Corona Virus Gene Sequence Analysis In MATLAB

Project Abstract

load sequence.mat
sequence
%%
figure
ntdensity(sequence)
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bases = basecount(sequence)
%%
compBases = basecount(seqrcomplement(sequence))
%%
figure
basecount(sequence,'chart','pie');
title('Distribution of Nucleotide Bases for Corona Virus Genome');
%%
figure
dimers = dimercount(sequence,'chart','bar')
title('Corona Virus Genome Dimer Histogram');
%%
seqshoworfs(sequence);
orfs = seqshoworfs(sequence,'GeneticCode','Vertebrate Mitochondrial',...
        'AlternativeStartCodons',true)

A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). As of Jan 26, 2020, more than 2000 cases of 2019-nCoV infection have been confirmed, most of which involved people living in or visiting Wuhan, and human-to-human transmission has been confirmed

Findings

The ten genome sequences of 2019-nCoV obtained from the nine patients were extremely similar, exhibiting more than 99·98% sequence identity. Notably, 2019-nCoV was closely related (with 88% identity) to two bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21, collected in 2018 in Zhoushan, eastern China, but were more distant from SARS-CoV (about 79%) and MERS-CoV (about 50%). Phylogenetic analysis revealed that 2019-nCoV fell within the subgenus Sarbecovirus of the genus Betacoronavirus, with a relatively long branch length to its closest relatives bat-SL-CoVZC45 and bat-SL-CoVZXC21, and was genetically distinct from SARS-CoV. Notably, homology modelling revealed that 2019-nCoV had a similar receptor-binding domain structure to that of SARS-CoV, despite amino acid variation at some key residues

Corona Virus Gene Sequence Analysis In MATLAB

Take care of your health and protect others by doing the following:

Wash your hands frequently

Regularly and thoroughly clean your hands with an alcohol-based hand rub or wash them with soap and water.

Why? Washing your hands with soap and water or using alcohol-based hand rub kills viruses that may be on your hands.

Maintain social distancing

Maintain at least 1 metre (3 feet) distance between yourself and anyone who is coughing or sneezing.

Why? When someone coughs or sneezes they spray small liquid droplets from their nose or mouth which may contain virus. If you are too close, you can breathe in the droplets, including the COVID-19 virus if the person coughing has the disease.

Avoid touching eyes, nose and mouth

Why? Hands touch many surfaces and can pick up viruses. Once contaminated, hands can transfer the virus to your eyes, nose or mouth. From there, the virus can enter your body and can make you sick.

Practice respiratory hygiene

Make sure you, and the people around you, follow good respiratory hygiene. This means covering your mouth and nose with your bent elbow or tissue when you cough or sneeze. Then dispose of the used tissue immediately.

Why? Droplets spread virus. By following good respiratory hygiene you protect the people around you from viruses such as cold, flu and COVID-19.

If you have fever, cough and difficulty breathing, seek medical care early

Stay home if you feel unwell. If you have a fever, cough and difficulty breathing, seek medical attention and call in advance. Follow the directions of your local health authority.

The coronavirus pandemic has brought about a need for quick and accurate analysis of the virus's genetic makeup. One tool that can be used for this analysis is MATLAB. MATLAB is a powerful programming language that can be used for a wide range of applications, including bioinformatics.

To analyze the gene sequence of the coronavirus in MATLAB, the first step is to obtain the sequence data. This can be done by downloading the data from public databases such as GenBank. Once the data is obtained, it can be loaded into MATLAB using the appropriate functions.

Once the data is loaded, it can be analyzed using a variety of bioinformatics tools available in MATLAB. These tools can be used to perform tasks such as sequence alignment, motif discovery, and gene annotation. For example, the Bioinformatics Toolbox in MATLAB can be used to align the coronavirus sequence with other known sequences, and to search for potential drug targets.

Another useful tool in MATLAB for coronavirus gene sequence analysis is the Global Alignment Kernel (GAK) which can be used to compare the genetic sequence of different coronavirus strains and identify mutations or variations.