Biomedical subjects

Adam Ameur

Publications and source records attributed to Adam Ameur.

5 recordsLinked to original sources

PubMed2026

Toward the clinical application of long-read sequencing in repeat-expansion disorders.

Repeat-expansion disorders (REDs) are a mechanistically and clinically well-defined subgroup of rare diseases caused by the expansion of short tandem repeats (STRs). These expansions can exceed several kilobases and show complex features, such as noncanonical secondary structures, somatic instability, repeat interruptions and allele-specific methylation. These characteristics are highly relevant for understanding disease mechanisms, clinical variability, prognosis and potentially therapeutic decision-making, but cannot be fully resolved using traditional diagnostic methods or short-read sequencing technologies. By contrast, long-read sequencing (LRS) enables accurate investigation of STR complexity in a single assay, facilitates the discovery of new pathogenic repeat expansions and drives advances in diagnostics, clinical and basic research, which may allow for better patient stratification in future clinical trials. This Perspective discusses recent LRS-driven discoveries, methodological and bioinformatic advances, and emerging diagnostic applications to illustrate the potential of LRS in reshaping both research and clinical practice.

Humans↗

PubMed2026

Nallo: a Nextflow pipeline for comprehensive human long-read genome analysis.

MOTIVATION: Long-read sequencing (LRS) is increasingly used for human medical research and clinical diagnostics due to its capacity to generate complete genome information. However, there is a lack of robust and easy-to-use pipelines for comprehensive LRS data analysis. RESULTS: Here we present Nallo, a Nextflow pipeline for analysis of PacBio and Oxford Nanopore data, with additional support for rare disease research projects. The pipeline detects a wide range of genetic variants, performs genome assembly, and reports CpG methylation. It also enables annotation and ranking of variants based on their predicted functional consequences. AVAILABILITY AND IMPLEMENTATION: Nallo is available from GitHub: https://github.com/genomic-medicine-sweden/nallo.

Humans↗

PubMed2006

The LCB Data Warehouse.

UNLABELLED: The Linnaeus Centre for Bioinformatics Data Warehouse (LCB-DWH) is a web-based infrastructure for reliable and secure microarray gene expression data management and analysis that provides an online service for the scientific community. The LCB-DWH is an effort towards a complete system for storage (using the BASE system), analysis and publication of microarray data. Important features of the system include: access to established methods within R/Bioconductor for data analysis, built-in connection to the Gene Ontology database and a scripting facility for automatic recording and re-play of all the steps of the analysis. The service is up and running on a high performance server. At present there are more than 150 registered users. AVAILABILITY: An open functional version is available at https://dw.lcb.uu.se/index.phtml?i_login=test. User accounts are created upon request. Additional facilities including plug-ins, user documentation and a password protected data storage system are available from http://www.lcb.uu.se/lcbdw.php

Computer Graphics↗

PubMed2005

Binding sites for metabolic disease related transcription factors inferred at base pair resolution by chromatin immunoprecipitation and genomic microarrays.

We present a detailed in vivo characterization of hepatocyte transcriptional regulation in HepG2 cells, using chromatin immunoprecipitation and detection on PCR fragment-based genomic tiling path arrays covering the encyclopedia of DNA element (ENCODE) regions. Our data suggest that HNF-4alpha and HNF-3beta, which were commonly bound to distal regulatory elements, may cooperate in the regulation of a large fraction of the liver transcriptome and that both HNF-4alpha and USF1 may promote H3 acetylation to many of their targets. Importantly, bioinformatic analysis of the sequences bound by each transcription factor (TF) shows an over-representation of motifs highly similar to the in vitro established consensus sequences. On the basis of these data, we have inferred tentative binding sites at base pair resolution. Some of these sites have been previously found by in vitro analysis and some were verified in vitro in this study. Our data suggests that a similar approach could be used for the in vivo characterization of all predicted/uncharacterized TF and that the analysis could be scaled to the whole genome.

Base Pairing↗

PubMed2004

Global gene expression analysis by combinatorial optimization.

Generally, there is a trade-off between methods of gene expression analysis that are precise but labor-intensive, e.g. RT-PCR, and methods that scale up to global coverage but are not quite as quantitative, e.g. microarrays. In the present paper, we show how how a known method of gene expression profiling (K. Kato, Nucleic Acids Res. 23, 3685-3690 (1995)), which relies on a fairly small number of steps, can be turned into a global gene expression measurement by advanced data post-processing, with potentially little loss of accuracy. Post-processing here entails solving an ancillary combinatorial optimization problem. Validation is performed on in silico experiments generated from the FANTOM data base of full-length mouse cDNA. We present two variants of the method. One uses state-of-the-art commercial software for solving problems of this kind, the other a code developed by us specifically for this purpose, released in the public domain under GPL license.

Algorithms↗