Dear bioconductors,
I just installed the lumiHumanV1 package via the biocLite() procedure
yesterday. The identifiers of the single probes look very strange to
me.
Beside that they don't appear in the annotation file provided by
Illumina
the name composition itself made me, let me say somehow suspicious!
Here
comes a quick extract. Did someone observe that before?
> xx <- as.list(lumiHumanV1ACCNUM)
> xx[1:5]
$x00WAIBIVaMvS3EVQ0
[1] NA
$`9iFKOnl5SKK4SnkAS8`
[1] "NM_032360"
$Ke_INOf6KSdNz6Qeek
[1] "NM_030945"
$rKBxx.U0SoWkRRVxac
[1] "NM_025258"
$ilenrd0XnE.4v_3Zec
[1] NA
> sessionInfo()
R version 2.5.0 (2007-04-23)
i386-pc-mingw32
locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252
attached base packages:
[1] "tools" "stats" "graphics" "grDevices" "utils"
"datasets"
[7] "methods" "base"
other attached packages:
lumiHumanV1 lumi annotate mgcv affy
affyio
"1.2.0" "1.2.0" "1.14.1" "1.3-23" "1.14.0"
"1.4.0"
Biobase
"1.14.0"
Cheers,
Benjamin
======================================
Benjamin Otto
University Hospital Hamburg-Eppendorf
Institute For Clinical Chemistry
Martinistr. 52
D-20246 Hamburg
Tel.: +49 40 42803 1908
Fax.: +49 40 42803 4971
======================================
--
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Gerichtsstand: Hamburg
Vorstandsmitglieder:
Prof. Dr. J?rg F. Debatin (Vorsitzender)
Dr. Alexander Kirstein
Ricarda Klein
Prof. Dr. Dr. Uwe Koch-Gromus
Benjamin Otto wrote:
> Dear bioconductors,
>
> I just installed the lumiHumanV1 package via the biocLite()
procedure
> yesterday. The identifiers of the single probes look very strange to
me.
> Beside that they don't appear in the annotation file provided by
Illumina
> the name composition itself made me, let me say somehow suspicious!
Here
> comes a quick extract. Did someone observe that before?
>
>
>> xx <- as.list(lumiHumanV1ACCNUM)
>> xx[1:5]
>>
> $x00WAIBIVaMvS3EVQ0
> [1] NA
>
> $`9iFKOnl5SKK4SnkAS8`
> [1] "NM_032360"
>
> $Ke_INOf6KSdNz6Qeek
> [1] "NM_030945"
>
> $rKBxx.U0SoWkRRVxac
> [1] "NM_025258"
>
> $ilenrd0XnE.4v_3Zec
> [1] NA
>
>
>> sessionInfo()
>>
> R version 2.5.0 (2007-04-23)
> i386-pc-mingw32
>
> locale:
> LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
> States.1252;LC_MONETARY=English_United
> States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252
>
> attached base packages:
> [1] "tools" "stats" "graphics" "grDevices" "utils"
"datasets"
> [7] "methods" "base"
>
> other attached packages:
> lumiHumanV1 lumi annotate mgcv affy
affyio
> "1.2.0" "1.2.0" "1.14.1" "1.3-23" "1.14.0"
"1.4.0"
> Biobase
> "1.14.0"
>
These IDs are nuIDs. They are used by the lumi package and are a
base-64 encoded version of the actual sequence of the probe. You may
find that the "illumina...." data packages, rather than the "lumi...."
data packages have the standard keys. However, if you are using the
lumi package for dealing with Illumina data, the "lumi...." data
packages will work just fine. Perhaps Pan Du or Simon Lin will fill
in
some more details about why they use nuID.
Sean
Hi Benjamin
There are potential problems of directly using Illumina Target
identifier or
probe identifier because of its imperfect design. For example, there
are
duplicated Target IDs in the same chip. The same probe can have
different
Target IDs. The nuID is designed to solve these problems. It can be
directly
convert to the probe sequence and get the latest annotation easily.
Also,
the annotation packages like lumiHumanV1 provides the mapping between
TargetID to nuID and probe Id to nuID.
Please check the vignette of lumi package and the paper published in
Biology
Direct 2007, 2:16:
nuID: a universal naming scheme of oligonucleotides for Illumina,
Affymetrix, and other microarrays
Tell me if you have any questions.
Pan
On 7/6/07 5:00 AM, "bioconductor-request at stat.math.ethz.ch"
<bioconductor-request at="" stat.math.ethz.ch=""> wrote:
> ------------------------------
>
> Message: 2
> Date: Thu, 5 Jul 2007 13:00:14 +0200
> From: "Benjamin Otto" <b.otto at="" uke.uni-hamburg.de="">
> Subject: [BioC] Manufacturer ids in lumiHumanV1
> To: "BioClist" <bioconductor at="" stat.math.ethz.ch="">
> Message-ID: <000901c7bef3$ac604870$9f05a20a at matrix.com>
> Content-Type: text/plain; charset="us-ascii"
>
> Dear bioconductors,
>
> I just installed the lumiHumanV1 package via the biocLite()
procedure
> yesterday. The identifiers of the single probes look very strange to
me.
> Beside that they don't appear in the annotation file provided by
Illumina
> the name composition itself made me, let me say somehow suspicious!
Here
> comes a quick extract. Did someone observe that before?
Hi everyone,
My question is of statistical nature.
I am trying to finalize the analysis of real-time PCR experiments.
I have 4 technical replicates (pipeting errors) and three biological
replicates (repeat treatment).
I use gapdh as an external reference gene.
1) Can I average all replication regardless of technical/biological?
2) Similarily can I use the standard error from the combined standard
deviations and what would the population size be in that case? (would
it be
4 technical x 3 biological?)
If I can not do the above how does someone proceed with these two
different
types of replication?
I can imagine that the technical replication reflects only on the
threshold
cycles and the biological replication at the actual fold
difference[2^-(threshold cycle)] but how can I combine the two
differently
calculated standard errors?
I apologize that the e-mail is not directly linking to some BioC
package but
there are no packages for real-time and I had nowhere else to turn!
Thanks
Niki
Swann Building
The King's Buildings
University of Edinburgh
Edinburgh, EH9 3JR
Scotland
UK
tel:(0044)0131-6507072
fax:(0044)0131-6505379
R.Athanasiadou at sms.ed.ac.uk
-----Original Message-----
From: bioconductor-bounces@stat.math.ethz.ch
[mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Pan Du
Sent: 06 July 2007 15:46
To: bioconductor at stat.math.ethz.ch
Cc: Simon Lin
Subject: Re: [BioC] Manufacturer ids in lumiHumanV1
Hi Benjamin
There are potential problems of directly using Illumina Target
identifier or
probe identifier because of its imperfect design. For example, there
are
duplicated Target IDs in the same chip. The same probe can have
different
Target IDs. The nuID is designed to solve these problems. It can be
directly
convert to the probe sequence and get the latest annotation easily.
Also,
the annotation packages like lumiHumanV1 provides the mapping between
TargetID to nuID and probe Id to nuID.
Please check the vignette of lumi package and the paper published in
Biology
Direct 2007, 2:16:
nuID: a universal naming scheme of oligonucleotides for Illumina,
Affymetrix, and other microarrays
Tell me if you have any questions.
Pan
On 7/6/07 5:00 AM, "bioconductor-request at stat.math.ethz.ch"
<bioconductor-request at="" stat.math.ethz.ch=""> wrote:
> ------------------------------
>
> Message: 2
> Date: Thu, 5 Jul 2007 13:00:14 +0200
> From: "Benjamin Otto" <b.otto at="" uke.uni-hamburg.de="">
> Subject: [BioC] Manufacturer ids in lumiHumanV1
> To: "BioClist" <bioconductor at="" stat.math.ethz.ch="">
> Message-ID: <000901c7bef3$ac604870$9f05a20a at matrix.com>
> Content-Type: text/plain; charset="us-ascii"
>
> Dear bioconductors,
>
> I just installed the lumiHumanV1 package via the biocLite()
procedure
> yesterday. The identifiers of the single probes look very strange to
me.
> Beside that they don't appear in the annotation file provided by
Illumina
> the name composition itself made me, let me say somehow suspicious!
Here
> comes a quick extract. Did someone observe that before?
_______________________________________________
Bioconductor mailing list
Bioconductor at stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/bioconductor
Search the archives:
http://news.gmane.org/gmane.science.biology.informatics.conductor
Hello Niki,
You should not treat biological and technical replicates in the same
way. The standard deviations provided by the termocycler software only
pertain to the within sample (purely technical) variability. Moreover,
to infer upon treatment effects in a broad inference context you
should
refer to the sample-to-sample variability (so-called biological
variability). For this last purpose you have 4 reps (not 12).
You can use a hierarchical model to account for different levels of
replication. This can be done using a linear mixed model including
both
the test and control gene and computing the (corrected) contrasts of
interest.
Please follow the link to a short paper with a linear model (model
[3])
that we have proposed for this type of analysis. We did not use R for
the computations, but perhaps the lme4 package could be used.
http://www.wcgalp8.org.br/wcgalp8/articles/paper/23_528-1915.pdf
Best,
Juan Pedro
r.athanasiadou wrote:
> Hi everyone,
> My question is of statistical nature.
> I am trying to finalize the analysis of real-time PCR experiments.
> I have 4 technical replicates (pipeting errors) and three biological
> replicates (repeat treatment).
>
> I use gapdh as an external reference gene.
>
> 1) Can I average all replication regardless of technical/biological?
> 2) Similarily can I use the standard error from the combined
standard
> deviations and what would the population size be in that case?
(would it be
> 4 technical x 3 biological?)
>
> If I can not do the above how does someone proceed with these two
different
> types of replication?
>
>
> I can imagine that the technical replication reflects only on the
threshold
> cycles and the biological replication at the actual fold
> difference[2^-(threshold cycle)] but how can I combine the two
differently
> calculated standard errors?
>
>
>
> I apologize that the e-mail is not directly linking to some BioC
package but
> there are no packages for real-time and I had nowhere else to turn!
>
> Thanks
> Niki
>
>
>
>
> Swann Building
> The King's Buildings
> University of Edinburgh
> Edinburgh, EH9 3JR
> Scotland
> UK
>
> tel:(0044)0131-6507072
> fax:(0044)0131-6505379
> R.Athanasiadou at sms.ed.ac.uk
>
>
>
--
=============================
Juan Pedro Steibel
Postdoctoral researcher
Statistical Genetics
Department of Animal Science
Michigan State University
1205-I Anthony Hall
East Lansing, MI
48823 USA
Phone: 1-517-353-5102
E-mail: steibelj at msu.edu
Erratum: you have 3 true reps.
Sorry about that...
JP
Juan Pedro Steibel wrote:
> Hello Niki,
> You should not treat biological and technical replicates in the same
> way. The standard deviations provided by the termocycler software
only
> pertain to the within sample (purely technical) variability.
Moreover,
> to infer upon treatment effects in a broad inference context you
should
> refer to the sample-to-sample variability (so-called biological
> variability). For this last purpose you have 4 reps (not 12).
>
> You can use a hierarchical model to account for different levels of
> replication. This can be done using a linear mixed model including
both
> the test and control gene and computing the (corrected) contrasts of
> interest.
>
> Please follow the link to a short paper with a linear model (model
[3])
> that we have proposed for this type of analysis. We did not use R
for
> the computations, but perhaps the lme4 package could be used.
>
> http://www.wcgalp8.org.br/wcgalp8/articles/paper/23_528-1915.pdf
>
> Best,
> Juan Pedro
>
>
>
>
>
> r.athanasiadou wrote:
>
>> Hi everyone,
>> My question is of statistical nature.
>> I am trying to finalize the analysis of real-time PCR experiments.
>> I have 4 technical replicates (pipeting errors) and three
biological
>> replicates (repeat treatment).
>>
>> I use gapdh as an external reference gene.
>>
>> 1) Can I average all replication regardless of
technical/biological?
>> 2) Similarily can I use the standard error from the combined
standard
>> deviations and what would the population size be in that case?
(would it be
>> 4 technical x 3 biological?)
>>
>> If I can not do the above how does someone proceed with these two
different
>> types of replication?
>>
>>
>> I can imagine that the technical replication reflects only on the
threshold
>> cycles and the biological replication at the actual fold
>> difference[2^-(threshold cycle)] but how can I combine the two
differently
>> calculated standard errors?
>>
>>
>>
>> I apologize that the e-mail is not directly linking to some BioC
package but
>> there are no packages for real-time and I had nowhere else to turn!
>>
>> Thanks
>> Niki
>>
>>
>>
>>
>> Swann Building
>> The King's Buildings
>> University of Edinburgh
>> Edinburgh, EH9 3JR
>> Scotland
>> UK
>>
>> tel:(0044)0131-6507072
>> fax:(0044)0131-6505379
>> R.Athanasiadou at sms.ed.ac.uk
>>
>>
>>
>>
>
>
--
=============================
Juan Pedro Steibel
Postdoctoral researcher
Statistical Genetics
Department of Animal Science
Michigan State University
1205-I Anthony Hall
East Lansing, MI
48823 USA
Phone: 1-517-353-5102
E-mail: steibelj at msu.edu
