Seth Falcon | 1 May 01:08 2010

Re: segfault with rmaMicroRna in AgiMicroRna package

Heyi,

A couple of suggestions to help you get help more quickly.

1. Try upgrading your R and Bioconductor packages to the latest release 
and see if that resolves the problem for you.

2. If you still see the crash, since you are running on Linux you should 
be able to extract some further debugging information that will be 
useful to the package maintainer.  Do as follows:

    bash$ R -d gdb
    (gdb) run
       R> # run your example to get the crash
    (gdb) bt 15

Send the output of the backtrace to help identify where things are going 
astray.

+ seth

On 4/30/10 3:48 PM, heyi xiao wrote:
>
>
>
>
> Dear Pedro,
>
> I am using AgiMicroRna 1.0.0 to process my agilent miRNA
> microarray data. Agilent Feature Extraction Software v10.7 was
(Continue reading)

mauede | 1 May 07:11 2010
Picon

Validated miRNAs revisited

I apologize for asking again the same question I asked some months ago.
The reason is that  a question has been raised recently by people I work with.
The question stemmed from the double meaning of the word "validated" with reference to miRNAs.
Some time ago I downloaded the Fasta files "mature.fa" and "matureStart.fa" (the latter cannot be
found any more).  
I meant to get miRNAs that have been experimentally validated against (binding to) some gene targets.
I  used the dat set "hsTargets" avaiilable with Bioconductor to find the matching miRNA-terget pairs.

The question arisen is: "are the nmiRNAs I got just predicted by some code (miRanda or the like) or have they
been experimentally validated" ?

I would appreciate your comments.

Thank you in advance
Maura

tutti i telefonini TIM!

	[[alternative HTML version deleted]]

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michael watson (IAH-C | 1 May 11:29 2010
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Picon

Re: Validated miRNAs revisited

Tarbase and miRecords are the only databases of validated targets I know of. MirWalk has a validated
section but I think it comes from text mining.
________________________________________
From: bioconductor-bounces@...
[bioconductor-bounces@...] On Behalf Of
mauede@... [mauede@...]
Sent: 01 May 2010 06:11
To: Bioconductor  List
Subject: [BioC] Validated miRNAs revisited

I apologize for asking again the same question I asked some months ago.
The reason is that  a question has been raised recently by people I work with.
The question stemmed from the double meaning of the word "validated" with reference to miRNAs.
Some time ago I downloaded the Fasta files "mature.fa" and "matureStart.fa" (the latter cannot be
found any more).
I meant to get miRNAs that have been experimentally validated against (binding to) some gene targets.
I  used the dat set "hsTargets" avaiilable with Bioconductor to find the matching miRNA-terget pairs.

The question arisen is: "are the nmiRNAs I got just predicted by some code (miRanda or the like) or have they
been experimentally validated" ?

I would appreciate your comments.

Thank you in advance
Maura

tutti i telefonini TIM!

        [[alternative HTML version deleted]]

(Continue reading)

Andreia Fonseca | 1 May 21:53 2010
Picon

Re: htqPCR question

Dear Heidi,

So I have each of my biological replicate in a plate, I have used the
following command to read the data:

> raw <- readCtData(files=files$File, path=path, n.features = 96, flag = 4,
feature = 1, type = 2, position = 3, Ct = 5, header = FALSE, SDS = FALSE)
 my files:

 File Treatment
1   Emb1.txt    Embrio
2   Emb2.txt    Embrio
3   Emb3.txt    Embrio
4  lin1a.txt        BM
5   lin2.txt        BM
6 lin_1a.txt        BM
7  lin1b.txt        BM
8   Sca3.txt     Heart

I did the filtering
 raw.cat<-setCategory(raw, groups=files$Treatment, quantile=0.8)

and now I want to normalize:

 d.norm<-normalizeCtData(raw.cat,norm="deltaCt", deltaCt.genes=c("U6"))
 and then I get the message:

Calculating deltaCt values
        Using control gene(s): U6
        Card 1: Mean=33.62      Stdev=NA
(Continue reading)

Michael Imbeault | 2 May 01:34 2010
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BioC 2.6 - changelog for individual packages?

Hi everyone,

Is there a way to get a changelog of what changed between bioC 2.5 and 
2.6 for individual packages? New functions, bugs fixed, etc? The 
associated documentation of packages I looked at don't seem to include this.

Cheers,
Michael

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Benilton Carvalho | 2 May 03:09 2010
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Re: BioC 2.6 - changelog for individual packages?

news() is the tool for that... and emailing the maintainer is the
backup approach, in case a NEWS file is not present in the package. b

On Sun, May 2, 2010 at 12:34 AM, Michael Imbeault
<michael.imbeault@...> wrote:
> Hi everyone,
>
> Is there a way to get a changelog of what changed between bioC 2.5 and 2.6
> for individual packages? New functions, bugs fixed, etc? The associated
> documentation of packages I looked at don't seem to include this.
>
> Cheers,
> Michael
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor@...
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>

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Heidi Dvinge | 2 May 10:26 2010
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Re: HTqPCR (plotCtOverview) problem

>
> On Apr 30, 2010, at 3:08 PM, Heidi Dvinge wrote:
>
>>>
>>> On Apr 30, 2010, at 2:42 PM, Heidi Dvinge wrote:
>>>
>>>> Hello Mike,
>>>>
>>>>> Greetings
>>>>>
>>>>> I have R 2.11, BioC 2.6 and HTqPCR 1.2 (see session info at the
>>>>> end).
>>>>>
>>>>> I created a qPCRset object by using rbind() to concatenate four
>>>>> pairs
>>>>> of dissimilar cards for each experimental condition and then
>>>>> cbind()
>>>>> to concatenate the four objects into one:
>>>>>
>>>>> WT_time1.a |
>>>>> WT_time1.b |---> WT_time1
>>>>> MT_time1.a |
>>>>> MT_time1.b |---> MT_time1
>>>>> WT_time2.a |                           ---> s2010004660
>>>>> WT_time2.b |---> WT_time2
>>>>> MT_time2.a |
>>>>> MT_time2.b |---> MT_time2
>>>>>
>>>>> I set g <- c("MammU6") which is a endogenous control gene.
>>>>>
(Continue reading)

Heidi Dvinge | 2 May 10:34 2010
Picon
Picon

Re: htqPCR question

Hi Andreia,

> Dear Heidi,
>
> So I have each of my biological replicate in a plate, I have used the
> following command to read the data:
>
>> raw <- readCtData(files=files$File, path=path, n.features = 96, flag =
>> 4,
> feature = 1, type = 2, position = 3, Ct = 5, header = FALSE, SDS = FALSE)
>  my files:
>
>  File Treatment
> 1   Emb1.txt    Embrio
> 2   Emb2.txt    Embrio
> 3   Emb3.txt    Embrio
> 4  lin1a.txt        BM
> 5   lin2.txt        BM
> 6 lin_1a.txt        BM
> 7  lin1b.txt        BM
> 8   Sca3.txt     Heart
>
> I did the filtering
>  raw.cat<-setCategory(raw, groups=files$Treatment, quantile=0.8)
>
> and now I want to normalize:
>
>  d.norm<-normalizeCtData(raw.cat,norm="deltaCt", deltaCt.genes=c("U6"))
>  and then I get the message:
>
(Continue reading)

Andreia Fonseca | 2 May 21:22 2010
Picon

Re: htqPCR question

Hi Heidi,
thanks for your response. I only have one qPCR per probe in each plate, so I
have only one copy of U6 in each plate. I have only technical replicates for
one sample, lin1a.txt, lin_1a.txt and lin1b.txt, but each technical
replicate was analyzed in a different plate. So to use the quantile
normalization or the rank invariant methods, do I have to, add an option
saying to do normalization between samples, or I just have to follow the
vignette? Another question, do these methods make the normalization between
samples of the same treatment?
Thanks once again.
With kind regards,
Andreia

On Sun, May 2, 2010 at 9:34 AM, Heidi Dvinge <heidi@...> wrote:

> Hi Andreia,
>
> > Dear Heidi,
> >
> > So I have each of my biological replicate in a plate, I have used the
> > following command to read the data:
> >
> >> raw <- readCtData(files=files$File, path=path, n.features = 96, flag =
> >> 4,
> > feature = 1, type = 2, position = 3, Ct = 5, header = FALSE, SDS = FALSE)
> >  my files:
> >
> >  File Treatment
> > 1   Emb1.txt    Embrio
> > 2   Emb2.txt    Embrio
(Continue reading)

Laurent Gautier | 2 May 22:10 2010
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Picon

package pair "hugene10stv1cdf"/"hugene10stprobeset.db"

Dear List,

I am noting potential issues in the package pair  
"hugene10stv1cdf"/"hugene10stprobeset.db", as the respective sets of 
probe set IDs are not overlapping:

 > library(hugene10stv1cdf)
 > library(hugene10stprobeset.db)
 > summary(ls(hugene10stv1cdf) %in% Lkeys(hugene10stprobesetSYMBOL))
    Mode   FALSE    TRUE    NA's
logical   28026    4295       0
 > summary(Lkeys(hugene10stprobesetSYMBOL) %in% ls(hugene10stv1cdf))
    Mode   FALSE    TRUE    NA's
logical  252727    4295       0

Reading closely, one can observe that "hugene10stprobeset.db" refers to 
a "revision 5" while the "v1" in "hugene10stv1cdf" suggests a revision 
1. It is unclear to me whether this is linked to the problem, but if so 
then there is no hugene10stv5cdf, neither annotation for v1.

The obligatory sessionInfo() is:

 > sessionInfo()
R version 2.11.0 Patched (2010-04-24 r51813)
i686-pc-linux-gnu

locale:
  [1] LC_CTYPE=en_GB.utf8       LC_NUMERIC=C
  [3] LC_TIME=en_GB.utf8        LC_COLLATE=en_GB.utf8
  [5] LC_MONETARY=C             LC_MESSAGES=en_GB.utf8
(Continue reading)


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