I am new to microarray analysis and need help on two fronts:
1. Can any one direct me to a resources that provide directions on a
how to systematically conduct an analysis of differential expression
data.
Something like what the paper by Harrel and others "Tutorial in
biostatistics,
multivariate prognostic models: issues in developing models,
evaluating
assumptions and adequacy, and measuring and reducing errors" provides
for regular biostatistical analysis
2. I have this affymetrix hg_u1332a chip data in a 22000 X 62 matrix.
The columns are different patients and I am seeking suggestions on
analysis. My goal is to report on informative genes relative to
disease under study.
Thanks for all the help I can get.
--
A Smile costs Nothing But Rewards Everything
-
Anonymous
Happiness is not perfected until it is shared
-Jane
Porter
[[alternative HTML version deleted]]
On Fri, Mar 27, 2009 at 10:38 AM, Philip Twumasi-Ankrah <
nana_kwadwo_derkyi@yahoo.com> wrote:
> I am new to microarray analysis and need help on two fronts:
>
> 1. Can any one direct me to a resources that provide directions on a
how to
> systematically conduct an analysis of differential expression data.
>
> Something like what the paper by Harrel and others "Tutorial in
> biostatistics,
> multivariate prognostic models: issues in developing models,
evaluating
> assumptions and adequacy, and measuring and reducing errors"
provides for
> regular biostatistical analysis
>
> 2. I have this affymetrix hg_u1332a chip data in a 22000 X 62
matrix. The
> columns are different patients and I am seeking suggestions on
analysis. My
> goal is to report on informative genes relative to disease under
study.
>
Hi, Philip. If you take a look at the Bioconductor website, there are
a
number of resources in the form of books that are not TOO expensive.
Those
are a good place to start. Also, you might notice that each of the
bioconductor packages has at least one "vignette", sort of like a
manual,
that describes how to use the various packages; these are also
fantastic
sources of information. Finally, for differential expression, there
are a
number of packages in bioconductor that can do what you want, but you
might
want to start with the limma package.
And just a comment on what you have so far: a matrix is a poor
representation of microarray data. You might want to look at the affy
and
Biobase packages for the bioconductor approach to dealing with
affymetrix
data.
Sean
[[alternative HTML version deleted]]
There are web several resources, you could download course material
from there.
A microarray analysis for differential gene expression in the soybean
genome using Bioconductor and R
Briefings in Bioinformatics 2007 8 415-431.
Course material from:
http://compdiag.molgen.mpg.de/ngfn/pma2008may.phphttp://faculty.ucr.edu/~tgirke/Documents/R_BioCondManual.html
This will be a good start for you, and there are books.
Hope this helps
Narendra
>>> Sean Davis <seandavi at="" gmail.com=""> 27/03/2009 15:28 >>>
On Fri, Mar 27, 2009 at 10:38 AM, Philip Twumasi-Ankrah <
nana_kwadwo_derkyi at yahoo.com> wrote:
> I am new to microarray analysis and need help on two fronts:
>
> 1. Can any one direct me to a resources that provide directions on a
how to
> systematically conduct an analysis of differential expression data.
>
> Something like what the paper by Harrel and others "Tutorial in
> biostatistics,
> multivariate prognostic models: issues in developing models,
evaluating
> assumptions and adequacy, and measuring and reducing errors"
provides for
> regular biostatistical analysis
>
> 2. I have this affymetrix hg_u1332a chip data in a 22000 X 62
matrix. The
> columns are different patients and I am seeking suggestions on
analysis. My
> goal is to report on informative genes relative to disease under
study.
>
Hi, Philip. If you take a look at the Bioconductor website, there are
a
number of resources in the form of books that are not TOO expensive.
Those
are a good place to start. Also, you might notice that each of the
bioconductor packages has at least one "vignette", sort of like a
manual,
that describes how to use the various packages; these are also
fantastic
sources of information. Finally, for differential expression, there
are a
number of packages in bioconductor that can do what you want, but you
might
want to start with the limma package.
And just a comment on what you have so far: a matrix is a poor
representation of microarray data. You might want to look at the affy
and
Biobase packages for the bioconductor approach to dealing with
affymetrix
data.
Sean
[[alternative HTML version deleted]]
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