DNA Microarray analysis help please!

[DNA_science]

I need DNA Microarray analysis help please!

I have generated data but I need software for statistical analysis.
Please help,
thanks in advance!

[dave2006]

Several Bioinformatic Programs for your analysis:
[Only registered users see links. ]

[Only registered users see links. ]


Cheers

[admin]

Hey Guys, look for upcoming articles at our new website:
Microarray Station

Also, there are sections there that have many bioinformatic programs and software. I am not exactly an expert at analyzing microarray data although I have some ideas...however the people working on those sites are. There should be a forum up there or it will link here and you can get help from them.

Cheers.

[Aristotle]

Are there any tutorials to help in the analysis of microarrays?

thanks

[signalpathways]

Hello
I read article about microarray. Could you tell me what 22K or 44K array means? and what "spike-in" means?

please

[oBWhat]

Hey Signal,
22k and 44k probably refer to the number of capture molecules (primers or cDNA capture molecules) located on the array. They can be even overlapping primers / cDNAs, or even primers that act as controls for other primers (ie to test background).

There can be 1-100 primers for a single gene (cDNA), so the 44K is quite large.

[stanleygeorge]

Hi,

Well when we talk about microarray data analysis it starts with normalization and can proceed till the biological interpretation. I am into the field of DNA data analysis and can even perform for you. There are several tutorials available on this topic. However, I believe that a good knowledge of statistics is required for the data analysis. As far as interpretation of DNA microarray data is concerned, I do not know what sort of experiment you are performing. Based on your experiment several other interpretation analysis can be performed besides GO based clustering and pathway analysis. If you need more information hesitate not to contact me.

Stanley

[cyberpostdoc]

R: open source statistics package.

Cyberpostdoc recommends R for statistics, biological data manipulations and graphics:

1. Describe basic statistics of your data.
2. Statistical tests can be done with simple, easy to understand commands.
3. Open source packages specific to microarray analysis.
4. R scripting language can further be used to program for more sophisticated tasks.
5. Example:
Data: Affymetrix microarray expression levels (HG-U95A) of seven genes inferred from the average difference values (AD), random picked from Su et al..
amygdala thalamus fetal brain whole brain caudate nucleus testis
gene1 32.47 39.17 32.33 29.37 44.65 84.59
gene2 54.51 64.76 40.52 31.26 50.92 45.76
gene3 12.14 8.78 3.59 5.43 7.22 48.67
gene4 65.95 5.49 28.54 109.90 83.06 304.02
gene5 34.61 43.86 36.54 35.67 36.44 27.65
gene6 134.53 147.83 133.96 33.89 130.17 216.44
gene7 62.09 25.48 52.20 67.65 44.14 122.73


Read the data in as tab-delimited file, gene names as rows, tissues as columns:
> as.matrix(read.table(file="p0002_data",sep="t",row .name=1,header=TRUE))->test.data


Boxplot shows that gene6 expression level is generally higher than others and that gene4 expression level varies the most across tissues; Pearson correlations of transcription profiles specified by genes can be used to cluster tissues:
> par(mfrow=c(1,2),mar=c(20,3,1,0)) // plot two image side by side
> boxplot(as.data.frame(t(test.data)),col=c(1:7),las =2) // boxplot at left
> plot(hclust(as.dist(1-cor(test.data,method="Pearson")),method="a"),xlab= "",main="") // cluster dendrogram at right, use Pearson correlation as distance, agglomeration method for clustering is "average"

Image


T-test show different in expression levels between gene5 and gene6:
> t.test(test.data["gene6",],test.data["gene5",])

Image

I am not allowed to paste image yet, so please go to my website and look into bioinformatics -> software review section.

[ecualchem]

You can find a download book in the pages of embrace (seeks with google) click in the next and last courses choose the finland (I believe that it is) courses and choose books section and OK here you are your book.
Or (csc.fi/csc) +arraybook_overview Maybe go direct
Best regards
Ecualchem

[nnath]

Dear Stanley ,

I am doing some microarray analysis and I am very confused with some of the steps. Would you be able to provide me some advice on the same?

Thanks