Re: [base] Dealing wiht duplicate spots

[Nantel Andre]

On 2011-11-21, at 2:13 PM, Nicklas Nordborg wrote:

 The demo data set is a GenePix data set and for each spot the file 
 contains the coordinates, reporter id and a lot of measured intensities 
 and other values. So if your data is similar to this, then I think you 
 don't need any special new importer. Use the generic Raw data flat file 
 importer and make sure to map spot coordinates, reporter id and 
 intensity columns that are in your data files.
 
 Maybe you can post a few lines from the files you are working with so I 
 don't have to guess...

Here is our data format. We never got the generic importer working even after 
updating the raw-data-types.xml file to our version of the Imagene files. When 
we try to use that, we get a no plug-in error. 

Begin Header
version 9.0.
DateTue Nov 15 13:49:21 EST 2011
Image File  C:\Documents and Settings\All Users\Documents\Andre\29 
Avr\14261085_cy3.tif
Page0
Page Name   
Invertedfalse
Image File  C:\Documents and Settings\All Users\Documents\Andre\29 
Avr\14261085_cy5.tif
Page0
Page Name   
Invertedfalse
Begin Field Dimensions
Field   MetarowsMetacolsRowsCols
A   12  4   16  18
End Field Dimensions
Begin Measurement parameters
Segmentation Method auto
Signal Low  0.0
Signal High 0.0
Background Low  0.0
Background High 0.0
Background Buffer   2.0
Background Width5.0
End Measurement parameters
End Header
Begin Normalization
Background measure  Bckgr. Mean
Correction method   Local
Sliding window  false
Take logtrue
Log baseBase 2
Normalization type  Lowess
Scope   SubGrid
Smoothing   0.2
Using control spots Use all spots
End Normalization
Begin Raw Data
Field   MR  MC  Row Col.GeneID  Annotation 1Flag
N. Signal Mean, ch1 N. Signal Mean, ch2 N. Signal Median, ch1   N. 
Signal Median, ch2   N. Signal Mode, ch1 N. Signal Mode, ch2
A   1   1   1   1   orf19.5337  0   
10.0631 10.2463 9.9099  9.9951  9.9646  9.9756
A   1   1   1   2   orf19.5337  0   
9.1418  9.3703  9.1036  9.1544  9.2753  9.5736
A   1   1   1   3   orf19.5642  0   
13.5228 13.3390 13.4454 13.2718 13.5748 13.3829
A   1   1   1   4   orf19.5642  0   
12.3849 12.4358 12.3075 12.4157 12.3422 12.4249
A   1   1   1   5   orf19.3173  0   
11.9102 11.9314 11.8002 11.8241 11.8276 11.8270


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Re: [base] Dealing wiht duplicate spots

[Nantel Andre]

On 2011-11-21, at 2:51 PM, Nicklas Nordborg wrote:

 On 2011-11-21 20:31, Nantel Andre wrote:
 On 2011-11-21, at 2:13 PM, Nicklas Nordborg wrote:
 
 The demo data set is a GenePix data set and for each spot the file
 contains the coordinates, reporter id and a lot of measured intensities
 and other values. So if your data is similar to this, then I think you
 don't need any special new importer. Use the generic Raw data flat file
 importer and make sure to map spot coordinates, reporter id and
 intensity columns that are in your data files.
 
 Maybe you can post a few lines from the files you are working with so I
 don't have to guess...
 
 Here is our data format. We never got the generic importer working even
 after updating the raw-data-types.xml file to our version of the Imagene
 files. When we try to use that, we get a no plug-in error.
 
 This is usually due to lack of permission for the logged in user. Make 
 sure that the file format configuration has been shared properly.
 
 The file seems to be equivalent to and contain information that is very 
 similar to GenePix files. I don't see any reason why the generic raw 
 data importer shouldn't work in this case.
 
 

We don't have any regular users yet since we are still figuring out how it 
works. I am doing everything from my administrator account.

Anyway that's all the time I can give to this problem until later this week. 
This whole process has been much much more difficult than we expected. Please 
don't take this the wrong way but it might be a problem for your team as well 
if you ever hope to expand on your user base. It's not like we're new at this, 
we've been using microarrays since 1999 but I was getting tired of sending 
thousands of dollars to Agilent every year.

Thanks,
--
All the data continuously generated in your IT infrastructure 
contains a definitive record of customers, application performance, 
security threats, fraudulent activity, and more. Splunk takes this 
data and makes sense of it. IT sense. And common sense.
http://p.sf.net/sfu/splunk-novd2d
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