Manhattan plot for CNVs association results
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Yadav Sapkota ▴ 130
@yadav-sapkota-5156
Last seen 9.6 years ago
Hello, I am trying to generate a Manhattan plot using the association results from CNVs. Following is the example data: Regions P value =-LOG10(P value) chr1:100132667-100143425 0.2238316 0.650078601 chr1:100274010-100276481 0.2766402 0.55808471 chr1:100295062-100304021 0.3608504 0.442672809 chr1:100763109-100777987 0.8155034 0.088574224 chr1:100797078-100799030 1 0 chr1:100910270-100930160 1 0 chr1:100943609-100975280 0.4864253 0.312983845 I would appreciate if anyone knows any package or script for this. Regards, Yadav [[alternative HTML version deleted]]
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Tengfei Yin ▴ 420
@tengfei-yin-4323
Last seen 8.0 years ago
Hi Yadav, if you are going to use *ggbio* package, it require GRanges as input for your Manhattan plot, you need to *rearrange* your results into a GRanges object, generally you have to parse chromosome names and region from your original data and use GRanges constructor for saving them as a GRanges object. like library(GenomicRanges) gr.snp <- GRanges(chrs, IRanges(start = your_start_pos, end = your_end_pos), pvalue = your_pvalue)) ## where chrs are your chromosome vectors, and your_start_pos, your_end_pos defines your region, you put your p-value, as your extra elementMetadata column. ## then library(ggbio) plotGrandLinear(gr.snp, y = pvalue, geom = "point") + theme_bw() you can check example ?plotGrandLinear FYI: this is going to be a separate transformation stage in the very near future, it is undergoing some change,so if you came across any issues, you could file a issue at https://github.com/tengfei/ggbio/issues, or email me back. This week I am renewing the website, I will put a example for Manhattan plot as one of the case studies on the website. Will sent you an email later. HTH Tengfei On Tue, Apr 3, 2012 at 12:45 PM, Yadav Sapkota <ysapkota@ualberta.ca> wrote: > Hello, > > I am trying to generate a Manhattan plot using the association results from > CNVs. Following is the example data: > > Regions P value =-LOG10(P value) chr1:100132667-100143425 0.2238316 > 0.650078601 chr1:100274010-100276481 0.2766402 0.55808471 > chr1:100295062-100304021 0.3608504 0.442672809 chr1:100763109-100777987 > 0.8155034 0.088574224 chr1:100797078-100799030 1 0 > chr1:100910270-100930160 1 0 chr1:100943609-100975280 0.4864253 > 0.312983845 > > I would appreciate if anyone knows any package or script for this. > > > Regards, > Yadav > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Tengfei Yin MCDB PhD student 1620 Howe Hall, 2274, Iowa State University Ames, IA,50011-2274 Homepage: www.tengfei.name [[alternative HTML version deleted]]
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Hi Tengfei, Thanks for the info. It worked so far using the following code: source("http://bioconductor.org/biocLite.R") biocLite("GenomicRanges") library(GenomicRanges) mydata=read.table('C:/......Book1.csv', header=T, sep=',') attach(mydata) gr.cnv=GRanges(Chr, IRanges(Start, Stop), pvalue=mydata$P1) source("http://bioconductor.org/biocLite.R") biocLite("ggbio") library(ggbio) plotGrandLinear(gr.cnv, y=pvalue, geom='point', color.type='twocolor', two.color=c('red', 'blue'), xlab='Chromosomes', ylab=substitute('-log10 p-value'))+theme_bw() - In the generated plot, I have some chromosomes overlapping, due to which its hard to see these. I know the reason as there are too little signatures to plot. Is there any way that I can manipulate the code so that I will have a 'FIXED' size for all the chromosomes? This would avoid the overlapping the chromosomes despite the number of signatures to plot. - Another thing, chromosomes in the plot appear like 1, 10, 11.......2, 20, 21, 3, 4, 5....X. I tried to sort using 'order' function but I think this does not work in GRanges objects. How do I order these chromosomes like 1, 2,3,4,5,6,7,8,9,10,.....X? Your advice would be much appreciated. Regards, Yadav On Tue, Apr 3, 2012 at 12:18 PM, Tengfei Yin <yintengfei@gmail.com> wrote: > Hi Yadav, > > if you are going to use *ggbio* package, it require GRanges as input for > your Manhattan plot, you need to *rearrange* your results into a GRanges > object, generally you have to parse chromosome names and region from your > original data and use GRanges constructor for saving them as a GRanges > object. like > > library(GenomicRanges) > gr.snp <- GRanges(chrs, > IRanges(start = your_start_pos, end = your_end_pos), > pvalue = your_pvalue)) > > ## where chrs are your chromosome vectors, and your_start_pos, > your_end_pos defines your region, you put your p-value, as your extra > elementMetadata column. > > ## then > library(ggbio) > plotGrandLinear(gr.snp, y = pvalue, geom = "point") + theme_bw() > > you can check example ?plotGrandLinear > > FYI: this is going to be a separate transformation stage in the very near > future, it is undergoing some change,so if you came across any issues, you > could file a issue at https://github.com/tengfei/ggbio/issues, or email > me back. > This week I am renewing the website, I will put a example for Manhattan > plot as one of the case studies on the website. Will sent you an email > later. > > HTH > > Tengfei > > > > > > On Tue, Apr 3, 2012 at 12:45 PM, Yadav Sapkota <ysapkota@ualberta.ca>wrote: > >> Hello, >> >> I am trying to generate a Manhattan plot using the association results >> from >> CNVs. Following is the example data: >> >> Regions P value =-LOG10(P value) chr1:100132667-100143425 0.2238316 >> 0.650078601 chr1:100274010-100276481 0.2766402 0.55808471 >> chr1:100295062-100304021 0.3608504 0.442672809 chr1:100763109-100777987 >> 0.8155034 0.088574224 chr1:100797078-100799030 1 0 >> chr1:100910270-100930160 1 0 chr1:100943609-100975280 0.4864253 >> 0.312983845 >> >> I would appreciate if anyone knows any package or script for this. >> >> >> Regards, >> Yadav >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > > > -- > Tengfei Yin > MCDB PhD student > 1620 Howe Hall, 2274, > Iowa State University > Ames, IA,50011-2274 > Homepage: www.tengfei.name > > [[alternative HTML version deleted]]
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On Tue, Apr 3, 2012 at 2:50 PM, Yadav Sapkota <ysapkota@ualberta.ca> wrote: > Hi Tengfei, > > Thanks for the info. It worked so far using the following code: > > source("http://bioconductor.org/biocLite.R") > biocLite("GenomicRanges") > library(GenomicRanges) > mydata=read.table('C:/......Book1.csv', header=T, sep=',') > attach(mydata) > gr.cnv=GRanges(Chr, IRanges(Start, Stop), pvalue=mydata$P1) > source("http://bioconductor.org/biocLite.R") > biocLite("ggbio") > library(ggbio) > plotGrandLinear(gr.cnv, y=pvalue, geom='point', color.type='twocolor', > two.color=c('red', 'blue'), xlab='Chromosomes', ylab=substitute('-log10 > p-value'))+theme_bw() > > Hi Yadav, Thanks for your nice feedback. > > - In the generated plot, I have some chromosomes overlapping, due to > which its hard to see these. I know the reason as there are too little > signatures to plot. Is there any way that I can manipulate the code so that > I will have a 'FIXED' size for all the chromosomes? This would avoid the > overlapping the chromosomes despite the number of signatures to plot. > > That's exactly what I am doing now, when I mention it's under going some change, it's not in plotGrandLinear function yet(some lower level function have that features), the strategy will be 1. it first parse seqlengths with you could set on your GRanges object with fixed width. 2. if you don't have seqlengths defined, it will use data space. 3. allow you add buffer in between > - Another thing, chromosomes in the plot appear like 1, 10, > 11.......2, 20, 21, 3, 4, 5....X. I tried to sort using 'order' function > but I think this does not work in GRanges objects. How do I order these > chromosomes like 1, 2,3,4,5,6,7,8,9,10,.....X? > > I leave that to users, your should re-order your seqname and remove your unused seqlevels for your gr.cnv, please check ?keepSeqlevels and ?renameSeqlevels in package GenomicRanges. Let's keep in touch, I will update a case study on-line and plotGrandLinear function in these two days, and will let you know then you can test with your data. cheers Tengfei > > > Your advice would be much appreciated. > > Regards, > Yadav > > > > > On Tue, Apr 3, 2012 at 12:18 PM, Tengfei Yin <yintengfei@gmail.com> wrote: > >> Hi Yadav, >> >> if you are going to use *ggbio* package, it require GRanges as input for >> your Manhattan plot, you need to *rearrange* your results into a GRanges >> object, generally you have to parse chromosome names and region from your >> original data and use GRanges constructor for saving them as a GRanges >> object. like >> >> library(GenomicRanges) >> gr.snp <- GRanges(chrs, >> IRanges(start = your_start_pos, end = your_end_pos), >> pvalue = your_pvalue)) >> >> ## where chrs are your chromosome vectors, and your_start_pos, >> your_end_pos defines your region, you put your p-value, as your extra >> elementMetadata column. >> >> ## then >> library(ggbio) >> plotGrandLinear(gr.snp, y = pvalue, geom = "point") + theme_bw() >> >> you can check example ?plotGrandLinear >> >> FYI: this is going to be a separate transformation stage in the very near >> future, it is undergoing some change,so if you came across any issues, you >> could file a issue at https://github.com/tengfei/ggbio/issues, or email >> me back. >> This week I am renewing the website, I will put a example for Manhattan >> plot as one of the case studies on the website. Will sent you an email >> later. >> >> HTH >> >> Tengfei >> >> >> >> >> >> On Tue, Apr 3, 2012 at 12:45 PM, Yadav Sapkota <ysapkota@ualberta.ca>wrote: >> >>> Hello, >>> >>> I am trying to generate a Manhattan plot using the association results >>> from >>> CNVs. Following is the example data: >>> >>> Regions P value =-LOG10(P value) chr1:100132667-100143425 0.2238316 >>> 0.650078601 chr1:100274010-100276481 0.2766402 0.55808471 >>> chr1:100295062-100304021 0.3608504 0.442672809 chr1:100763109-100777987 >>> 0.8155034 0.088574224 chr1:100797078-100799030 1 0 >>> chr1:100910270-100930160 1 0 chr1:100943609-100975280 0.4864253 >>> 0.312983845 >>> >>> I would appreciate if anyone knows any package or script for this. >>> >>> >>> Regards, >>> Yadav >>> >>> [[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor@r-project.org >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >> >> >> >> -- >> Tengfei Yin >> MCDB PhD student >> 1620 Howe Hall, 2274, >> Iowa State University >> Ames, IA,50011-2274 >> Homepage: www.tengfei.name >> >> > -- Tengfei Yin MCDB PhD student 1620 Howe Hall, 2274, Iowa State University Ames, IA,50011-2274 Homepage: www.tengfei.name [[alternative HTML version deleted]]
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Sure....will wait for your e-mail... --Yadav On Tue, Apr 3, 2012 at 2:06 PM, Tengfei Yin <yintengfei@gmail.com> wrote: > > > On Tue, Apr 3, 2012 at 2:50 PM, Yadav Sapkota <ysapkota@ualberta.ca>wrote: > >> Hi Tengfei, >> >> Thanks for the info. It worked so far using the following code: >> >> source("http://bioconductor.org/biocLite.R") >> biocLite("GenomicRanges") >> library(GenomicRanges) >> mydata=read.table('C:/......Book1.csv', header=T, sep=',') >> attach(mydata) >> gr.cnv=GRanges(Chr, IRanges(Start, Stop), pvalue=mydata$P1) >> source("http://bioconductor.org/biocLite.R") >> biocLite("ggbio") >> library(ggbio) >> plotGrandLinear(gr.cnv, y=pvalue, geom='point', color.type='twocolor', >> two.color=c('red', 'blue'), xlab='Chromosomes', ylab=substitute('-log10 >> p-value'))+theme_bw() >> >> Hi Yadav, > > Thanks for your nice feedback. > >> >> - In the generated plot, I have some chromosomes overlapping, due to >> which its hard to see these. I know the reason as there are too little >> signatures to plot. Is there any way that I can manipulate the code so that >> I will have a 'FIXED' size for all the chromosomes? This would avoid the >> overlapping the chromosomes despite the number of signatures to plot. >> >> That's exactly what I am doing now, when I mention it's under going some > change, it's not in plotGrandLinear function yet(some lower level function > have that features), the strategy will be > 1. it first parse seqlengths with you could set on your GRanges object > with fixed width. > 2. if you don't have seqlengths defined, it will use data space. > 3. allow you add buffer in between > > >> - Another thing, chromosomes in the plot appear like 1, 10, >> 11.......2, 20, 21, 3, 4, 5....X. I tried to sort using 'order' function >> but I think this does not work in GRanges objects. How do I order these >> chromosomes like 1, 2,3,4,5,6,7,8,9,10,.....X? >> >> > I leave that to users, your should re-order your seqname and remove your > unused seqlevels for your gr.cnv, > please check ?keepSeqlevels and ?renameSeqlevels in package GenomicRanges. > > Let's keep in touch, I will update a case study on-line > and plotGrandLinear function in these two days, and will let you know then > you can test with your data. > > cheers > > Tengfei > > >> >> >> Your advice would be much appreciated. >> >> Regards, >> Yadav >> >> >> >> >> On Tue, Apr 3, 2012 at 12:18 PM, Tengfei Yin <yintengfei@gmail.com>wrote: >> >>> Hi Yadav, >>> >>> if you are going to use *ggbio* package, it require GRanges as input >>> for your Manhattan plot, you need to *rearrange* your results into a >>> GRanges object, generally you have to parse chromosome names and region >>> from your original data and use GRanges constructor for saving them as a >>> GRanges object. like >>> >>> library(GenomicRanges) >>> gr.snp <- GRanges(chrs, >>> IRanges(start = your_start_pos, end = your_end_pos), >>> pvalue = your_pvalue)) >>> >>> ## where chrs are your chromosome vectors, and your_start_pos, >>> your_end_pos defines your region, you put your p-value, as your extra >>> elementMetadata column. >>> >>> ## then >>> library(ggbio) >>> plotGrandLinear(gr.snp, y = pvalue, geom = "point") + theme_bw() >>> >>> you can check example ?plotGrandLinear >>> >>> FYI: this is going to be a separate transformation stage in the very >>> near future, it is undergoing some change,so if you came across any issues, >>> you could file a issue at https://github.com/tengfei/ggbio/issues, or >>> email me back. >>> This week I am renewing the website, I will put a example for Manhattan >>> plot as one of the case studies on the website. Will sent you an email >>> later. >>> >>> HTH >>> >>> Tengfei >>> >>> >>> >>> >>> >>> On Tue, Apr 3, 2012 at 12:45 PM, Yadav Sapkota <ysapkota@ualberta.ca>wrote: >>> >>>> Hello, >>>> >>>> I am trying to generate a Manhattan plot using the association results >>>> from >>>> CNVs. Following is the example data: >>>> >>>> Regions P value =-LOG10(P value) chr1:100132667-100143425 0.2238316 >>>> 0.650078601 chr1:100274010-100276481 0.2766402 0.55808471 >>>> chr1:100295062-100304021 0.3608504 0.442672809 chr1:100763109-100777987 >>>> 0.8155034 0.088574224 chr1:100797078-100799030 1 0 >>>> chr1:100910270-100930160 1 0 chr1:100943609-100975280 0.4864253 >>>> 0.312983845 >>>> >>>> I would appreciate if anyone knows any package or script for this. >>>> >>>> >>>> Regards, >>>> Yadav >>>> >>>> [[alternative HTML version deleted]] >>>> >>>> _______________________________________________ >>>> Bioconductor mailing list >>>> Bioconductor@r-project.org >>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>> Search the archives: >>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>>> >>> >>> >>> >>> -- >>> Tengfei Yin >>> MCDB PhD student >>> 1620 Howe Hall, 2274, >>> Iowa State University >>> Ames, IA,50011-2274 >>> Homepage: www.tengfei.name >>> >>> >> > > > -- > Tengfei Yin > MCDB PhD student > 1620 Howe Hall, 2274, > Iowa State University > Ames, IA,50011-2274 > Homepage: www.tengfei.name > > > -- Yadav Sapkota PhD Candidate Dept. of Laboratory Medicine and Pathology, UofA Cross Cancer Institute 11560 University Avenue, Edmonton AB T6G 1Z2 Phone: 780-5778092 [[alternative HTML version deleted]]
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On Tue, Apr 3, 2012 at 4:50 PM, Yadav Sapkota <ysapkota@ualberta.ca> wrote: > Sure....will wait for your e-mail... Hi Yadav, ...so sorry that I guess I forget to reply this email, please update ggbio in R 2.15, then you should be able to tweak the order and space and lengths by using keepSeqleves, seqlengths for GRanges control chromosome space, and space.skip argument in plotGrandLinear control buffer between chromosomes. http://tengfei.github.com/ggbio/blog/2012/04/12/Manhattan/ notice, I haven't update this page yet, ".ori.seqnames" used in this page is now just "seqnames" Please report issues at https://github.com/tengfei/ggbio/issues Thanks Tengfei Tengfei > > --Yadav > > > On Tue, Apr 3, 2012 at 2:06 PM, Tengfei Yin <yintengfei@gmail.com> wrote: > >> >> >> On Tue, Apr 3, 2012 at 2:50 PM, Yadav Sapkota <ysapkota@ualberta.ca>wrote: >> >>> Hi Tengfei, >>> >>> Thanks for the info. It worked so far using the following code: >>> >>> source("http://bioconductor.org/biocLite.R") >>> biocLite("GenomicRanges") >>> library(GenomicRanges) >>> mydata=read.table('C:/......Book1.csv', header=T, sep=',') >>> attach(mydata) >>> gr.cnv=GRanges(Chr, IRanges(Start, Stop), pvalue=mydata$P1) >>> source("http://bioconductor.org/biocLite.R") >>> biocLite("ggbio") >>> library(ggbio) >>> plotGrandLinear(gr.cnv, y=pvalue, geom='point', color.type='twocolor', >>> two.color=c('red', 'blue'), xlab='Chromosomes', ylab=substitute('-log10 >>> p-value'))+theme_bw() >>> >>> Hi Yadav, >> >> Thanks for your nice feedback. >> >>> >>> - In the generated plot, I have some chromosomes overlapping, due to >>> which its hard to see these. I know the reason as there are too little >>> signatures to plot. Is there any way that I can manipulate the code so that >>> I will have a 'FIXED' size for all the chromosomes? This would avoid the >>> overlapping the chromosomes despite the number of signatures to plot. >>> >>> That's exactly what I am doing now, when I mention it's under going some >> change, it's not in plotGrandLinear function yet(some lower level function >> have that features), the strategy will be >> 1. it first parse seqlengths with you could set on your GRanges object >> with fixed width. >> 2. if you don't have seqlengths defined, it will use data space. >> 3. allow you add buffer in between >> >> >>> - Another thing, chromosomes in the plot appear like 1, 10, >>> 11.......2, 20, 21, 3, 4, 5....X. I tried to sort using 'order' function >>> but I think this does not work in GRanges objects. How do I order these >>> chromosomes like 1, 2,3,4,5,6,7,8,9,10,.....X? >>> >>> >> I leave that to users, your should re-order your seqname and remove your >> unused seqlevels for your gr.cnv, >> please check ?keepSeqlevels and ?renameSeqlevels in package GenomicRanges. >> >> Let's keep in touch, I will update a case study on-line >> and plotGrandLinear function in these two days, and will let you know then >> you can test with your data. >> >> cheers >> >> Tengfei >> >> >>> >>> >>> Your advice would be much appreciated. >>> >>> Regards, >>> Yadav >>> >>> >>> >>> >>> On Tue, Apr 3, 2012 at 12:18 PM, Tengfei Yin <yintengfei@gmail.com>wrote: >>> >>>> Hi Yadav, >>>> >>>> if you are going to use *ggbio* package, it require GRanges as input >>>> for your Manhattan plot, you need to *rearrange* your results into a >>>> GRanges object, generally you have to parse chromosome names and region >>>> from your original data and use GRanges constructor for saving them as a >>>> GRanges object. like >>>> >>>> library(GenomicRanges) >>>> gr.snp <- GRanges(chrs, >>>> IRanges(start = your_start_pos, end = your_end_pos), >>>> pvalue = your_pvalue)) >>>> >>>> ## where chrs are your chromosome vectors, and your_start_pos, >>>> your_end_pos defines your region, you put your p-value, as your extra >>>> elementMetadata column. >>>> >>>> ## then >>>> library(ggbio) >>>> plotGrandLinear(gr.snp, y = pvalue, geom = "point") + theme_bw() >>>> >>>> you can check example ?plotGrandLinear >>>> >>>> FYI: this is going to be a separate transformation stage in the very >>>> near future, it is undergoing some change,so if you came across any issues, >>>> you could file a issue at https://github.com/tengfei/ggbio/issues, or >>>> email me back. >>>> This week I am renewing the website, I will put a example for Manhattan >>>> plot as one of the case studies on the website. Will sent you an email >>>> later. >>>> >>>> HTH >>>> >>>> Tengfei >>>> >>>> >>>> >>>> >>>> >>>> On Tue, Apr 3, 2012 at 12:45 PM, Yadav Sapkota <ysapkota@ualberta.ca>wrote: >>>> >>>>> Hello, >>>>> >>>>> I am trying to generate a Manhattan plot using the association results >>>>> from >>>>> CNVs. Following is the example data: >>>>> >>>>> Regions P value =-LOG10(P value) chr1:100132667-100143425 0.2238316 >>>>> 0.650078601 chr1:100274010-100276481 0.2766402 0.55808471 >>>>> chr1:100295062-100304021 0.3608504 0.442672809 >>>>> chr1:100763109-100777987 >>>>> 0.8155034 0.088574224 chr1:100797078-100799030 1 0 >>>>> chr1:100910270-100930160 1 0 chr1:100943609-100975280 0.4864253 >>>>> 0.312983845 >>>>> >>>>> I would appreciate if anyone knows any package or script for this. >>>>> >>>>> >>>>> Regards, >>>>> Yadav >>>>> >>>>> [[alternative HTML version deleted]] >>>>> >>>>> _______________________________________________ >>>>> Bioconductor mailing list >>>>> Bioconductor@r-project.org >>>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>>> Search the archives: >>>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>>>> >>>> >>>> >>>> >>>> -- >>>> Tengfei Yin >>>> MCDB PhD student >>>> 1620 Howe Hall, 2274, >>>> Iowa State University >>>> Ames, IA,50011-2274 >>>> Homepage: www.tengfei.name >>>> >>>> >>> >> >> >> -- >> Tengfei Yin >> MCDB PhD student >> 1620 Howe Hall, 2274, >> Iowa State University >> Ames, IA,50011-2274 >> Homepage: www.tengfei.name >> >> >> > > > -- > Yadav Sapkota > PhD Candidate > Dept. of Laboratory Medicine and Pathology, UofA > Cross Cancer Institute > 11560 University Avenue, Edmonton AB T6G 1Z2 > Phone: 780-5778092 > > > -- Tengfei Yin MCDB PhD student 1620 Howe Hall, 2274, Iowa State University Ames, IA,50011-2274 Homepage: www.tengfei.name [[alternative HTML version deleted]]
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