MOTIVATION: The combination of long-read sequencing technologies like Oxford Nanopore with single-cell RNA sequencing (scRNAseq) assays enables the detailed exploration of transcriptomic complexity, including isoform detection and quantification, by capturing full-length cDNAs. However, challenges remain, including the lack of advanced simulation tools that can effectively mimic the unique complexities of scRNAseq long-read datasets. Such tools are essential for the evaluation and optimization of isoform detection methods dedicated to single-cell long-read studies. RESULTS: We developed AsaruSim, a workflow that simulates synthetic single-cell long-read Nanopore datasets, closely mimicking real experimental data. AsaruSim employs a multi-step process that includes the creation of a synthetic count matrix, generation of perfect reads, optional PCR amplification, introduction of sequencing errors, and comprehensive quality control reporting. Applied to a dataset of human peripheral blood mononuclear cells, AsaruSim accurately reproduced experimental read characteristics. AVAILABILITY AND IMPLEMENTATION: The source code and full documentation are available at https://github.com/GenomiqueENS/AsaruSim.

MOTIVATION: Data management and quality control of output from Illumina sequencers is a disk space- and time-consuming task. Thus, we developed Aozan to automatically handle data transfer, demultiplexing, conversion and quality control once a run has finished. This software greatly improves run data management and the monitoring of run statistics via automatic emails and HTML web reports. AVAILABILITY AND IMPLEMENTATION: Aozan is implemented in Java and Python, supported on Linux systems, and distributed under the GPLv3 License at: http://www.outils.genomique.biologie.ens.fr/aozan/ . Aozan source code is available on GitHub: https://github.com/GenomicParisCentre/aozan . CONTACT: [email protected].

UNLABELLED: We developed a modular and scalable framework called Eoulsan, based on the Hadoop implementation of the MapReduce algorithm dedicated to high-throughput sequencing data analysis. Eoulsan allows users to easily set up a cloud computing cluster and automate the analysis of several samples at once using various software solutions available. Our tests with Amazon Web Services demonstrated that the computation cost is linear with the number of instances booked as is the running time with the increasing amounts of data. AVAILABILITY AND IMPLEMENTATION: Eoulsan is implemented in Java, supported on Linux systems and distributed under the LGPL License at: http://transcriptome.ens.fr/eoulsan/

SUMMARY: Doelan is an automated tool designed to monitor the quality of DNA microarray production. The software executes a series of quality control tests on hybridizations to validate batches of chips. The reports generated by Doelan should help microarray platforms aiming at quality labels, such as ISO 9001 certification. The Doelan application is written in Java and works with a plug-in system that allows everyone to add custom validation tests. AVAILABILITY: The Doelan application is distributed under the GNU General Public License at http://transcriptome.ens.fr/doelan/