALBERTO MICOL

Keyword(s):

World Wide Web ◽

Web Application ◽

World Wide ◽

Markup Language ◽

Command Line ◽

Command Line Interface ◽

The World ◽

Hypertext Transfer Protocol ◽

Hypertext Markup Language ◽

Near Future

On 3rd November, 1993, ESIS announced its Homepage on the World Wide Web (WWW) to the user community. Ever since then, ESIS has steadily increased its Web support to the astronomical community to include a bibliographic service, the ESIS catalogue documentation and the ESIS Data Browser. More functionality will be added in the near future. All these services share a common ESIS structure that is used by other ESIS user paradigms such as the ESIS Graphical User Interface (Giommi and Ansari, 1993), and the ESIS Command Line Interface. A forms-based paradigm, each ESIS-Web application interfaces to the hypertext transfer protocol (http) translating queries from/to the hypertext markup language (html) format understood by the NCSA Mosaic interface. In this paper, we discuss the ESIS system and show how each ESIS service works on the World Wide Web client.

Download Full-text

Best practices for MRI systematic reviews and meta‐analyses

Journal of Magnetic Resonance Imaging ◽

10.1002/jmri.26198 ◽

2018 ◽

Vol 49 (7) ◽

pp. e51-e64 ◽

Cited By ~ 14

Author(s):

Trevor A. McGrath ◽

Patrick M. Bossuyt ◽

Paul Cronin ◽

Jean‐Paul Salameh ◽

Noémie Kraaijpoel ◽

...

Keyword(s):

Best Practices ◽

Systematic Reviews ◽

Meta Analyses

Download Full-text

MALDIViz: A Comprehensive Informatics Tool for MALDI-MS Data Visualization and Analysis

SLAS DISCOVERY Advancing Life Sciences ◽

10.1177/2472555217727517 ◽

2017 ◽

Vol 22 (10) ◽

pp. 1246-1252 ◽

Cited By ~ 1

Author(s):

Kishore Kumar Jagadeesan ◽

Simon Ekström

Keyword(s):

Mass Spectrometry ◽

High Throughput ◽

High Throughput Screening ◽

Web Application ◽

Low Cost ◽

Maldi Ms ◽

Ionization Mass ◽

Label Free ◽

Label Free Detection ◽

R Shiny

Recently, mass spectrometry (MS) has emerged as an important tool for high-throughput screening (HTS) providing a direct and label-free detection method, complementing traditional fluorescent and colorimetric methodologies. Among the various MS techniques used for HTS, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) provides many of the characteristics required for high-throughput analyses, such as low cost, speed, and automation. However, visualization and analysis of the large datasets generated by HTS MALDI-MS can pose significant challenges, especially for multiparametric experiments. The datasets can be generated fast, and the complexity of the experimental data (e.g., screening many different sorbent phases, the sorbent mass, and the load, wash, and elution conditions) makes manual data analysis difficult. To address these challenges, a comprehensive informatics tool called MALDIViz was developed. This tool is an R-Shiny-based web application, accessible independently of the operating system and without the need to install any program locally. It has been designed to facilitate easy analysis and visualization of MALDI-MS datasets, comparison of multiplex experiments, and export of the analysis results to high-quality images.

Download Full-text

Best Practices for Technical Reproducibility Assessment of Multiplex Immunofluorescence

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.660202 ◽

2021 ◽

Vol 8 ◽

Author(s):

Caddie Laberiano-Fernández ◽

Sharia Hernández-Ruiz ◽

Frank Rojas ◽

Edwin Roger Parra

Keyword(s):

Best Practices ◽

Signal Amplification ◽

Data Generation ◽

Technical Requirements ◽

Analysis Strategies ◽

Technical Reproducibility ◽

High Flexibility ◽

Correct Data ◽

Cancer Studies ◽

Single Slide

Multiplex immunofluorescence (mIF) tyramide signal amplification is a new and useful tool for the study of cancer that combines the staining of multiple markers in a single slide. Several technical requirements are important to performing high-quality staining and analysis and to obtaining high internal and external reproducibility of the results. This review manuscript aimed to describe the mIF panel workflow and discuss the challenges and solutions for ensuring that mIF panels have the highest reproducibility possible. Although this platform has shown high flexibility in cancer studies, it presents several challenges in pre-analytic, analytic, and post-analytic evaluation, as well as with external comparisons. Adequate antibody selection, antibody optimization and validation, panel design, staining optimization and validation, analysis strategies, and correct data generation are important for reproducibility and to minimize or identify possible issues during the mIF staining process that sometimes are not completely under our control, such as the tissue fixation process, storage, and cutting procedures.

Download Full-text

UCEasy: A software package for automating and simplifying the analysis of ultraconserved elements (UCEs)

Biodiversity Data Journal ◽

10.3897/bdj.9.e78132 ◽

2021 ◽

Vol 9 ◽

Author(s):

Caio Ribeiro ◽

Lucas Oliveira ◽

Romina Batista ◽

Marcos De Sousa

Keyword(s):

Best Practices ◽

Software Package ◽

Phylogenetic Trees ◽

Computational Analysis ◽

Data Matrix ◽

Command Line ◽

Command Line Interface ◽

Ultraconserved Elements ◽

Research Software ◽

Different Levels

The use of Ultraconserved Elements (UCEs) as genetic markers in phylogenomics has become popular and has provided promising results. Although UCE data can be easily obtained from targeted enriched sequencing, the protocol for in silico analysis of UCEs consist of the execution of heterogeneous and complex tools, a challenge for scientists without training in bioinformatics. Developing tools with the adoption of best practices in research software can lessen this problem by improving the execution of computational experiments, thus promoting better reproducibility. We present UCEasy, an easy-to-install and easy-to-use software package with a simple command line interface that facilitates the computational analysis of UCEs from sequencing samples, following the best practices of research software. UCEasy is a wrapper that standardises, automates and simplifies the quality control of raw reads, assembly and extraction and alignment of UCEs, generating at the end a data matrix with different levels of completeness that can be used to infer phylogenetic trees. We demonstrate the functionalities of UCEasy by reproducing the published results of phylogenomic studies of the bird genus Turdus (Aves) and of Adephaga families (Coleoptera) containing genomic datasets to efficiently extract UCEs.

Download Full-text

FAN-C: A Feature-rich Framework for the Analysis and Visualisation of C data

10.1101/2020.02.03.932517 ◽

2020 ◽

Cited By ~ 6

Author(s):

Kai Kruse ◽

Clemens B. Hug ◽

Juan M. Vaquerizas

Keyword(s):

High Throughput ◽

Matrix Analysis ◽

Set Covering ◽

Command Line ◽

Chromosome Conformation ◽

C Storage ◽

Data Formats ◽

Analysis Tools ◽

Command Line Tool ◽

Broad Feature

Chromosome conformation capture data, particularly from high-throughput approaches such as Hi-C and its derivatives, are typically very complex to analyse. Existing analysis tools are often single-purpose, or limited in compatibility to a small number of data formats, frequently making Hi-C analyses tedious and time-consuming. Here, we present FAN-C, an easy-to-use command-line tool and powerful Python API with a broad feature set covering matrix generation, analysis, and visualisation for C-like data (https://github.com/vaquerizaslab/fanc). Due to its comprehensiveness and compatibility with the most prevalent Hi-C storage formats, FAN-C can be used in combination with a large number of existing analysis tools, thus greatly simplifying Hi-C matrix analysis.

Download Full-text

SpiderSeqR: an R package for crawling the web of high-throughput multi-omic data repositories for data-sets and annotation

10.1101/2020.04.13.039420 ◽

2020 ◽

Author(s):

Anna M. Sozanska ◽

Charles Fletcher ◽

Dóra Bihary ◽

Shamith A. Samarajiwa

Keyword(s):

High Throughput ◽

R Package ◽

Data Reuse ◽

Massively Parallel ◽

Data Sets ◽

Similar Data ◽

Data Generation ◽

Data Repositories ◽

Public Data ◽

Omic Data

AbstractMore than three decades ago, the microarray revolution brought about high-throughput data generation capability to biology and medicine. Subsequently, the emergence of massively parallel sequencing technologies led to many big-data initiatives such as the human genome project and the encyclopedia of DNA elements (ENCODE) project. These, in combination with cheaper, faster massively parallel DNA sequencing capabilities, have democratised multi-omic (genomic, transcriptomic, translatomic and epigenomic) data generation leading to a data deluge in bio-medicine. While some of these data-sets are trapped in inaccessible silos, the vast majority of these data-sets are stored in public data resources and controlled access data repositories, enabling their wider use (or misuse). Currently, most peer reviewed publications require the deposition of the data-set associated with a study under consideration in one of these public data repositories. However, clunky and difficult to use interfaces, subpar or incomplete annotation prevent discovering, searching and filtering of these multi-omic data and hinder their re-purposing in other use cases. In addition, the proliferation of multitude of different data repositories, with partially redundant storage of similar data are yet another obstacle to their continued usefulness. Similarly, interfaces where annotation is spread across multiple web pages, use of accession identifiers with ambiguous and multiple interpretations and lack of good curation make these data-sets difficult to use. We have produced SpiderSeqR, an R package, whose main features include the integration between NCBI GEO and SRA databases, enabling an integrated unified search of SRA and GEO data-sets and associated annotations, conversion between database accessions, as well as convenient filtering of results and saving past queries for future use. All of the above features aim to promote data reuse to facilitate making new discoveries and maximising the potential of existing data-sets.Availabilityhttps://github.com/ss-lab-cancerunit/SpiderSeqR

Download Full-text

OnTheFly2.0: a text-mining web application for automated biomedical entity recognition, document annotation, network and functional enrichment analysis

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqab090 ◽

2021 ◽

Vol 3 (4) ◽

Author(s):

Fotis A Baltoumas ◽

Sofia Zafeiropoulou ◽

Evangelos Karatzas ◽

Savvas Paragkamian ◽

Foteini Thanati ◽

...

Keyword(s):

Web Application ◽

Named Entity Recognition ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Entity Recognition ◽

Clinical Biomarkers ◽

Processing Information ◽

Meta Analyses ◽

Or Genes

Abstract Extracting and processing information from documents is of great importance as lots of experimental results and findings are stored in local files. Therefore, extracting and analyzing biomedical terms from such files in an automated way is absolutely necessary. In this article, we present OnTheFly2.0, a web application for extracting biomedical entities from individual files such as plain texts, office documents, PDF files or images. OnTheFly2.0 can generate informative summaries in popup windows containing knowledge related to the identified terms along with links to various databases. It uses the EXTRACT tagging service to perform named entity recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and gene ontology terms. Multiple files can be analyzed, whereas identified terms such as proteins or genes can be explored through functional enrichment analysis or be associated with diseases and PubMed entries. Finally, protein–protein and protein–chemical networks can be generated with the use of STRING and STITCH services. To demonstrate its capacity for knowledge discovery, we interrogated published meta-analyses of clinical biomarkers of severe COVID-19 and uncovered inflammatory and senescence pathways that impact disease pathogenesis. OnTheFly2.0 currently supports 197 species and is available at http://bib.fleming.gr:3838/OnTheFly/ and http://onthefly.pavlopouloslab.info.

Download Full-text