two difficult loop

0.85. For example consider there are 38 rows between 29220   in  63933 in sorted

Hi Bert;

I do appreciate for this. I need check your codes on task2 tomorrow at my
office on the real data as I have difficulty (because a technical issue) to
remote connection. I am sure it will work well.

I am sorry that I was not able to explain my first question. Basically

Values in ref data represent the region of chromosome. I need choose these
regions in map (all regions values in ref data are exist in map data in the
first column -column map$reg). And then summing up the column "map$rate and
count the numbers that gives >0.85. For example, consider  the first row in
data ref. They are 29220   and  63933. After sorting the first column in
map then summing column "map$rate" only between 29220   to  63933 in
sorted map and cut off at >0.85. Then count how many rows in sorted map
gives >0.85. For example consider there are 38 rows between 29220   in
 63933 in sorted map$reg and only summing first 12 of them  gives>0.85.
Then my answer is going to be 12 for 29220   -  63933 in ref.

Thanks I lot for your patience.

Cheers,
Greg

On Sun, Jun 12, 2016 at 6:36 PM, Bert Gunter <bgunter.4567 at gmail.com>
wrote:

Greg:

I was not able to understand your task 1. Perhaps others can.

My understanding of your task 2 is that for each row of ref, you wish
to find all rows,of map such that the reg values in those rows fall
between the reg1 and reg2 values in ref (inclusive change <= to < if
you don't want the endpoints), and then you want the minimum map$p
values of all those rows. If that is correct, I believe this will do
it (but caution, untested, as you failed to provide data in a
convenient form, e.g. using dput() )

task2 <- with(map,vapply(seq_len(nrow(ref)),function(i)
min(p[ref[i,1]<=reg & reg <= ref[i,2] ]),0))


If my understanding is incorrect, please ignore both the above and the
following:


The "solution" I have given above seems inefficient, so others may be
able to significantly improve it if you find that it takes too long.
OTOH, my understanding of your specification is that you need to
search for all rows in map data frame that meet the criterion for each
row of ref, and without further information, I don't know how to do
this without just repeating the search 560 times.


Cheers,
Bert


Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Sun, Jun 12, 2016 at 1:14 PM, greg holly <mak.hholly at gmail.com> wrote:

Dear all;



I have two data sets, data=map and data=ref). A small part 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 task. 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

29220

63933. So I need write an R code normally first look the first row in

ref

(which they are 29220 and 63933) than summing the column of "map$rate"

and

give the number of rows that >0.85. Then do the same for the second,
third....in ref. At the end I would like a table gave below (the

results I

need). Please notice the all value specified in ref data file are exist

in

map$reg column.



Task2)

Again example, the first and second columns for row 1 in data ref are

29220

63933. So I need write an R code give the minimum map$p for the 29220
-63933 intervals in map file. Than

do the same for the second, third....in ref.




#my attempt for the first question

temp<-map[order(map$reg, map$p),]

count<-1

temp<-unique(temp$reg

for(i in 1:length(ref) {

  for(j in 1:length(ref)

  {

temp1<-if (temp[pos[i]==ref[ref$reg1,] & (temp[pos[j]==ref[ref$reg2,]
& temp[cumsum(temp$rate)

0.70,])

count=count+1

    }

}

#my attempt for the second question



temp<-map[order(map$reg, map$p),]

count<-1

temp<-unique(temp$reg

for(i in 1:length(ref) {

  for(j in 1:length(ref)

  {

temp2<-if (temp[pos[i]==ref[ref$reg1,] & (temp[pos[j]==ref[ref$reg2,])

output<-temp2[temp2$p==min(temp2$p),]

    }

}



Data sets


  Data= map

  reg   p      rate

 10276 0.700  3.867e-18

 71608 0.830  4.542e-16

 29220 0.430  1.948e-15

 99542 0.220  1.084e-15

 26441 0.880  9.675e-14

 95082 0.090  7.349e-13

 36169 0.480  9.715e-13

 55572 0.500  9.071e-12

 65255 0.300  1.688e-11

 51960 0.970  1.163e-10

 55652 0.388  3.750e-10

 63933 0.250  9.128e-10

 35170 0.720  7.355e-09

 06491 0.370  1.634e-08

 85508 0.470  1.057e-07

 86666 0.580  7.862e-07

 04758 0.810  9.501e-07

 06169 0.440  1.104e-06

 63933 0.750  2.624e-06

 41838 0.960  8.119e-06


 data=ref

  reg1         reg2

  29220     63933

  26441     41838

  06169     10276

  74806     92643

  73732     82451

  86042     93502

  85508     95082



       the results I need

     reg1      reg2 n

   29220   63933  12

   26441   41838   78

   06169 10276  125

   74806 92643   11

   73732 82451   47

   86042 93502   98

   85508 95082  219

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