How is the average and normalization of each column in the table using "for" loop?

I have a table with 50x10. In the table, first column is Genes and the second column will be reference column for normalization. Other 8 column will divide reference column. Afterward, this table will be normalized and each column will be averaged after normalization. Therefore there will be one row and 8 columns. How can I do this process in a table. Is it necessary to convert this table to a matrix or dataset, or can we solve it with a simle loop?

I m trying this code for table:

%import data 
data = readtable("data.xlsx", "UseExcel", false);
%I coverted table to matrix form by deleting first row
for i = 2:10
    res(:,i-1) = data(:,i)./data(:,1);
        res_m = mean(res);
    
end

Bu code is not working as I want and I want to try this with table or dataset form

% Genes	gsm335244	gsm335245	gsm335246
% A1CF	1,194	         0,848	         0,905
% A2M	        0,325	         6,301	         0,607
% A4GALT	1,048	         0,592	         1,964

[KALYAN ACHARJYA]

In the RHS, what does it mean?

res(:,i-1)=data(:,i)./data(:,1);  % RHS > Same Parameters  

Please attach data file

[expert]

I converted data to a mtrix form, I did calculation with these code:

for i = 2:10
    res(:,i-1) = data(:,i)./data(:,1);
    res_norm = normalize(res,'norm',Inf);
    res_m = mean(res_norm);
end

in the res_m data, there are means of each column but there are nocolumn legends and I tried some plots but I could not obtain good plot. I think it is better use dataset or table form. What do you think?

Answer 1

[Srijith Kasaragod]

From my understanding you have a 50x10 table, columns 3 to 10 must be divided with corresponding elements from column 2, followed by taking the mean of those eight columns. The required output can be obtained by simple manipulation of the table. Following code implements the steps:

%reading the table 
data= readtable('data.xlsx'); 
%perform normalization and take mean of columns 
data{:,3:end}=data{:,3:end}./data{:,2}; 
data= mean(data{:,3:end}) 

Final result is a table of size 1x8 which contains mean of columns 3 to 10.