DNA Analysis Using S Transform Corrected

8/12/2019 DNA Analysis Using S Transform Corrected

1/25

DNA Analysis using

S-TransformSUPERVISOR Ms.T.M.INBAMALAR ,Associate Professor

PROJECT MEM ERS

B.SNEHAS.SUBHASHINIM.P.SUGANYA


2/25

INTRODUCTION Digital Signal Processing (DSP) has applications in genomic

sequence analysis . We use DSP principles to analyze DNA sequences, DNA sequences should be converted into numeric

sequences . DFT, digital filtering, DWT, Parametric modeling and entropy

are some of the important DSP concepts used for DNAanalysis.

we propose S transform based DNA analysis to improve the

performance of identification of exons in DNA sequences. DNA sequences will be downloaded from NCBI website .


3/25

LIFE STRAND(DNA)

DNA(DeoxyRibonucleic acid) is theone that inherits the

physical characteristicsand intellectualproperties of parent tothe offspring. A single strand of

DNA is a biomoleculehaving nucleotides. Eachnucleotide is designatedby 4 amino acids A, T, C,and G


4/25

DNA STRUCTURE


5/25

DOUBLE HELIX

DNAs-formed by twosingle strands pairingtogether -double helix A - T and C - G T gets converted into Uwhich gives rise to 16 to 20amino acids. DNA when replicatedforms RNA which inturnforms proteins Four amino acids form

groups of three giving 64genetic codes. Genetic code ATG-initiate Genetic code TAA-stops If this process doesnot

happen, it is mutation.


6/25

DIAGNOSING MUTATION Mutation may lead to many diseases.

To diagnose this , DNA code sequences are obtained from the blood bySEQUENCING.

Unlike taking blood sample, we take code sequences from NCBI website. As code sequences cannot be directly used, they are converted into

numerical sequences

EXISITING TECHNIQUES FT Filter STFT DWT Gabor wavelet transform


7/25

CHALLENGES FACED

Lack of clarity

More number of co-efficients obtained Outline is not clear Blurring Phase and Frequency problem


8/25

S- Transform

S-Transform is a generalised and extended formof STFT. It gives a time-frequency representation. We get co-efficients from the transform thatgives the exons present areas.


9/25

FORMULA


10/25

FLOWCHART

START

Obtain

sequence

ApplyS transform

Obtain peak

Compare withthreshold values

If TV>= OV?

Presence of

disease

Absence of

disease

yes no


11/25

IMPLEMENTATION

SOFTWARE

Matlab 2012


12/25

WORK DONE Implemented Fourier transform

*FFT Obtained Spectrum Identified Normal and Cancer cell. Tried implementation of S-Transform and got the

value. Exact spectrum is yet to be obtained.


13/25

OUTPUTS FOR FFT

Normal Cell (AF186607)


14/25

Normal Cell (AF065986)


15/25


16/25

Cancer cell (Af348515)


17/25

Cancer Cell (Nm012403)


18/25

Cancer cell


19/25

S-Transform Programclc;

close all ;

clear all; s=( 'GTCGACTCGATTCCTCAGTCTGACCTCTAAGCCTTGGTACTCTCTCTGAAGAGT' ); s=double(s); [rs cs]=size(s); for t=1:cs

if s(:,t)== 'A' s(:,t)=0.1206;

elseif s(:,t)== 'T' s(:,t)=0.1335;

elseif s(:,t)== 'G' s(:,t)=0.0806;

elseif s(t)== 'C' s(:,t)=0.1340;

end end

N=length(s); n=0:1:N-1; subplot(3,1,1); stem(n,s); fun = @(t,f) exp(((15-(t.^2)).*(f.^2))./2).*exp(-1i.*2.*pi.*f.*t).*(f./(2.*pi).^(1./2)); q = integral(@(t)fun(t,1),0,inf) subplot(3,1,2);

stem(q);


20/25

S-Transform Implementation


21/25

Output for S-Transform


22/25

CONCLUSION

CANCER CELL

Magnitude approx. = 100 NORMAL CELL

Magnitude approx. = 50


23/25

DISCUSSION

Understood that S-Transform helps to classifynormal and diseased cells.


24/25

FUTURE WORK

Apply many DNA inputs of normal anddiseased cell(Eg: HIV,Cancer etc) and obtainthe exact output.

Modify to get better performance.


25/25

DNA Analysis Using S Transform Corrected

Documents

Transcript of DNA Analysis Using S Transform Corrected