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GOSe-6mo-imputation
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Kevin Kunzmann
GOSe-6mo-imputation
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54cbfb2d
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54cbfb2d
authored
Sep 03, 2020
by
Kevin Kunzmann
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README.md
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54cbfb2d
# GOSe
6mo
imputation for CENTER-TBI
# GOSe imputation for CENTER-TBI
This repository contains the code for imputing the 6 months GOSe using
This repository contains the code for imputing the 6 months GOSe using
a multi-state model in CENTER-TBI.
a multi-state model in CENTER-TBI.
The workflow is completely automated using snakemake and a singularity
Execution requires
container with the required dependencies is awailable at
[
zenodo.org
](
https://zenodo.org/record/2641161
)
(DOI: 10.5281/zenodo.2641161).
Singularity >= 2.6.0 is required to run the code in a container, alternatively
1.
access to the CENTER-TBI Neurobot database at https://center-tbi.incf.org/ or
the dependencies can be installed manually (check the
`container-recipe`
file).
a manually downloaded data file according to the specification given below
2.
a recent version of
[
R
](
https://www.r-project.org/
)
(
4+
)
3.
(optionally) the
[
RStudio IDE
](
https://rstudio.com/products/rstudio/download/
)
4.
(optionally) the version control system
[
git
](
https://git-scm.com/
)
to
easily download this repository to your local file system.
To get started, download the code and
`cd`
in the repository folder
To get started, download the code and change into the repository folder.
Using git on a Unix system (Linux) this can be done via
```
bash
```
bash
git clone https://git.center-tbi.eu/kunzmann/gose-6mo-imputation-production.git
git clone https://git.center-tbi.eu/kunzmann/gose-6mo-imputation-production.git
cd
gose-6mo-imputation-production
cd
gose-6mo-imputation-production
```
```
Next, download the pre-build container image from zenodo.org via the
Open this folder in Rstudio. This should activate the prepared
provided script
R environment automatically and locall;y install any R package dependencies.
```
bash
See the documentation for
[
renv
](
https://rstudio.github.io/renv/articles/renv.html
)
./scripts/download-container
in case of problems.
The required R environment can also be restored manually by invoking
```
```
This will download the
`container.sif`
file (~1Gb) in the current working
install.packages("renv")
directory.
renv::restore(clean = TRUE, prompt = FALSE)
An automated download script via the Neurobot-API is provided but requires
that the Neurobot username and API token are available as environment variables
```
bash
export
NEUROBOT_USR
=[
your-neurobot-username]
export
NEUROBOT_API
=[
your-neurobot-api-token]
```
```
The required data set (for version 1.2 on the Neurobot staging server) can
in an R console with working directory set to
`[my-working-direcrtory]/gose-6mo-imputation-production`
then automatically be downloaded via
where
`[my-working-direcrtory]`
is the location on yur file system that you
```
bash
placed the repository in.
singularity
exec
container.sif snakemake download
To execute the markdown file the recorded GOSe values are required
in a .csv file named
`tbl_gose.csv`
in the same folder, i.e.
`[my-working-direcrtory]/gose-6mo-imputation-production/tbl_gose.csv`
.
The .csv file must contain the Neurobot variables
```
```
Alternatively, a .csv file with the correct column names / ordering can
subjectId
directly be places in the
`data`
subfolder (see
`scripts/check-inputs`
for
Outcomes.DerivedCompositeGOSE
detailed specification).
Outcomes.DerivedCompositeGOSEDaysPostInjury
The imputation can then be started by invoking
Subject.Age
```
bash
Subject.PatientType
singularity
exec
container.sif snakemake impu
te
Subject.DeathDa
te
```
```
This produces a .html and a .csv file with imputed values in the subfolder
in exactly this order.
`output`
.
At the time of writing this report the newest staging data set could be
accessed via the saved link
`https://neurobot-stage.incf.org/_5f476d41eedb867816a10376`
.
Finally, open the project in Rstudio, open the
`imputation-report.Rmd`
in
Rstudio and
[
`knit' it
](
https://rmarkdown.rstudio.com/
)
.
This produces a .html with a basic report and a
`tbl_gose_imputed.csv`
file with imputed values.
imputation-report.Rmd
View file @
54cbfb2d
...
@@ -212,7 +212,7 @@ fit <- msm::msm(
...
@@ -212,7 +212,7 @@ fit <- msm::msm(
censor.states = 2:7, # cannot be dead since these were filtered previously
censor.states = 2:7, # cannot be dead since these were filtered previously
control = list(
control = list(
fnscale = 12000,
fnscale = 12000,
maxit = 10
,# 10
^4,
maxit = 10^4,
trace = 2
trace = 2
)
)
)
)
...
...
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