How to normalize Microarray expression data?
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Biologist ▴ 120
@biologist-9801
Last seen 4.7 years ago

I have a data frame "df" like following with Microarray expression Data (Affymetrix SNP 6.0 data):

 

  S1 S2 S3 S4 S5 S6 S7
A1BG 6.429276339 6.338451158 6.333760753 6.419191996 6.503471181 6.329103499 6.211373601
A2BP1 6.379471993 6.296018518 6.237316465 6.2696332 6.329489132 6.359770303 6.240070336
A2M 12.84498365 12.00265682 13.92741965 12.553162 13.39001307 13.8933423 12.58695704
A2ML1 8.661860382 6.723004202 6.300975176 7.661012019 7.905219709 6.957578023 6.70945883
A3GALT2 6.945382967 6.814979733 6.575916303 6.63460198 6.627380524 6.733926424 6.280618235
A4GALT 9.280222581 8.81560969 9.683073561 9.480038673 8.801438707 9.190943942 7.743705471
A4GNT 6.593564871 6.63502488 6.389962535 6.511360029 6.694572404 6.6492763 6.527199544
AAA1 6.431615372 6.309515078 6.248153876 6.329288965 6.46768078 6.355268547 6.384284754
AAAS 7.513349406 7.234654595 7.490935892 6.801368215 7.323811386 7.018733196 7.055932044

I want to make a clustering heat map for this data. But before that I want to apply Normalization on it. I would like to know which normalization should be applied on this type of data and which R package and function should I use for this?

Thank you !!

r affymetrix microarrays normalization bioconductor • 1.6k views
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Have you tried asking Dr. Google? Googling `microarray data analysis using r` brings up this Bioconductor guide as first hit.

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@james-w-macdonald-5106
Last seen 1 day ago
United States

That doesn't look like SNP data to me. In other words, it is not common to use HUGO gene symbols to annotate SNPs, because most are not within a gene, and for those that are there are usually more than one. So probably you should figure out exactly what those data are before proceeding.

In addition, you are asking for analysis advice rather than technical advice. This support site is intended to help people with technical problems with Bioconductor packages. If you are planning to analyze these data, then you should also have to take the responsibility for knowing what you are doing and being able to defend what you have done. If you don't know what you are doing, then your best recourse is to find somebody local who does. Failing that, you should try to educate yourself. You may be able to get some random person on a support site to give you advice (without knowing the least thing about your experiment), but that advice is likely to be worth about what you paid for it.

 

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Although the question says "Affymetrix SNP 6.0 data", it also says "Microarray expression Data". Thus, it may very well be an expression array, not a SNP array. Then gene symbols would make sense.

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