Hello,
I have a question about background correction and normalization.
Please help me out! Thank you for your time!
I have four chips of microarray experiments, and therefore four data
sets. I combined them together by merging on ProbeID and read in them
as one file using read.ilmn(), and I combined all the control probe
files into one and read it in. I just followed the limma user guide
and use neqc() for background correction and normalization. Is it good
enough? Do I need to consider within array and between array
normalization?
Thanks,
Xiayu
[[alternative HTML version deleted]]
Dear Xiayu,
Yes, it is good enough. neqc() has done between-array normalization
already, and there is no need for within-array normalization for
Illumina
BeadChips.
Please look at the help page
?neqc
The read stages that you describe sound complicated. read.ilmn()
reads
the files as output by Genome Studio at our core facility without any
need
for intermediate processing.
Best wishes
Gordon
-------------------- original message --------------------
[BioC] read.ilmn() and variation between chips
Rao,Xiayu XRao at mdanderson.org
Wed Jun 26 20:08:09 CEST 2013
Hello,
I have a question about background correction and normalization.
Please
help me out! Thank you for your time!
I have four chips of microarray experiments, and therefore four data
sets.
I combined them together by merging on ProbeID and read in them as one
file using read.ilmn(), and I combined all the control probe files
into
one and read it in. I just followed the limma user guide and use
neqc()
for background correction and normalization. Is it good enough? Do I
need
to consider within array and between array normalization?
Thanks,
Xiayu
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:4}}
Hello, Gordon
Thanks a lot for answering my two questions. The information you
provided was very important to us.
One quick question, you said that read.ilmn() reads the files as
output by Genome Studio without any need for intermediate processing.
What if I have so many samples from several chips, and I read in the
data from each chip using read.ilmn(), and then I want to do
comparisons based on all the samples? How to combine them?
Really appreciate your kind help!
Thanks,
Xiayu
-----Original Message-----
From: Gordon K Smyth [mailto:smyth@wehi.EDU.AU]
Sent: Friday, June 28, 2013 2:37 AM
To: Rao,Xiayu
Cc: Bioconductor mailing list
Subject: read.ilmn() and variation between chips
Dear Xiayu,
Yes, it is good enough. neqc() has done between-array normalization
already, and there is no need for within-array normalization for
Illumina BeadChips.
Please look at the help page
?neqc
The read stages that you describe sound complicated. read.ilmn()
reads the files as output by Genome Studio at our core facility
without any need for intermediate processing.
Best wishes
Gordon
-------------------- original message -------------------- [BioC]
read.ilmn() and variation between chips Rao,Xiayu XRao at
mdanderson.org Wed Jun 26 20:08:09 CEST 2013
Hello,
I have a question about background correction and normalization.
Please help me out! Thank you for your time!
I have four chips of microarray experiments, and therefore four data
sets.
I combined them together by merging on ProbeID and read in them as one
file using read.ilmn(), and I combined all the control probe files
into one and read it in. I just followed the limma user guide and use
neqc() for background correction and normalization. Is it good enough?
Do I need to consider within array and between array normalization?
Thanks,
Xiayu
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:6}}
Dear Xiayu,
Genome Studio normally exports multiple BeadChips to the same probe
summary profile file. Our core centre normally exports all the chips
for
each experiment to the same file. Even if you do have multiple files,
read.ilmn() will read multiple files and collate them for you.
Have you read the documentation?
Best wishes
Gordon
On Fri, 28 Jun 2013, Rao,Xiayu wrote:
> Hello, Gordon
>
> Thanks a lot for answering my two questions. The information you
> provided was very important to us.
>
> One quick question, you said that read.ilmn() reads the files as
output
> by Genome Studio without any need for intermediate processing. What
if I
> have so many samples from several chips, and I read in the data from
> each chip using read.ilmn(), and then I want to do comparisons based
on
> all the samples? How to combine them?
>
> Really appreciate your kind help!
>
> Thanks,
> Xiayu
>
>
>
> -----Original Message-----
> From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
> Sent: Friday, June 28, 2013 2:37 AM
> To: Rao,Xiayu
> Cc: Bioconductor mailing list
> Subject: read.ilmn() and variation between chips
>
> Dear Xiayu,
>
> Yes, it is good enough. neqc() has done between-array normalization
already, and there is no need for within-array normalization for
Illumina BeadChips.
>
> Please look at the help page
>
> ?neqc
>
> The read stages that you describe sound complicated. read.ilmn()
reads the files as output by Genome Studio at our core facility
without any need for intermediate processing.
>
> Best wishes
> Gordon
>
> -------------------- original message -------------------- [BioC]
read.ilmn() and variation between chips Rao,Xiayu XRao at
mdanderson.org Wed Jun 26 20:08:09 CEST 2013
>
> Hello,
>
> I have a question about background correction and normalization.
Please help me out! Thank you for your time!
>
> I have four chips of microarray experiments, and therefore four data
sets.
> I combined them together by merging on ProbeID and read in them as
one file using read.ilmn(), and I combined all the control probe files
into one and read it in. I just followed the limma user guide and use
neqc() for background correction and normalization. Is it good enough?
Do I need to consider within array and between array normalization?
>
> Thanks,
> Xiayu
>
>
______________________________________________________________________
> The information in this email is confidential and
inte...{{dropped:10}}
