RStudio Server

Carolina Cloud’s RStudio Server is a web-based R development environment pre-loaded with a comprehensive genomics and bioinformatics toolkit. It includes 30+ command-line tools (samtools, GATK, STAR, PLINK, Nextflow) and a full R/Bioconductor stack (DESeq2, edgeR, GenomicRanges, tidyverse).

Via the Dashboard

Sign in at console.carolinacloud.io
In the sidebar, click Create then Genomics
Click the RStudio Server card
Select your CPU tier — High Performance is recommended for CPU-intensive bioinformatics workloads
Use the sliders to configure vCPUs, RAM, and disk size. Genomics workloads often benefit from generous RAM (64+ GiB) and disk (500+ GiB) allocations
Optionally expand S3 Integration to pre-configure aws s3 access for pulling reference genomes or uploading results
Review the cost and click Create
Once running, click the Open button on your instance card

Logging in to RStudio:

Username: ccloud
Password: Shown on your instance card in the dashboard

Via the API

curl -X POST https://console.carolinacloud.io/api/instance/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "resource_type": "container",
    "flavor": "rstudioserver",
    "n_vcpus": 16,
    "mem_gib": 64,
    "disk_size_gib": 500,
    "cpu_tier": "high-performance"
  }'

The response includes a webapp_url field — that’s the URL to open RStudio.

Optional fields:

Field	Description
`name`	Human-friendly name
`cpu_tier`	`general-purpose` (default) or `high-performance`
`aws_access_key_id`	S3 access key for pre-configured `aws s3` access
`aws_secret_access_key`	S3 secret key
`aws_endpoint_url`	S3 endpoint (required for non-AWS providers)
`aws_prefill_bucket`	Bucket path to pre-download into `~/s3-prefill/` on startup

Via the CLI

# RStudio Server for genomics research
ccloud new container --cpus 16 --ram 64 --disk 500 \
  --flavor rstudioserver \
  --name rstudio-genomics

# Access the URL from the dashboard after creation

Accessing RStudio

RStudio Server is accessed through your web browser:

Click the Open button on the instance card, or
Navigate to https://<instance-name>.<slave-hostname>.carolina.cloud
Log in with username ccloud and the password from your instance card

All genomics tools (samtools, GATK, bowtie2, STAR, kallisto, bcftools, Nextflow, etc.) are available from the command line, alongside the RStudio web interface.

Pre-installed tools

R packages: DESeq2, edgeR, limma, GenomicRanges, Biostrings, rtracklayer, tidyverse, ggplot2, BiocManager

Command-line tools: samtools 1.22, bcftools 1.22, GATK 4.6, STAR 2.7, bowtie2 2.5, kallisto 0.51, PLINK 2.0, beagle 5.4, GLIMPSE2 2.0, Nextflow 25.10

System: Python 3.12, Java (OpenJDK), R with full dev tools, complete build toolchain

For the full list, see the Pre-installed Tools reference.