README.md

In HetzDra/turboGliph: Find Specificity Groups with GLIPH and GLIPH2 Method

turboGliph

GLIPH (Grouping of Lymphocyte Interactions by Paratope Hotspots) is an algorithm developed by Glanville et al. to identify specificity groups in the T cell receptor repertoire based on local (motif sharing) and global (hamming distance) similarities. [1,2]

The authors of the paper published a version of GLIPH written in Perl [2], but its disadvantage is a long runtime, especially for larger sample sizes. Recently, with a new version of the package, GLIPH2, they introduced an improved algorithm that speeds up the analysis by substituting repeated sampling by Fisher's exact test to assess the statistical significance of a given motif. [3,4]

In this R implementation of GLIPH we followed their Perl script and we tried to include all the options of the original algorithm, but with a constant look on the analysis speed. With an input size of ~10,000, this R implementation is about 50 times faster and for an input size of ~100,000 sequences it is about 500 times faster than the Perl script. In addition, we implemented a function for visualizing the clusters generated by GLIPH, which enables graphical processing and analysis of GLIPH results through numerous customization options. The implementation of GLIPH2 as well as the function gliph_combined, which combines the different features of GLIPH and GLIPH2 in a customizable way, complete this package and allow the user to use the different GLIPH algorithms according to his own needs.

For more information about the functions included in this package see the included vignette.

For more details about the method we recommend reading the original papers and the GLIPH/GLIPH2 documentation on github. [1,2,3,4]

1: Glanville, Jacob, et al. "Identifying specificity groups in the T cell receptor repertoire." Nature 547.7661 (2017): 94. 2: https://github.com/immunoengineer/gliph 3: Huang, Huang, et al. "Analyzing the Mycobacterium tuberculosis immune response by T-cell receptor clustering with GLIPH2 and genome-wide antigen screening." Nature Biotechnology 38.10 (2020): 1194-1202. 4: http://50.255.35.37:8080/tools

HetzDra/turboGliph documentation built on Oct. 2, 2022, 2:22 a.m.