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I have a heat-map of gene expression measurements (log₂-transformed microarray signals, after inter-microarray data normalization, etc.) that I am using to illustrate the expression of 72 genes ('rows' of the heat-map) which I had identified as differentially expressed among different sub-groups of the 60 samples ('columns' of the heat-map, ordered by sub-groups) of my study. The ranges of gene measurements are within the 1-12 range (e.g., 4-8 for gene X, 2-10 for gene Y, and so on). It is a two-color heat-map, with the brightest green, black, and brightest red colors of the color scale used for values 1, 4 and 12, respectively. You can see an image here: http://i.imgur.com/JBu9f.png

A reviewer has commented that the heat-map will be more informative if Z-scores of the gene expression measurements are used instead. I don't get this because to me it seems that the heat-map will be less informative; Z-scoring will reduce the dimensionality of the data as one can no longer compare one gene to another for a given sample.

Can anyone comment on this? Thanks.

I have a heat-map of gene expression measurements (log₂-transformed microarray signals, after inter-microarray data normalization, etc.) that I am using to illustrate the expression of 72 genes ('rows' of the heat-map) which I had identified as differentially expressed among different sub-groups of the 60 samples ('columns' of the heat-map, ordered by sub-groups) of my study. The ranges of gene measurements are within the 1-12 range (e.g., 4-8 for gene X, 2-10 for gene Y, and so on). It is a two-color heat-map, with the brightest green, black, and brightest red colors of the color scale used for values 1, 4 and 12, respectively.

A reviewer has commented that the heat-map will be more informative if Z-scores of the gene expression measurements are used instead. I don't get this because to me it seems that the heat-map will be less informative; Z-scoring will reduce the dimensionality of the data as one can no longer compare one gene to another for a given sample.

Can anyone comment on this? Thanks.

An image showing the current and reviewer-proposed heat-maps can be seen here: https://i.sstatic.net/haeZ9.png

I have a heat-map of gene expression measurements (log₂-transformed microarray signals, after inter-microarray data normalization, etc.) that I am using to illustrate the expression of 72 genes ('rows' of the heat-map) which I had identified as differentially expressed among different sub-groups of the 60 or so samples ('columns' of the heat-map, ordered by sub-groups) of my study. The ranges of gene measurements are within the 4-16 range (e.g., 4-8 for gene X, 7-14 for gene Y, and so on). It is a two-color heat-map, with the brightest green, black, and brightest red colors of the color scale used for values 4, 10 and 16, respectively

A reviewer has commented that the heat-map will be more informative if Z-scores of the gene expression measurements are used instead. I don't get this because to me it seems that the heat-map will be less informative; Z-scoring will reduce the dimensionality of the data as one can no longer compare one gene to another for a given sample.

Can anyone comment on this? Thanks.

I have a heat-map of gene expression measurements (log₂-transformed microarray signals, after inter-microarray data normalization, etc.) that I am using to illustrate the expression of 72 genes ('rows' of the heat-map) which I had identified as differentially expressed among different sub-groups of the 60 samples ('columns' of the heat-map, ordered by sub-groups) of my study. The ranges of gene measurements are within the 1-12 range (e.g., 4-8 for gene X, 2-10 for gene Y, and so on). It is a two-color heat-map, with the brightest green, black, and brightest red colors of the color scale used for values 1, 4 and 12, respectively. You can see an image here: http://i.imgur.com/JBu9f.png

A reviewer has commented that the heat-map will be more informative if Z-scores of the gene expression measurements are used instead. I don't get this because to me it seems that the heat-map will be less informative; Z-scoring will reduce the dimensionality of the data as one can no longer compare one gene to another for a given sample.

Can anyone comment on this? Thanks.

I have a heat-map of gene expression measurements (log₂-transformed microarray signals, after inter-microarray data normalization, etc.) that I am using to illustrate the expression of 72 genes which I had identified as differentially expressed among different sub-groups of the 60 or so samples of my study.

A reviewer has commented that the heat-map will be more informative if Z-scores of the gene expression measurements are used instead. I don't get this because to me it seems that the heat-map will be less informative; Z-scoring will reduce the dimensionality of the data as one can no longer compare one gene to another for a given sample.

Can anyone comment on this? Thanks.

I have a heat-map of gene expression measurements (log₂-transformed microarray signals, after inter-microarray data normalization, etc.) that I am using to illustrate the expression of 72 genes ('rows' of the heat-map) which I had identified as differentially expressed among different sub-groups of the 60 or so samples ('columns' of the heat-map, ordered by sub-groups) of my study. The ranges of gene measurements are within the 4-16 range (e.g., 4-8 for gene X, 7-14 for gene Y, and so on). It is a two-color heat-map, with the brightest green, black, and brightest red colors of the color scale used for values 4, 10 and 16, respectively

A reviewer has commented that the heat-map will be more informative if Z-scores of the gene expression measurements are used instead. I don't get this because to me it seems that the heat-map will be less informative; Z-scoring will reduce the dimensionality of the data as one can no longer compare one gene to another for a given sample.

Can anyone comment on this? Thanks.