I am using TCGAbiolinks package. I have run this code:
coadquery <- GDCquery(project = "TCGA-COAD",
data.category = "Transcriptome Profiling",
data.type ="Gene Expression Quantification",
workflow.type ="STAR - Counts", legacy = F,
experimental.strategy ="RNA-Seq")
GDCdownload(query = coadquery, method = "api")
coadprpr <- GDCprepare(coadquery, summarizedExperiment = T)
but when I run GDCprepare function it gives me error:
|==================================================|100%
Completed after 12 m
Error in `vectbl_as_col_location()`: ! Can't subset columns past the
end. i Locations 2, 3, and 4 don't exist. i There is only 1 column.
Run `rlang::last_error()` to see where the error occurred. There were
50 or more warnings (use warnings() to see the first 50)
Related
I am following the tutorial below in the link:
https://ycl6.github.io/16S-Demo/4_picrust2_tutorial.html
after copying this code :
# EC
set.seed(12345)
system.time({
aldex2_EC1 = aldex(p2EC1, sample_data(ps1a)$Group, mc.samples = 500, test = "t",
effect = TRUE, denom = "iqlr", verbose = TRUE)
})
it gives me an error : Error in aldex.clr.function(as.data.frame(reads), conds, mc.samples, denom, :
mismatch between number of samples and condition vector.
I am working on 5 or 6 samples..
I don't know what is the cause of the error
I have no solution in google.
I have a table with 6 columns in R (Date_T0, Date_T1 ...), all including Dates of assessment (e.g. 2015-03-29, 2015-04-14). I am now trying to calculate the difference between time points in weeks using the following code:
definition_blocks <- definition_blocks %>%
rowwise() %>%
mutate(dif_block1 = round((Date_T1-Date_T0)/7,2),
dif_block2 = round((Date_T2-Date_T1)/7,2),
dif_block3 = round((Date_T3-Date_T2)/7,2),
dif_block4 = round((Date_T4-Date_T3)/7,2),
dif_block5 = round((Date_T5-Date_T4)/7,2))
The following error occurs:
Error: Problem with `mutate()` column `dif_block1`.
i `dif_block1 = round((Date_T1 - Date_T0)/7, 2)`.
x / not defined for "Date" Object
i The error occurred in row 1.
Run `rlang::last_error()` to see where the error occurred.
In addition: Warning message:
Problem with `mutate()` column `dif_block1`.
i `dif_block1 = round((Date_T1 - Date_T0)/7, 2)`.
i Incompatible methods ("-.Date", "-.POSIXt") for "-"
i The warning occurred in row 1.
I am not sure why this code is not working. Can some help me? Thank you so much
I try to run tis command
dtm <- CreateDtm(tokens$text,
doc_names = tokens$ID,
ngram_window = c(1, 2))
However I receive this error:
Error in seq.default(1, length(tokens), 5000) :
wrong sign in 'by' argument
In addition: Warning message:
In CreateDtm(tokens$text, doc_names = tokens$ID, ngram_window = c(1, :
No document names detected. Assigning 1:length(doc_vec) as names.
Any idea what I have to change in order to run it properly?
I'm working the npreg example in the R np package documentation (by T. Hayfield, J. Racine), section 3.1 Univariate Regression.
library("np")
data("cps71")
model.par = lm(logwage~age + I(age^2),data=cps71)
summary(model.par)
#
attach(cps71)
bw = npregbw(logwage~age) # thislne not in example 3.1
model.np = npreg(logwage~age,regtype="ll", bwmethod="cv.aic",gradients="TRUE",
+ data=cps71)
This copied directly from the example, but the npreg call results in error message
*Rerun with Debug
Error in npreg.rbandwidth(txdat = txdat, tydat = tydat, bws = bws, ...) :
NAs in foreign function call (arg 15)
In addition: Warning message:
In npreg.rbandwidth(txdat = txdat, tydat = tydat, bws = bws, ...) :
NAs introduced by coercion*
The npreg R documentation indicates the first argument should be BW specificaion. I tried setting bws=1
model.np = npreg(bws=1,logwage~age,regtype="ll",
+ bwmethod="cv.aic",gradients="TRUE", data=cps71)
which gives the following error
*Error in toFrame(xdat) :
xdat must be a data frame, matrix, vector, or factor*
First time working with density estimation in R. Please suggest how to resolve these errors.
I'm trying to use cor.ci to obtain polychoric correlations with significance tests, but it keeps giving me an error message. Here is the code:
install.packages("Hmisc")
library(Hmisc)
mydata <- spss.get("S-IAT for R.sav", use.value.labels=TRUE)
install.packages('psych')
library(psych)
poly.example <- cor.ci(mydata(nvar = 10,n = 100)$items,n.iter = 10,poly = TRUE)
poly.example
print(corr.test(poly.example$rho), short=FALSE)
Here is the error message it gives:
> library(psych)
> poly.example <- cor.ci(mydata(nvar = 10,n = 100)$items,n.iter = 10,poly = TRUE)
Error in cor.ci(mydata(nvar = 10, n = 100)$items, n.iter = 10, poly = TRUE) :
could not find function "mydata"
> poly.example
Error: object 'poly.example' not found
> print(corr.test(poly.example$rho), short=FALSE)
Error in is.data.frame(x) : object 'poly.example' not found
How can I make it recognize mydata and/or select certain variables from this dataset for the analysis? I got the above code from here:
Polychoric correlation matrix with significance in R
Thanks!
You have several problems.
1) As previously commented upon, you are treating mydata as a function, but you need to treat it as a data.frame. Thus the call should be
poly.example <- cor.ci(mydata,n.iter = 10,poly = TRUE)
If you are trying to just get the first 100 cases and the first 10 variables, then
poly.example <- cor.ci(mydata[1:10,1:100],n.iter = 10,poly = TRUE)
2) Then, you do not want to run corr.test on the resulting correlation matrix. corr.test should be run on the data.
print(corr.test(mydata[1:10,1:100],short=FALSE)
Note that corr.test is testing the Pearson correlation.