[BioC] RE: Bioconductor Digest, Vol 13, Issue 27

Victor M Trevino-Alvarado VMT359 at bham.ac.uk
Mon Mar 15 12:59:32 MET 2004


Yes, I have the distance matrices computed.

	-----Original Message----- 
	From: bioconductor-bounces at stat.math.ethz.ch on behalf of bioconductor-request at stat.math.ethz.ch 
	Sent: Mon 15/03/2004 11:26 
	To: bioconductor at stat.math.ethz.ch 
	Cc: 
	Subject: Bioconductor Digest, Vol 13, Issue 27
	
	

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	Today's Topics:
	
	   1. questions about Affy package from new user (Lizhe Xu)
	   2. questions about Affy package from new user: one more question
	      (Lizhe Xu)
	   3. MOE430 A and B (peter robinson)
	
	
	----------------------------------------------------------------------
	
	Message: 1
	Date: Sun, 14 Mar 2004 17:00:58 -0600
	From: "Lizhe Xu" <lxu at chnola-research.org>
	Subject: [BioC] questions about Affy package from new user
	To: <bioconductor at stat.math.ethz.ch>
	Message-ID:
	        <A7040F7FA2D8AA40B897DE7B16FC97B34ACB32 at chre-exchange.chre.com>
	Content-Type: text/plain; charset="utf-8"
	
	I started to use Bioconductor recently and had several questions about the Affy package. Please help me and even answer to one question will be appreciated. I know some question may take la ong paragraph to answer.
	(1) is it possible to do the summary first followed by normalization on probe set level with Affy?
	(2) what is the advantage to do normailization first, then probe set summary compared to normalization at probe set level?
	(3) After running bgcorrect, normalization and summary on probe set in Affy (expresso function), I want to export the probe set data and analyze it with GS (is there another package can do the same job as GS in bioconductor)? Should I do the per chip normalization again in GS?
	Thanks.
	
	Lizhe
	
	        -----Original Message-----
	        From: bioconductor-request at stat.math.ethz.ch [mailto:bioconductor-request at stat.math.ethz.ch]
	        Sent: Sun 3/14/2004 5:04 AM
	        To: bioconductor at stat.math.ethz.ch
	        Cc:
	        Subject: Bioconductor Digest, Vol 13, Issue 26
	       
	       
	
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	        Today's Topics:
	       
	           1. LC-MS data (Nicholas Lewin-Koh)
	       
	       
	        ----------------------------------------------------------------------
	       
	        Message: 1
	        Date: Sat, 13 Mar 2004 22:48:50 +0800
	        From: "Nicholas Lewin-Koh" <nikko at hailmail.net>
	        Subject: [BioC] LC-MS data
	        To: bioconductor at stat.math.ethz.ch, S.Nyangoma at cs.rug.nl
	        Message-ID: <1079189330.2264.182616685 at webmail.messagingengine.com>
	        Content-Type: text/plain; charset="ISO-8859-1"
	       
	        Hi,
	        To my knowledge there are only 2 packages in R specifically for MS data,
	        mscalib on CRAN, and PROcess in bioconductor devel. The first is for
	        MALDI tof spectrometers and assumes you have picked peaks already and
	        works on the peaks list. The second is for seldi, but the baseline
	        correction and peak picking are pretty generic. To process LC-MS data you
	        have to decide how far back in the device internal processing you want to
	        go. Personally, I have found that the mantra for mass spec data at the
	        moment is "Don't trust vendor software". It mostly sucks. If you can get
	        it you want to be grabbing the data stream as it is read of the column by
	        the sensor, because it helps to warp the chromatagram from each scan so
	        that the peaks align properly. Then you want to conver to m/z. After that
	        comes all the signal processing song and dance, to subtract the chemical
	        noise, make a baseline adjustment, etc. The tools for this in R are here
	        and there and development for processing this stuff is nacent. There is
	        much more available in matlab, which though much more expensive is mostly
	        faster than R. The signal processing community and the chemometrics
	        people tend to work in matlab.
	       
	       
	        Note that it has been my experience that automated peak detection is an
	        art, with more pitfalls than clustering. If you can do anything to avoid
	        that using prior knowledge it helps. Good luck.
	       
	        Nicholas
	        >
	        > Message: 2
	        > Date: 12 Mar 2004 19:12:32 +0100
	        > From: Stephen Nyangoma <S.Nyangoma at cs.rug.nl>
	        > Subject: [BioC] LC-MS proteomics data
	        > To: bioconductor at stat.math.ethz.ch
	        > Message-ID: <1079115152.10700.12.camel at iwi142>
	        > Content-Type: text/plain
	        >
	        > Sorry for bothering you with this question.
	        >
	        > Has someone analylsed LC-MS data? How do you read this data into R? Are
	        > there preprocessing tools in R? What are the crusial preprocessing
	        > steps? Do the ascii files obtained from Brucker software contain raw
	        > files? Thanks. Stephen.
	        >
	        >
	        >
	        >
	        >
	       
	       
	       
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	Message: 2
	Date: Sun, 14 Mar 2004 17:20:14 -0600
	From: "Lizhe Xu" <lxu at chnola-research.org>
	Subject: [BioC] questions about Affy package from new user: one more
	        question
	To: <bioconductor at stat.math.ethz.ch>
	Message-ID:
	        <A7040F7FA2D8AA40B897DE7B16FC97B34ACB34 at chre-exchange.chre.com>
	Content-Type: text/plain;       charset="UTF-8"
	
	Now, I tried to load the exported data from Bioconductor to GeneSpring and found another question. Since I used U133 chip set, I wonder if I can joint the U133A and B directly and import them to GS or I should do probeset level normalization first (if so, which package in bioconductor can do it) before joint them. Thanks.
	
	Lxu
	
	
	
	------------------------------
	
	Message: 3
	Date: Mon, 15 Mar 2004 13:20:25 +0100
	From: Peter.Robinson at t-online.de (peter robinson)
	Subject: [BioC] MOE430 A and B
	To: bioconductor at stat.math.ethz.ch
	Message-ID: <200403151320.25817.peter.robinson at t-online.de>
	Content-Type: text/plain;  charset="us-ascii"
	
	Dear List members,
	
	I would like to use the affy package to analyze data from MOE430A and -B
	chips. I tried to read in data from both types of chips at once using
	data <- ReadAffy(widget=T)
	and then reading in 3 MOE430A and 3 MOE430B CEL files.
	I got the error message:
	"Cel file does not seem to beo of 430MOEA type" when the script tried to input
	data from a 430MOEB Cel file. I had imported the CDF and annotation packages
	for both types of chip.
	I am using R 1.81, Bioconductor 1.3 on a SuSe 8.1 linux system.
	
	Thanks for any advice/tips!
	
	Peter
	
	
	
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