Spatial Analysis of Amino Acid Patterns

This repository contains R code for performing spatial analysis of amino acid patterns in biological sequences. The code utilizes various functions from stringr, mmand, and ape libraries for pattern recognition, frequency analysis, morphological operations, and phylogenetic tree construction. Below, you will find documentation on how to use the code and its functionalities. Olfaction plays a crucial role in insects, including the common fruit fly Drosophila melanogaster. Drosophila melanogaster possesses 66 distinct olfactory receptor protein sequences, showcasing significant diversity. This article presents a novel approach for clustering these 66 protein sequences using image-based similarity indices derived from mathematical morphology. Two distinct methodologies are explored: one leveraging the natural occurrence of the twenty standard amino acids, while the other employs chemical grouping of amino acids. A specific metric is devised to facilitate clustering of pairs of sequences based on their similarity indices, categorizing them into three classes: Highest, Moderate, and Least. Notably, OR83b emerges as a prominent olfactory receptor expressed across diverse insect populations, a finding corroborated quantitatively through our investigation.

Installation

To run the code, you need to have R installed on your system along with the following libraries:

• stringr
• mmand
• ape

You can install these libraries using the following R commands:

install.packages("stringr")
install.packages("mmand")
install.packages("ape")

Usage

1. Clone the Repository:

git clone https://github.com/tayyabrahmani/Protein-Sequence-analysis.git

2. Prepare Data: Ensure that your data is in the appropriate format. For the amino acid analysis, the sequences should be in a file named drosophilaaligned.txt. Each sequence should be separated by a newline character.

3. Run the R Script: Open RStudio or any R environment and run the script algorithm.R. Ensure that all required libraries are loaded.

4. Interpret Results: After running the script, you will get various outputs including heatmaps, dendrograms, and phylogenetic trees. Interpret these results based on your analysis requirements.

Code Overview

The code performs the following main tasks:

• Pattern Recognition: Defines amino acid patterns and identifies their frequencies in biological sequences.
• Infima and Suprema Calculation: Computes infima and suprema matrices based on the identified patterns.
• Area Interaction Matrix: Calculates area interaction matrices using infima and suprema matrices.
• Grayscale Morphological Operations: Performs grayscale morphological dilation and erosion operations to compute distances.
• Ranking Spatial Fields: Ranks pairs of spatial fields based on spatial interactions.
• Phylogenetic Tree Construction: Constructs phylogenetic trees and dendrograms based on the spatial analysis results.