A pangenome represents the total genetic diversity of a species or a species complex. One can describe pangenomes in terms of gene presence / absence variations (PAVs) but a more recent alternative aims to integrate full length genomes in a sequence graph . In particular, pairwise alignments of a genome set can be used to build a “Variation Graph” (VG) in which nodes represent words of genome fragments and edges represent the contiguity of the words in one to several genomes (e.g., edges are associated to genome subsets). Each input genome consequently corresponds to a particular path in the graph. It has been showed that VGs can improve variant calling and genotyping processes . Indeed, variant calling is often based on the mapping of linear query sequences to linear reference genomes, thus biasing the prediction to regions present in the reference and limiting the identification of structural variations that are specific to other genomes. In particular, biases are reduced when large structural variations (>50bp) are targeted. Identifying new variants via a pangenome graph requires a compulsory preliminary step of querying sequence to graph mapping. Several approaches have been proposed, with algorithms dedicated to either long or short sequence reads. Most of these tools use a 2 steps method with : a) the identification of candidate sub-graphs showing similarity to the query read via different techniques of indexation followed by b) a refined alignment in the selected sub-graphs (generally via a technique of partial order alignment). In practice, it remains unclear how this preliminary will impact further variants predictions. In particular, it has yet to be shown how resilient will be the different approaches to diverse mutation and indel rates. The poster will present the results produced by Hajar Bouamout during her Master internship dedicated to the evaluation of sequence to graph read mapping tools. It will briefly describe the main ideas behind the algorithms proposed by 4 tool: GraphAligner, vg map, vg giraffe and Minichain and report benchmarks made with these tools.