[R] help for fine mappting
PIKAL Petr
petr.pikal at precheza.cz
Thu Jun 16 09:16:17 CEST 2016
Hi
From posted ref and map you cannot obtain final file need, they have nothing in common.
answers see in line
> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of greg holly
> Sent: Wednesday, June 15, 2016 5:21 PM
> To: r-help at r-project.org
> Subject: [R] help for fine mappting
>
> dear all;
>
>
> I am sorry for this posting. I have got help from Jim, Bert, Jeff and PIKAL
> on similar issue before. I tried to modify Jim`s code to the real data but
> it did not work. Now I am posting first two rows the imitation of real data
> using dput() format (please see at the bottom). I have two data sets,
> data=map and data=ref. The first to rows of each data set are given below.
> Data map has more than 27 million and data ref has about 560 rows.
> Basically I need run two different tasks. My R codes for these task are
> given below but they do not work properly. I sincerely do appreciate your
> helps.
>
>
>
> Regards,
>
> Greg
>
>
>
> Task 1)
>
> For example, the first and second columns for row 1 in data ref are chr1,
> 6457839 and 6638389. So I need write an R code normally first look the
> first row in ref (which they are chre1 6457839 and 6638389) than summing
> the column of "map$post_prob" and give the number of map$snp falls
> between
> 6457839 and 6638389 that their cumulative sum is >0.85. Then do the same
> for the second, third....in ref. At the end I would like a table gave below
> (need_ouput). Please notice the all value specified info in ref data file
> are exist in map$CHR and map$POS columns.
If I understand correctly you need to get
sel <- map$POS >= ref$POS_start & map$POS < ref$POS_end
result1 <- sum( map$post_prob[sel] )
and then check if the result is >0.85
(but in your final table post_prob is below this threshold)
compute
result2 <- length( map$post_prob[sel] )
and add the results into final table.
>
>
>
> Task2)
>
> Again example, the first and second columns for row 1 in data ref are chr1,
> 6457839 and 6638389. So I need that R gives me the minimum map$p for the
> 2
> chr1, 6457839 and 6638389 (as there are many snps between these regions
> and
> would like choose the smallest one in those regions. Than do the same for
> the second, third....rows in ref.
Your task 2 can be done alongside task1
result3 <- min( map$p[sel] )
>
>
>
> Then put the results of Task1 and Task2 into need_ouput file
Again if I understand correctly your result data frame shall have same number of rows as ref data frame. I wonder how do you want to put there POS, snp, allele... and other multiple values from map data frame? How do you want to summarise them?
Two final comments:
Do not post in HTML, you can see that the code below is rather scrammbled due to behaviour of HTML mail.
If posting some examples, it would be preferable that they can be used directly with code we are trying to find to help you solve your task. Especially if you want quick answer.
Cheers
Petr
>
>
>
>
> #R codes modified from Jim
>
>
> map2<-map[order(map$CHR, map$POS, -map$post_prob),]
>
>
>
> # get a field for the counts
>
> ref$n<-NA
>
>
>
> # and a field for the minimum p values
>
> ref$min_p<-NA
>
>
>
> # get the number of rows in "ref"
>
> nref<-dim(ref)[1]
>
> for(i in 1:nref) {
>
> CHR<- which(map2$CHR==ref$CHR[i])
>
> POS_start<-which(map2$POS==ref$POS_start[i])
>
> POS_end<-which(map2$POS==ref$POS_end[i])
>
> cat("CHR", "CHR"," POS_start",POS_start,"POS_end",POS_end,"\n")
>
>
>
> # get the range of matches
>
> POSrange<-range(c(CHR,POS_start,POS_end))
>
>
>
> # convert this to a sequence spanning all matches
>
> allPOS<-POSrange[1]:POSrange[2]
>
> ref$n[i]<-sum(map2$post_prob[allPOS] > 0.99)
>
> ref$min_p[i]<-min(map2$p[allPOS])
>
> }
>
>
>
>
>
> dput(map)
>
> structure(list(CHR = structure(c(1L, 1L), .Label = "chr1", class =
> "factor"),
>
> snp = structure(1:2, .Label = c("rs4747841", "rs4749917"), class
> = "factor"),
>
> Allel1 = structure(1:2, .Label = c("A", "T"), class = "factor"),
>
> Allel2 = structure(c(2L, 1L), .Label = c("C", "G"), class =
> "factor"),
>
> fr = c(0.551, 0.436), effec = c(-0.0011, 0.0011), SE = c(0.0029,
>
> 0.0029), p = c(0.7, 0.7), POS = c(9960129L, 9960259L), post_prob
> = c(1.248817e-158,
>
> 1.248817e-158)), .Names = c("CHR", "snp", "Allel1", "Allel2",
>
> "fr", "effec", "SE", "p", "POS", "post_prob"), class = "data.frame",
> row.names = c(NA,
>
> -2L))
>
>
>
>
>
> dput(ref)
>
> structure(list(CHR = structure(1:2, .Label = c("chr10", "chr14"
>
> ), class = "factor"), POS_start = c(6457839L, 21005246L), POS_end =
> c(6638389L,
>
> 21550658L)), .Names = c("CHR", "POS_start", "POS_end"), class =
> "data.frame", row.names = c(NA,
>
> -2L))
>
>
>
>
>
> dput(need_output)
>
> structure(list(CHR = structure(1:2, .Label = c("chr1", "chr22"
>
> ), class = "factor"), POS = c(312127953L, 46487552L), POS_start =
> c(32036927L,
>
> 45766451L), POS_end = c(3232240262, 46801601), snp = structure(1:2, .Label
> = c("rs1143427",
>
> "rs55958907"), class = "factor"), alle1l = structure(1:2, .Label = c("G",
>
> "T"), class = "factor"), allel2 = structure(1:2, .Label = c("A",
>
> "G"), class = "factor"), fr = c(0.278, 0.974), effec = c(0.6,
>
> 0.106), SE = c(0.015, 0.027), P = c(0.000156, 7.63e-05), post_prob =
> c(0.229,
>
> 0.125), n = c(612L, 4218L)), .Names = c("CHR", "POS", "POS_start",
>
> "POS_end", "snp", "alle1l", "allel2", "fr", "effec", "SE", "P",
>
> "post_prob", "n"), class = "data.frame", row.names = c(NA, -2L
>
> ))
>
> [[alternative HTML version deleted]]
>
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