Hi Hana,
I didn't look closely. The simplest rule that I can see is that the
letters (nucleotides?) should be swapped if there has been a sign
change in the beta value. Therefore:
mydf<-read.table(text=
"IDnumber OA EA beta
1 C A -0.05
2 GA0.098
3 GT
Imagine that it's the year 2022 and you don't know how to look up
information about performing a Kruskal-Wallis H test.
It would take you longer to join the listserv and then write such a
cokamemie email than to open the stats textbook you are supposed to have
for the course, much less doing
Dear jim thanks for your help! I want to change also the value of OA and EF
simultaneously.For instance i am looking the datamydf IDnumber OA EA beta1
1 A C 0.0502 2 G A 0.0983 3 T G 0.789Best, Hana
Original message From: Jim Lemon
Hi Hana,
I think this is what you want:
# first read in your example
mydf<-read.table(text=
"IDnumber OA EA beta
1 C A -0.05
2 GA0.098
3 GT-0.789",
header=TRUE,stringsAsFactors=FALSE)
# check it
mydf
IDnumber OA EA beta
11 C A -0.05
This is a plain text list. Your html post got mangled (see below). You
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Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-
I have the following data set in data frameIDnumber OA EA beta1
C A -0.052 G A
0.0983 G T -0.789I want to change
the sign of negative beta. If the negative value change to post
Homework!
On 2022-06-11 10:24, Shantanu Shimpi wrote:
Dear R community,
Please help me in knowing how to do following non-parametric tests:
1. kruskal-Wallis test
2. Wilcoxson rank sum test
3. Lee Cronbac Alpha test
4. Spearman's Rank correlation test
5. Henry Garrett
Looks like the center effect improves overall accuracy while being
independent of the other terms.
A few things to try
Compare coef(model.fix) to fixef(model.rand).
Add center as a fixed effect to model .fix
Try a conditional logit (clogit from survival)
See how consistent the coefficients are
Dear R users,
I'm analyzing a particular score "y" among several individuals, each of which
belongs to a center, a factor with three
different levels (3 possible centers). I have treated the "center" as a fixed
effect, and as a random term (package lme4):
1) model.fix <- glm(y ~ var.1 + var.2
Hello,
The code below is a hack.
First I create a layout ll, then see that vertex K coordinates are in
the layout matrix 2nd row.
Now, to multiply K's coordinates by a number d>1 will move the point
away from A. Add that value to the K group and plot.
ll <- layout_with_kk(my.graph)
d <- ll
Hi, Dear Respected Professors! I hope that you are doing well. Now all
files are in .txt files. Now kindly help me with the following:
I have the R-codes for the "Quantile Augmented Mean Group" method. The
relevant codes and data are attached herewith.
Note: The link to the reference paper is:
htt
Hi,
I was trying to make a network plot of this data:
library(igraph)
library(network)
df1 <- data.frame(from="A",to=c("B","C","D","E","F","G"),value=1)
df2 <- data.frame(from="K",to=c("L","M","N"),value=1)
df3 <- data.frame(from="A",to="K",value=3)
my.df <- rbind(df1,df2,df3)
my.g
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