Thierry Lecroq B

CONSENT: Scalable long read self-correction and assembly polishing with multiple sequence alignment

CONSENT corrects long reads using multiple sequence alignment and de Bruijn graphs, outperforming existing methods on Oxford Nanopore data and enabling efficient processing of ultra-long reads.

Long-read error correction: a survey and qualitative comparison

This paper surveys and benchmarks long-read error correction tools, evaluating their performance across various datasets and error characteristics.

Improving bioinformatics prediction of microRNA targets by ranks aggregation

The paper introduces miRabel, a tool that aggregates results from three miRNA prediction algorithms to improve target prediction accuracy and consistency.

UMI-VarCal: a new UMI-based variant caller that efficiently improves low-frequency variant detection in paired-end sequencing NGS libraries

UMI-Gen: a UMI-based reads simulator for variant calling evaluation in paired-end sequencing NGS libraries

UMI-Gen simulates UMI-based reads for variant calling evaluation in paired-end sequencing, allowing benchmarking of variant callers at low frequencies.

ELECTOR: Evaluator for long reads correction methods

ELECTOR evaluates long reads correction methods by providing efficient and comprehensive metrics to assess quality improvements.

Hybrid correction of highly noisy Oxford Nanoporelong reads using a variable-order de Bruijn graph

This paper introduces HG-CoLoR, a method to correct noisy Oxford Nanopore long reads using a variable-order de Bruijn graph, achieving high-quality correction with efficient runtime.