BigPint Bioconductor package that makes BIG (RNA seq) data pint sized
The BigPint package can help examine any large multivariate dataset. However, we note that the example datasets and example code in this package consider RNA-sequencing datasets. If you are using this software for RNA-sequencing data, then it can help you confirm that the variability between your treatment groups is larger than that between your replicates and determine how various normalization techniques in popular RNA-sequencing analysis packages (such as edgeR, DESeq2, and limma) affect your dataset. Moreover, you can easily superimpose lists of differentially expressed genes (DEGs) onto your dataset to check that they show the expected patterns (large variability between treatment groups and small variability between replicates).
BigPint software website: https://lindsayrutter.github.io/bigPint/
Article explaining the BigPint methodology: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2968-1
Research article showcasing the BigPint software: https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-019-5767-1
Article explaining the BigPint software: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007912
Project Author(s)
Lindsay Rutter; Dianne Cook
Project Links
https://github.com/lindsayrutter/bigPint
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