affy expression values
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Larry ▴ 10
@larry-57
Last seen 8.1 years ago
This is a multi-part message in MIME format. ------=_NextPart_000_0025_01C236DB.74C991A0 Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Greetings Dr. Irizarry and Dr. Gautier, I have a question regarding the affy procedures that I am hoping you can = help me with. I am in the process of exploring use of affy analysis as = an alternative to using the Affymetrix expression values and in doing so = I am trying to understand the process for generating expression values. = Specifically, the medianpolish default procedure used by the express = function. =20 As I understand it, in calculating expression values for multiple chips, = medianpolish does not treat the chips independently. It runs through = this process of removing row and column medians for all the chips then = generates an overall value for all the chips with corrections for each = chip. The expression value generated is then calculated from these two = values. Does this then mean that I should expect different results = depending on the number of chips I am analyzing?=20 For example, I've run a subset of data through the process, using chips = hybridized with extract from untreated cells and cells exposed to = various treatment. I then analyzed the cells using 2 chips, 3 chips, 4 = chips and 5 chips (ie. untreated + 1-4 treatments), and the results I = obtained were different each time. Below is the values generated for 10 = genes in for the untreated condition only. gene 2 chips 3chips 4chips 5chips=20 untreated 203307_at 8.47863 8.42976 8.213314 8.44459=20 205793_x_at 9.063024 9.022368 8.84279 9.022368=20 209168_at 7.840245 7.743475 7.584038 7.817369=20 210260_s_at 10.42869 10.37537 10.02658 10.42127=20 210373_at 8.373434 8.366322 8.076776 8.366322=20 214692_s_at 8.729106 8.765005 8.457484 8.769177=20 215294_s_at 6.884695 6.95363 6.691277 6.849249=20 216017_s_at 8.90209 8.637539 8.472341 8.830136=20 217431_x_at 7.288174 7.246028 6.960451 7.288174=20 59437_at 7.960958 8.008521 7.547648 7.834895=20 I recognize that the values don't vary greatly, but I am concerned that = having a treatment that causes profound effects to expression of certain = genes may affect my results considerably (with respect to not having = had done that treatment). =20 I hope my question is clear and would very much appreciate your comments = on this. Regards Larry Heisler Dept of Laboratory Medicine and Pathobiology Program in Proteomics and Pathobiology University of Toronto Toronto, Ontario Canada l.heisler@rogers.com ------=_NextPart_000_0025_01C236DB.74C991A0 Content-Type: text/html; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable <html><head> <meta http-equiv="3DContent-Type" content="3D"text/html;" =="" charset="3Diso-8859-1""> <meta content="3D"MSHTML" 6.00.2600.0"="" name="3DGENERATOR"> <style></style> </head> <body bgcolor="3D#ffffff">
<font face="3DArial" size="3D2">Greetings Dr. Irizarry and Dr.=20 Gautier,</font>
<font face="3DArial" size="3D2"></font> 
<font face="3DArial" size="3D2">I have a question regarding the affy = procedures=20 that I am hoping you can help me with.   I am in the process = of=20 exploring use of affy analysis as an alternative to using the Affymetrix = expression values and in doing so I am trying to understand the process = for=20 generating expression values. Specifically, the medianpolish default = procedure=20 used by the express function.  </font>
<font face="3DArial" size="3D2"></font> 
<font face="3DArial" size="3D2">As I understand it, in calculating = expression=20 values for multiple chips,  medianpolish does not treat the chips=20 independently. It runs through this process of removing row and column = medians=20 for all the chips then generates an overall value for all the chips with = corrections for each chip.  The expression value generated is=20 then calculated from these two values.  Does this then mean = that I=20 should expect different results depending on the number of chips I = am=20 analyzing? </font>
<font face="3DArial" size="3D2"></font> 
<font face="3DArial" size="3D2"> For example, I've run a subset of = data=20 through the process, using chips hybridized with extract from untreated = cells=20 and cells exposed to various treatment.  I then analyzed the cells = using 2=20 chips, 3 chips, 4 chips and 5 chips (ie. untreated + 1-4 treatments), = and the=20 results I obtained were different each time.  Below is the values = generated=20 for 10 genes in for the untreated condition only.</font>
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border-bottom:="" #c0c0c0;="" background-color:="" transparent"="20" align="3Dright" x:num="3D"7.2881739681123001""><font face="3DArial=20" size="3D2">7.288174</font> <td=20 style="3D"BORDER-RIGHT:" #c0c0c0;="" border-top:="" #c0c0c0;="" border-left:="#c0c0c0;" border-bottom:="" #c0c0c0;="" height:="" 12.75pt;="" background-color:="transparent"=20" height="3D17"><font face="3DArial" size="3D2"></font> <td=20 style="3D"BORDER-RIGHT:" #c0c0c0;="" border-top:="" #c0c0c0;="" border-left:="#c0c0c0;" border-bottom:="" #c0c0c0;="" background-color:="" transparent"=""><font=20 face="3DArial" size="3D2">59437_at</font> <td=20 style="3D"BORDER-RIGHT:" #c0c0c0;="" border-top:="" #c0c0c0;="" border-left:="#c0c0c0;" border-bottom:="" #c0c0c0;="" background-color:="" transparent"="20" align="3Dright" x:num="3D"7.96095786675121""><font face="3DArial=20" size="3D2">7.960958</font> <td=20 style="3D"BORDER-RIGHT:" #c0c0c0;="" border-top:="" #c0c0c0;="" border-left:="#c0c0c0;" border-bottom:="" #c0c0c0;="" background-color:="" transparent"="20" align="3Dright" x:num="3D"8.0085213058109801""><font face="3DArial=20" size="3D2">8.008521</font> <td=20 style="3D"BORDER-RIGHT:" #c0c0c0;="" border-top:="" #c0c0c0;="" border-left:="#c0c0c0;" border-bottom:="" #c0c0c0;="" background-color:="" transparent"="20" align="3Dright" x:num="3D"7.5476482311749402""><font face="3DArial=20" size="3D2">7.547648</font> <td=20 style="3D"BORDER-RIGHT:" #c0c0c0;="" border-top:="" #c0c0c0;="" border-left:="#c0c0c0;" border-bottom:="" #c0c0c0;="" background-color:="" transparent"="20" align="3Dright" x:num="3D"7.8348951315787199""><font face="3DArial=20" size="3D2">7.834895</font>
<font face="3DArial" size="3D2"></font> 
<font face="3DArial" size="3D2">I recognize that the values don't vary = greatly, but=20 I am concerned that having a treatment that causes profound effects to=20 expression of certain genes may affect my results considerably  = (with=20 respect to not having had done that treatment).  </font>
<font face="3DArial" size="3D2"></font> 
<font face="3DArial" size="3D2"></font> 
<font face="3DArial" size="3D2">I hope my question is clear and would = very much=20 appreciate your comments on this.</font>
<font face="3DArial" size="3D2"></font> 
<font face="3DArial" size="3D2">Regards</font>
<font face="3DArial" size="3D2">Larry Heisler</font>
<font face="3DArial" size="3D2">Dept of Laboratory Medicine and=20 Pathobiology</font>
<font face="3DArial" size="3D2">Program in Proteomics and = Pathobiology</font>
<font face="3DArial" size="3D2">University of Toronto</font>
<font face="3DArial" size="3D2">Toronto, Ontario Canada</font>
<font face="3DArial" size="3D2"><a=20 href="3D"mailto:l.heisler@rogers.com"">l.heisler@rogers.com</font>
<font face="3DArial" size="3D2"></font> 
<font face="3DArial" size="3D2"></font> 
</body></html> ------=_NextPart_000_0025_01C236DB.74C991A0--
Proteomics affy PROcess Proteomics affy PROcess • 869 views
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Entering edit mode
@rafael-a-irizarry-14
Last seen 8.1 years ago
dear larry, I hope laurent's note was helpful, here are some further thoughts. there are two things here: 1) the R package and 2) the expression measure. The expression measures is described in a paper (to appear in biostatistics) that you can download from http://www.biostat.jhsph.edu/~ririzarr/papers/index.html with the R package you can do anything you want. RMA (our meausre) is the default but there are many (infinite) options. if you are concerned about the use of multi-chip analysis you can easily alter the express function in the package as laurent pointed out. you can, for example, use apply(x,2,median) instead of median polish. this will make it chip indenpendent. you can also use normalization procedures that dont depend heavily on multiple chips. scaling for example. some collaborators and myself, are currently writing a manuscript of the advantages of multichip analysis. keep your eyes open for that. rafael On Mon, 29 Jul 2002, Larry wrote: > Greetings Dr. Irizarry and Dr. Gautier, > > I have a question regarding the affy procedures that I am hoping you can help me with. I am in the process of exploring use of affy analysis as an alternative to using the Affymetrix expression values and in doing so I am trying to understand the process for generating expression values. Specifically, the medianpolish default procedure used by the express function. > > As I understand it, in calculating expression values for multiple chips, medianpolish does not treat the chips independently. It runs through this process of removing row and column medians for all the chips then generates an overall value for all the chips with corrections for each chip. The expression value generated is then calculated from these two values. Does this then mean that I should expect different results depending on the number of chips I am analyzing? > > For example, I've run a subset of data through the process, using chips hybridized with extract from untreated cells and cells exposed to various treatment. I then analyzed the cells using 2 chips, 3 chips, 4 chips and 5 chips (ie. untreated + 1-4 treatments), and the results I obtained were different each time. Below is the values generated for 10 genes in for the untreated condition only. > > gene 2 chips 3chips 4chips 5chips > untreated 203307_at 8.47863 8.42976 8.213314 8.44459 > 205793_x_at 9.063024 9.022368 8.84279 9.022368 > 209168_at 7.840245 7.743475 7.584038 7.817369 > 210260_s_at 10.42869 10.37537 10.02658 10.42127 > 210373_at 8.373434 8.366322 8.076776 8.366322 > 214692_s_at 8.729106 8.765005 8.457484 8.769177 > 215294_s_at 6.884695 6.95363 6.691277 6.849249 > 216017_s_at 8.90209 8.637539 8.472341 8.830136 > 217431_x_at 7.288174 7.246028 6.960451 7.288174 > 59437_at 7.960958 8.008521 7.547648 7.834895 > > > I recognize that the values don't vary greatly, but I am concerned that having a treatment that causes profound effects to expression of certain genes may affect my results considerably (with respect to not having had done that treatment). > > > I hope my question is clear and would very much appreciate your comments on this. > > Regards > Larry Heisler > Dept of Laboratory Medicine and Pathobiology > Program in Proteomics and Pathobiology > University of Toronto > Toronto, Ontario Canada > l.heisler@rogers.com > > >
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Laurent Gautier ★ 2.3k
@laurent-gautier-29
Last seen 8.1 years ago
On Mon, Jul 29, 2002 at 08:39:30AM -0400, Larry wrote: > Greetings Dr. Irizarry and Dr. Gautier, ...thanks... but I still cannot claim for the two letters to preceede my name... ;) > > I have a question regarding the affy procedures that I am hoping you can help me with. I am in the process of exploring use of affy analysis as an alternative to using the Affymetrix expression values and in doing so I am trying to understand the process for generating expression values. Specifically, the medianpolish default procedure used by the express function. > > As I understand it, in calculating expression values for multiple chips, medianpolish does not treat the chips independently. It runs through this process of removing row and column medians for all the chips then generates an overall value for all the chips with corrections for each chip. The expression value generated is then calculated from these two values. Does this then mean that I should expect different results depending on the number of chips I am analyzing? > technically, yes. I guess one way to present it is to say that the more repeated measurments you make, the better you can approximate the 'true theoretical' value. I have seen a preprint of Dr. Irizarry's work about the computation of the expression values. He is surely the knowledgeable person to give further details. > For example, I've run a subset of data through the process, using chips hybridized with extract from untreated cells and cells exposed to various treatment. I then analyzed the cells using 2 chips, 3 chips, 4 chips and 5 chips (ie. untreated + 1-4 treatments), and the results I obtained were different each time. Below is the values generated for 10 genes in for the untreated condition only. > > gene 2 chips 3chips 4chips 5chips > untreated 203307_at 8.47863 8.42976 8.213314 8.44459 > 205793_x_at 9.063024 9.022368 8.84279 9.022368 > 209168_at 7.840245 7.743475 7.584038 7.817369 > 210260_s_at 10.42869 10.37537 10.02658 10.42127 > 210373_at 8.373434 8.366322 8.076776 8.366322 > 214692_s_at 8.729106 8.765005 8.457484 8.769177 > 215294_s_at 6.884695 6.95363 6.691277 6.849249 > 216017_s_at 8.90209 8.637539 8.472341 8.830136 > 217431_x_at 7.288174 7.246028 6.960451 7.288174 > 59437_at 7.960958 8.008521 7.547648 7.834895 > > > I recognize that the values don't vary greatly, but I am concerned that having a treatment that causes profound effects to expression of certain genes may affect my results considerably (with respect to not having had done that treatment). > Testing whether two groups of values vary can be considered different or not is addressed by specific tests. The t-test has been for example widely used with microarrays data. Alternatives can be found (the R-package 'permax' offers such an alternative). (note: In the case of Affymetrix arrays, for each gene several short probes (oligonucleotides) are found on the array. The values you present above are 'summary' values for all the probes values. You may want to look at the probe level the reason the differences (see the affy.pdf vignette). I have seen cases where an odd difference in the expression level of experiments is caused by artefacts (some of them being visible on the image of the chip (the package has function to let you observe the physical location of probes related to a particular gene (try 'demo(affy.tour)'). > > I hope my question is clear and would very much appreciate your comments on this. > I hope this could help a bit.... Regards, Laurent > Regards > Larry Heisler > Dept of Laboratory Medicine and Pathobiology > Program in Proteomics and Pathobiology > University of Toronto > Toronto, Ontario Canada > l.heisler@rogers.com > > -- -------------------------------------------------------------- Laurent Gautier CBS, Building 208, DTU PhD. Student DK-2800 Lyngby,Denmark tel: +45 45 25 24 89 http://www.cbs.dtu.dk/laurent
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