Cross-Species (Heterologous Hybridization) Microarray Analysis Help
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Entering edit mode
10.4 years ago
sam22 • 0

Hello,

I hope someone can help me

I am currently working with a genome and heterologous hybridization microarrays data from agilent. The probes for the microarray were design previously to the NGS sequencing from my genome.

exemplification of type of microarray http://postimg.org/image/vqbvfd3id/

So they used of a closely related Genome (species B ) to design the 60-mer probes.

Meanwhile, the genome of specie A (my genome) was sequenced.

Since the previous analysis of the microarray data gave small changes in the expression of the genome and also a lot of background so I inquired if the probes design were appropriated and if possible by removing some inappropriate probes the result would be more correct.

I used blastn from stand alone blast to verify if the probes matched my genome. However, most of the probes weren’t a perfect match. Most of them have several mismatches, some gaps and rarely the full length.

Table: example output blast for gene 300 http://postimg.org/image/ezkotebyp/

From what I see can I say that gene 300 will hybridize with only Ras_56701_D or with Ras_56701_D , Ras_56377_D , Ras_46891_R_m or more or none. Well if 43 nucleotides with 8 mismatches would hybridize so would 42 with 8 mismatches.

Do I need to see were in the probe the mismatches and the gaps happen? Could a gap in a certain place be less “damaging” to the hybridization than several mismatches?

What is the acceptable threshold? There is some better way to score these alignments?

Thanks.

Regard,

Sam.

microarray blastn • 1.9k views
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Hi Sam, this is a really interesting question. It's important to note that molecular binding, (what you're measuring), will not be a linear function of the count of mismatches. Series of CGCG will bind more easily/tightly than entropic 4-mers. So it might not be a good idea to try to look at the data in such a way. Instead focus on the probe-level intensities and their annotation files. The microarray will be defined with assay ID#s and you can look at their statistics. Was this a sample-sample comparison experimental design? I can't tell what you're trying to score threshold.

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Hi karl, Thank for your reply. The condition A (sample A-my genome) it’s the same in several microarrays, the Sample B is the same species (A) but in a different condition. When I talk of a threshold I was thinking of cutoff value. I will try to look at my microarray data (raw data) and see if I can make sense of it. I hoped that I could remove some of the probes by the blastn result before analyzing the microarray data so the probes that are not appropriated would be remove. Thanks.

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