PIPprofileR

A tool to easily generate Profiles of Percent Identical Positions from a fasta file (nucleotide or peptide sequences). With the help of an annotation file, it will be possible to simply explore the results.

Why ?

PIP profiles are widely used by virologists to detect recombination events and can be found in most publications concerning the origins of SARS-CoV-2.

How to use ?

1- Firstly, you should select a demo dataset, upload a FASTA file or a Rdata file (previous analysis).

2- [not mandatory] Add an annotation file to enrich the exploration of the PIP profile or refine the search during alignments.

3- Align sequence (if you have imported a fasta file) and explore PIP profile.

Use cases

- Virology researchers who wish to compare genomic or protein sequences from different viral strains. A example is available here https://doi.org/10.1051/medsci/2020123

- Teachers/trainers in the context of biological sequence analysis TP. A example is available here https://jvanheld.github.io/shnc-origines-sars-cov-2/

Publication

Sallard, E., Halloy, J., Casane, D., van Helden, J. & Decroly, É. 2020. Retrouver les origines du SARS-CoV-2 dans les phylogénies de coronavirus. Med Sci (Paris) 36: 783–796. https://doi.org/10.1051/medsci/2020123

1- Select Reference sequence

Select the reference sequence from all available sequences in the data.

2- Select query sequences

Select the sequences to be aligned against the reference sequence. Clear All

3- Pairwise Alignment type

Type of alignment for the function pairwiseAlignment (Biostrings).

Documentation :

4- Select a window size

Size of the sliding window to calculate PIP profiles

Run

PIP exploration

The table below is dynamic. Hover the graph or select an area
Show the strains / species displayed in the table below Update

Annotation

Hover over the plot to get the annotation information. The blue arrows are strand + and the orange arrows strand -.