I failed to come up with an algorithm based on dataset objects. I find the documentation hard to interpret. Here is an algorithm based on cell arrays. The result is in a structure, S, with one gene per field. I guess this dataset is not optimal for this problem.
function S = cssm()
% I have two datasets in
final = {
'Genes' 'T0&T2' 'T1&T3' 'T2&T4' 'T3&T5' 'T4&t6'
'YAR029W' 'd' [] 'd' [] 'd'
'YBL095W' 'd' [] [] 'd' 'd'
'YBL111C' 'u' 'u' 'u' 'u' []
'YBL113C' 'u' 'u' 'u' 'u' 'u'
'YBR096W' 'u' 'u' 'u' 'u' []
'YBR138C' 'd' [] [] 'd' 'd'};
Dataset1 = {
'Genes' 'T0&T2' 'T1&T3' 'T2&T4' 'T3&T5' 'T4&T6'
'YAR029W' 'dd' 'uu' 'dd' 'uu' 'du'
'YAR062W' 'du' 'uu' 'ud' 'uu' 'du'
'YAR068W' 'du' 'uu' 'uu' 'uu' 'uu'
'YBL095W' 'du' 'ud' 'ud' 'du' 'du'
'YBL111C' 'uu' 'uu' 'ud' 'ud' 'du'
'YBL113C' 'uu' 'uu' 'uu' 'ud' 'ud'
'YBR028C' 'du' 'uu' 'uu' 'ud' 'ud' };
for ff = 2 : size( final, 1 )
is_data = not( cellfun( @isempty, final( ff, 1:end ) ) );
S.( final{ff,1} ) = Dataset1( :, is_data );
S.( final{ff,1} )(ff,:) = final( ff, is_data );
end
end
==============
S = cssm()
S =
YAR029W: {8x4 cell}
YBL095W: {8x4 cell}
YBL111C: {8x5 cell}
YBL113C: {8x6 cell}
YBR096W: {8x5 cell}
YBR138C: {8x4 cell}
>> S.YAR029W
ans =
'Genes' 'T0&T2' 'T2&T4' 'T4&T6'
'YAR029W' 'd' 'd' 'd'
'YAR062W' 'du' 'ud' 'du'
'YAR068W' 'du' 'uu' 'uu'
'YBL095W' 'du' 'ud' 'du'
'YBL111C' 'uu' 'ud' 'du'
'YBL113C' 'uu' 'uu' 'ud'
'YBR028C' 'du' 'uu' 'ud'
