There is a user-group for PLINK, easily found by looking at the page you
cited. This is not the correct place to submit such questions.
https://groups.google.com/g/plink2-users?pli=1
--
David.
On 9/14/20 6:29 AM, Ana Marija wrote:
Hello,
I was running association analysis using --glm geno
I'm wondering if you want one of these:
(1) Plots of "Main Effects".
(2) "Partial Residual Plots".
Search for them, and you should be able to tell if they're what you want.
But a word of warning:
Many people (including many senior statisticians) misinterpret this
kind of information.
Because, it
Generally speaking, statistical questions like this are O/T here. This list
is mostly about R programming issues. While there is a non-null
intersection, I would nevertheless suggest that you post on
stats.stackexchange.com instead.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind
Hi everyone.
I'd like to perform RIDIT scoring of a column that consists of ordinal
values, but I don't have a comparison dataset to use against it as
required by the Ridit::ridit function.
As a question of best practice, could I use a normally distributed
frequency distribution table gen
Hello,
This is simple:
which(A == 1, arr.ind = TRUE)
Hope this helps,
Rui Barradas
Às 12:03 de 14/09/20, Tuomas Koponen escreveu:
Hi all dear R-list users,
This might sound a silly problem, but but for one reason or another it has
proved unsolvable to me.
I need to solve the following ta
Hi,
Bert has pointed you to some R specific packages for meta-analyses via the Task
View.
It sounds like you may need to first address some underlying conceptual issues,
which strictly speaking, is off-topic for this list.
That being said, a quick Google search came up with some possible resou
Did you first try a web search? -- you should always do this before posting
here.
"meta-analysis in R" brought up this:
https://CRAN.R-project.org/view=MetaAnalysis
Have you looked at this task view yet?
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
st
Is this a homework problem? We try not to do others' homework here.
Incidentally, this can easily be done much more efficiently without any
for() loops.
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed
Hello all
I am doing some text mining on a set of five plain text files and have
run into a snag when I run hclust in that there are just too many leaves
for anything to be read. It returns a solid black line.
The texts have been converted into a TDM which has a dim of 5,292 and 5
(as per 5 do
Dear sir/madam,
Thank you in advance for taking the time to read my question. I am currently
trying to conduct a meta-analysis combining parallel and crossover trials.
According to the Cochrane Handbook, I can include crossover trials by using
t-paired statistics. So far, I have managed to condu
Hi all dear R-list users,
This might sound a silly problem, but but for one reason or another it has
proved unsolvable to me.
I need to solve the following task. I have tried to use two nested for
loops as a solution, but have not been able to made it work. It would be
great, if someone could for
Hello,
Please Ana, post data in dput format.
And the expected output too.
Hope this helps,
Rui Barradas
Às 17:37 de 14/09/20, Ana Marija escreveu:
sorry not replace with NA but with empty string for a name, for example
for example this:
geneSymbol["Ku8QhfS0n_hIOABXuE"]
Ku8QhfS0n_hIOABXuE
I can't understand non-words with that many letters. I think this is what you
are looking for:
> tmp <- c(A="a",B="b",C="c",D="d")
> names(tmp)
[1] "A" "B" "C" "D"
> tmp
A B C D
"a" "b" "c" "d"
> ## change values of B and C to "x" and "y"
> names(tmp) %in% c("B","C")
[1] FALSE TRUE TRUE
sorry not replace with NA but with empty string for a name, for example
for example this:
> geneSymbol["Ku8QhfS0n_hIOABXuE"]
Ku8QhfS0n_hIOABXuE
"MACC1"
would go when I subject it to
> geneSymbol["Ku8QhfS0n_hIOABXuE"]
Ku8QhfS0n_hIOABXuE
On Mon, Sep 14, 2020 at 11:35 AM Ana Marija w
Hello,
I have a vector like this:
> head(geneSymbol)
Ku8QhfS0n_hIOABXuE Bx496XsFXiAlj.Eaeo W38p0ogk.wIBVRXllY
QIBkqIS9LR5DfTlTS8 BZKiEvS0eQ305U0v34 6TheVd.HiE1UF3lX6g
"MACC1""GGACT" "A4GALT"
"NPSR1-AS1""NPSR1-AS1" "AAAS"
it has around 15000 en
Thank you again.
I finally used aggregate because it build a data frame straight away.
Stefano
(oo)
--oOO--( )--OOo
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mai
Hello,
I was running association analysis using --glm genotypic from:
https://www.cog-genomics.org/plink/2.0/assoc with these covariates:
sex,age,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,TD,array,HBA1C. The
result looks like this:
#CHROMPOSIDREFALTA1TESTOBS_CTB
Hello,
Here are two aggregate options, the first base R only, the second one
with package zoo.
year_month <- format(df$data_POSIX, "%Y-%m")
aggregate(value ~ year_month, df, mean)# or even value ~ format(etc)
# year_monthvalue
#12019-01 6.430922
#22019-02 4.846731
#32019-
Yes, perfect.
Thank you.
Stefano
(oo)
--oOO--( )--OOo
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.so...@regione.marche.it
---Oo-oO---
Hi Stefano,
What about this?
df$months<-format(df$data_POSIX,"%Y-%m")
snow_means<-by(df$value,df$months,mean)
Jim
On Mon, Sep 14, 2020 at 8:19 PM Stefano Sofia
wrote:
>
> Dear R-list users,
> I know that this is a trivial question, but I already wasted quite a large
> amount of time on that.
>
Dear R-list users,
I know that this is a trivial question, but I already wasted quite a large
amount of time on that.
I have a data frame with daily data of snow fall. I need to evaluate the
monthly mean for each month and each year in the data frame.
Could you help me to find an eficient way for
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