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❯ checking R code for possible problems ... [11s/10s] NOTE
  .filter_transciptome: no visible binding for global variable
    'tempus_ensembl_id'
  .filter_transciptome: no visible binding for global variable
    'gene_symbol'
  .tbl_cnv: no visible binding for global variable 'n_reads'
  .tbl_cnv: no visible global function definition for 'STRING_AGG'
  .tbl_diagnosis: no visible global function definition for 'date_diff'
  .tbl_diagnosis_dates: no visible binding for global variable
Write a R package vignette for a package called "Tempustables" that has the following functions with descriptions and examples as given below. The vignette needs to be fairly easy for users to follow. Provide examples and description for each function.
Collect Normalized RNA by Cohort
Description:
Collecting the whole transcriptome for over 100 samples from
'normalized_rna' in your R session will typically fail, requiring
you to write some sort of a loop to get all the patients. This
function does all that work for you and runs the query in
parallel.
diff --cc R/tbl_patient_record.R
index 43600b0,b236cb4..0000000
--- a/R/tbl_patient_record.R
+++ b/R/tbl_patient_record.R
@@@ -1,132 -1,154 +1,198 @@@
-#' Table of patient records with a curated diagnosis
+#' Return a Table of Patient Records with a Curated Diagnosis
#'
-#' Returns relevant metadata regarding the patient records and the
-#' depth of associated data for each record. Excludes records that are
tbl_patient_record.R
44: tbl("patient") |>
61: tbl("molecular_inventory") |>
70: tbl("combined_diagnosis") |>
83: tbl("medications_enhanced") |>
tbl_sample_therapy.R
57: tbl("onco_care_plan") |>

How to locally run the docker image

Build a new docker image

docker build -t us.gcr.io/tl-jvu4eyij9cslnrj0msep/trreports:0.0.3

Test the docker image locally

library(readr)
library(dplyr)
cmd <- 'gcloud compute instances list --filter="tn-pytorch" --format="table(name, status, labels.created_by.list(), labels.image.list())" > tsci_gcloud.csv'
system(cmd)
dat <- read_table('tsci_gcloud.csv')

Review

DESCRIPTION

NAMESPACE

NEWS

R

setGeneric("cloud_cp", function(x, ...) standardGeneric("cloud_cp"))
cloud_rm <- function(x, ...)
UseMethod("cloud_rm")
cloud_rsync <- function(x, ...)
UseMethod("cloud_rsync")
## azure
setClass("Cloud")
AzureCloud <- setClass("AzureCloud", contains = "Cloud")
setMethod("cloud_cp", "AzureCloud", function(x, from, to, ...) {
## implement cp for Azure
> AnVIL:::repository_stats()
Container: bioconductor_docker
Bioconductor version: 3.15
Bioconductor binary repos:
https://bioconductor.org/packages/3.15/container-binaries/bioconductor_docker
PACKAGES timestamp: 2022-05-31 13:51:00 UTC
Query timestamp: 2022-06-07 13:25 UTC
Bioconductor software packages: 2120
Binary packages: 3692
Binary software packages: 2100
git pull origin master
git pull upstream master
## Make sure devel does not already exist
git branch -d devel
## Create and push the devel branch
git checkout -b devel
git push origin devel