Background: High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) has become a\nroutine tool for biodiversity survey and ecological studies. By including sample-specific tags in the primers prior PCR\namplification, it is possible to multiplex hundreds of samples in a single sequencing run. The analysis of millions of\nsequences spread into hundreds to thousands of samples prompts for efficient, automated yet flexible analysis\npipelines. Various algorithms and software have been developed to perform one or multiple processing steps, such\nas paired-end reads assembly, chimera filtering, Operational Taxonomic Unit (OTU) clustering and taxonomic\nassignment. Some of these software are now well established and widely used by scientists as part of their\nworkflow. Wrappers that are capable to process metabarcoding data from raw sequencing data to annotated OTUto-\nsample matrix were also developed to facilitate the analysis for non-specialist users. Yet, most of them require\nbasic bioinformatic or command-line knowledge, which can limit the accessibility to such integrative toolkits.\nFurthermore, for flexibility reasons, these tools have adopted a step-by-step approach, which can prevent an easy\nautomation of the workflow, and hence hamper the analysis reproducibility.\nResults: We introduce SLIM, an open-source web application that simplifies the creation and execution of\nmetabarcoding data processing pipelines through an intuitive Graphic User Interface (GUI). The GUI interact with\nwell-established software and their associated parameters, so that the processing steps are performed seamlessly\nfrom the raw sequencing data to an annotated OTU-to-sample matrix. Thanks to a module-centered organization,\nSLIM can be used for a wide range of metabarcoding cases, and can also be extended by developers for custom\nneeds or for the integration of new software. The pipeline configuration (i.e. the modules chaining and all their\nparameters) is stored in a file that can be used for reproducing the same analysis.\nConclusion: This web application has been designed to be user-friendly for non-specialists yet flexible with\nadvanced settings and extensibility for advanced users and bioinformaticians. The source code along with full\ndocumentation is available on the GitHub repository (https://github.com/yoann-dufresne/SLIM) and a\ndemonstration server is accessible through the application website (https://trtcrd.github.io/SLIM/).
Loading....