Hi Dr. Franggakis;
This can be explained because of collinearity and suppressor variable in
multiple regression models. In the first scenario, you have both correlated
variables and suppressor variables in the second scenario you do not have this
problem. I do wonder why to do not use the scale
uot;posB" ]
sB$pos
A[ i, "posA" ] <= sB$pos
sB$pos <= A[ i, "posB" ]
A[ i, "posA" ] <= sB$pos & sB$pos <= A[ i, "posB" ]
idx <- A[ i, "posA" ] <= sB$pos & sB$pos <= A[ i, "posB" ]
sB[ idx, "a" ]
a
data frame I get an error.
So please try to keep above mentioned when posting a query.
Regards
Petr
> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of oslo via R-
> help
> Sent: Friday, June 10, 2016 11:09 PM
> To: oslo ; Jeff Newmiller ;
Jeff;
thanks for this. My question was job related. No from my course. I need finish
a job for the place I work. I am so sorry for causing misunderstanding.
thanks,
Oslo
On Friday, June 10, 2016 5:08 PM, oslo via R-help
wrote:
Jeff thanks for this. My question was job related. No
PM PDT, oslo via R-help wrote:
Dear All;
I had difficulty to post a mail along with appropriate of data structure. I do
sincerely apologize for multiple posting
I would like to sum up the B$a column and cut off at 0.7 for the each row of
intervals giving in file=A.For example the interval at
Dear All;
I had difficulty to post a mail along with appropriate of data structure. I do
sincerely apologize for multiple posting
I would like to sum up the B$a column and cut off at 0.7 for the each row of
intervals giving in file=A.For example the interval at the first row in A$posA
and A$p
1.2]
[1] 0.36751828 0.08721951 0.08899027 0.38838635
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 Fri, Jun 10, 2016 at 12:27 PM,
I am so sorry that the data in my previous file was very mass;Here are my data
sets
> A posA posB1 1 92 2 73 5 124 4 75 9 13>
pos a b c1 4 0.4 7 0.802 2 0.1 5 0.403 7 0.5 8 0.324 1 0.4
1 0.105 13 0.1 6 0.136 12 0.2 11 0.017 9 0.3 12 0.23>
H
Hi all;
I am quite new in R. I have tried write a loop to sum up a column and cut off
when summation reach certain point. Here are a small example and my R codes.
Your helps are truly appreciated,
Oslo
file=AposA posB1 92 75 124 79 13. . . .
File=Bpos a b c 4
quot;,
"rs12307687", "rs12307687", "rs10071837", "rs10071837", "rs10071837",
"rs925098", "rs925098", "rs925098")), .Names = c("rs", "n0",
"Pvalue", "V1"), row.names = c(NA, -15L), class
Hi all;
I have a big data set (a small part is given below) and V1 column has repeated
info in it. That is rs941873, rs12307687... are repeating many times. I need
choose only one SNP (in first column named rs) which has the smallest Pvalue
withing V1 column. That is I need choose only one SNP
Hi all;
I have a big data set (a small part is given below) and V1 column has repeated
info in it. That is rs941873, rs12307687... are repeating many times. I need
choose only one SNP (in first column named rs) which has the smallest Pvalue
withing V1 column. That is I need choose only one SNP
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