Parallel coordinate plots, scatterplot matrices, and replicate line plots are useful visual tools to understand the relationship between variables in datasets. However, these plots are not typically effective when working with large multivariate datasets due to computational time constraints and overplotting problems. Here, we propose to develop an R package that provides tailored versions of these plots that can effectively be used with large multivariate datasets, and we aim to achieve this by leveraging interactivity, linking, and summarization techniques. These new methods could be useful for RNA-sequencing analysis, factor analysis, principal component analysis, and discriminant analysis. Once the new methods have been tested on large multivariate datasets across different fields, they will be combined into an R package called bigPint for the R community.