Nig General Analysis

NIG supercomputer — General Analysis zone

The NIG supercomputer (run by DDBJ at the National Institute of Genetics, Mishima, Japan) is a SLURM cluster. This skill covers the general analysis zone — the open zone for non-personal-genome work. It is reached through general-zone login nodes (e.g. nig-a003, hostname a003).

The personal genome analysis zone (controlled-access human data) is a completely separate network and is not reachable from the general zone — different login nodes, different SLURM, different databases. For that zone use the nig-personal-genome skill.

Everything here is designed so you rarely need to install anything: tools come as pre-built container images, and the major public databases are already on the shared filesystem. The three sections below map to the three things you do on this cluster: (a) run SLURM jobs, (b) run tools from /usr/local/biotools, (c) use the pre-installed databases.

When dispatching from Claude Science, the host is registered as an SSH compute target (typically ssh:nig-a003). Read compute_details({provider:'ssh:nig-a003'}) first — it accumulates verified partition/account/path facts across sessions — then follow the remote-compute-ssh skill for the submit → wait → harvest mechanics. This skill supplies the NIG-specific content that goes inside the job script.

(a) SLURM — partitions, accounts, submitting

The scheduler is SLURM. Jobs are submitted with sbatch; interactive shells with srun. From Claude Science you normally submit through host.compute.create('ssh:nig-a003').submit_job(...), which wraps sbatch — put the #SBATCH directives at the top of the command script.

Partitions (general zone).

Always trust the live sinfo output over any table — including the one below and the official docs. The general zone lends compute nodes out to labs, so partitions appear, disappear, and change size over time. The published documentation lags reality; the machine is the source of truth. Run sinfo -s (and scontrol show partition <name> for account gating) at the start of a session and target what is actually up.

sinfo -s                                  # live partitions + node availability
scontrol show partition epyc              # limits / AllowAccounts for one partition
sacctmgr -n show assoc user=$USER format=account,partition   # what you may use

The baseline open partitions (per DDBJ docs, subject to the caveat above):

login is the interactive node for development and small, short jobs — fine for quick interactive work but not for heavy batch compute. epyc is the standard batch partition; use rome for more cores-per-node throughput, medium when you need more memory per core (16 GB/core), and short.q for short jobs. Reality can differ from this table — e.g. a partition listed here may be temporarily withdrawn, and sinfo will show the current truth. If short.q is not in sinfo, it is simply not up right now; use epyc.

sinfo also lists many lab-owned partitions named <labname>-c<N> (e.g. kumamoto-c768, rikagaku-c192, nakayama-c576, tokai-c64). Each is gated by AllowAccounts=<labname>-group and is usable only if you belong to that group. Don't target them unless the user says they have access.

Account. The general-zone account is typically general_analysis. Confirm what the user's account is with sacctmgr -n show assoc user=$USER format=account,partition. In a job script set it with #SBATCH --account=... only if the cluster requires it (many general jobs run without an explicit account).

A minimal job script:

#SBATCH --partition=epyc
#SBATCH --cpus-per-task=8
#SBATCH --mem=16G
#SBATCH --time=2:00:00

# ... apptainer exec commands go here (see section b) ...

Time limits are generous (partitions allow very long walltimes), but always set --time to something realistic so the scheduler can backfill your job. Ask for --cpus-per-task / --mem that match the tool; most alignment and phylogenetics tools are happy with 4–16 cores and a few GB.

Useful commands: squeue --me (your queue), sinfo -s (partition state), sacct -j <jobid> (accounting for a finished job), scancel <jobid>.

(b) Tools — /usr/local/biotools via apptainer

This is the key idea: you almost never install a bioinformatics tool on NIG. The cluster ships the entire BioContainers collection as pre-built Singularity/apptainer images. Per the official DDBJ docs this is over 2,000 distinct analysis programs and, counting versions, more than 90,000 Singularity image files under /usr/local/biotools/. Do not try to list them all — know the layout and search for the one you need. For a tool's usage details, consult the BioContainers registry / the tool's own documentation.

Layout. Images live under:

/usr/local/biotools/<first-letter>/<tool>:<version>

The <first-letter> is the first character of the tool name. So MAFFT images are under /usr/local/biotools/m/, trimAl under t/, IQ-TREE under i/, and so on. Each tool usually has many versioned image files (e.g. mafft:7.310--hdbdd923_7).

Find a tool / its versions (cheap — scoped to one letter directory):

ls /usr/local/biotools/m/ | grep -i '^mafft:'      # all MAFFT versions
ls /usr/local/biotools/i/ | grep -i '^iqtree'      # iqtree and iqtree2

Pick the newest version tag (last line of a sorted list) unless the user needs a specific one.

Run a tool. apptainer (v1.x) is on the default PATH — no module load needed. The image is the executable environment; call the tool inside it with apptainer exec:

IMG=/usr/local/biotools/m/mafft:7.310--hdbdd923_7
apptainer exec "$IMG" mafft --auto input.fasta > aligned.fasta

singularity exec also works (singularity-ce 4.x is installed) and is interchangeable with apptainer exec here — the official DDBJ examples use singularity exec. For a tool you call repeatedly in a script, an alias keeps lines short, e.g. alias singR="singularity exec /usr/local/biotools/r/r-base:3.5.1 R".

Binding paths. apptainer auto-mounts your home and usually the current working directory. If a tool needs to read the pre-installed databases or a scratch path that isn't auto-mounted, bind it explicitly with -B:

apptainer exec -B /usr/local/resources:/usr/local/resources \
  /usr/local/biotools/b/blast:2.14.0--pl5321h6f7f691_0 \
  blastp -query q.fasta -db /usr/local/shared_data/blastdb/nr -out hits.tsv -outfmt 6

Keep all inputs and outputs under the job workdir (or a path you bind) so Claude Science's harvester can pull the results back.

A complete general-zone job script (MAFFT → trimAl → IQ-TREE, chained through three images):

#SBATCH --partition=epyc
#SBATCH --cpus-per-task=8
#SBATCH --mem=16G
#SBATCH --time=4:00:00

B=/usr/local/biotools
MAFFT=$B/m/$(ls $B/m/ | grep '^mafft:7.310' | tail -1)
TRIMAL=$B/t/$(ls $B/t/ | grep '^trimal:1.4.1' | tail -1)
IQTREE=$B/i/$(ls $B/i/ | grep '^iqtree:' | tail -1)

apptainer exec "$MAFFT"  mafft --auto input.fasta > aln.fasta
apptainer exec "$TRIMAL" trimal -in aln.fasta -out aln.trim.fasta -automated1
apptainer exec "$IQTREE" iqtree -s aln.trim.fasta -m MFP -bb 1000 -nt AUTO
ls -lh aln.trim.fasta.* aln.fasta

(c) Pre-installed databases

The DDBJ keeps large public databases on the shared filesystem, so you should point tools at these paths instead of downloading anything. As with tools, know the roots and look inside — don't enumerate everything.

Two roots:

• /usr/local/resources/ — the DDBJ archive and public mirrors:
  • mirror/ and mirror_database/ — mirrors of NCBI (ftp.ncbi.nih.gov), EBI (ftp.ebi.ac.uk), UniProt, PDB/PDBj, RefSeq, H-Invitational.
  • bioproject/, biosample/, dra/ (DDBJ Sequence Read Archive), gea/ (Genomic Expression Archive), metabobank/, trad/, reference/.
• /usr/local/shared_data/ — analysis-ready databases and references:
  • blastdb/ — pre-formatted BLAST databases (nr, nt, etc.).
  • genomes/, refseq/, uniprot/, pdb/ — sequence/structure references.
  • dfast/ (prokaryotic annotation), db/, dblink/, sra/, rdf/.
  • public-human-genomes/ — GRCh38 and CHM13 reference assemblies (open reference genomes; note individual human genotype data lives in the personal-genome zone, not here).

Discover what's actually present (versions change over time):

ls /usr/local/shared_data/blastdb/           # which BLAST DBs are formatted
ls /usr/local/resources/mirror_database/     # which mirrors exist
ls /usr/local/shared_data/genomes/           # reference genomes on hand

Using them. Point the tool's -db / reference argument directly at the path, and bind the root into the container if you're running via apptainer:

# BLAST against the shared nr, no download needed
apptainer exec -B /usr/local/shared_data:/usr/local/shared_data \
  /usr/local/biotools/b/$(ls /usr/local/biotools/b/ | grep '^blast:' | tail -1) \
  blastp -query q.fasta -db /usr/local/shared_data/blastdb/nr \
         -num_threads 8 -outfmt 6 -out hits.tsv

BLASTDB is not set by default, so always give the full DB path (or export BLASTDB=/usr/local/shared_data/blastdb at the top of your script).

Quick recall

• Tools: /usr/local/biotools/<letter>/<tool>:<ver> → apptainer exec <img> <cmd>. Search, don't enumerate.
• Databases: /usr/local/resources/ (archive + mirrors) and /usr/local/shared_data/ (blastdb, genomes, refseq, uniprot, pdb…). ls the root you need; bind with -B.
• SLURM: sinfo -s is the source of truth (docs lag; nodes get lent out). Default batch partition epyc; account usually general_analysis; never heavy compute on login.
• From Claude Science: compute_details first, then remote-compute-ssh for submit/wait/harvest; put #SBATCH + apptainer lines in the job command.
• This is the general zone; controlled human-genome work → nig-personal-genome.

Official documentation

The DDBJ maintains docs (Japanese, with an English toggle). Treat them as background/orientation, not ground truth for live cluster state: the published tables can lag reality (nodes get lent to labs, partitions change). For anything that must be current — which partitions are up, which DBs are present, which tool versions exist — query the machine (sinfo, ls) and prefer that. Use these pages to understand concepts and layout:

• Hardware (2025): https://sc.ddbj.nig.ac.jp/guides/hardware/hardware2025/
• SLURM partitions (general zone): https://sc.ddbj.nig.ac.jp/guides/using_general_analysis_division/ga_slurm_partition/
• Apptainer / Singularity: https://sc.ddbj.nig.ac.jp/guides/software/Container/Apptainer/
• BioContainers images: https://sc.ddbj.nig.ac.jp/guides/software/Container/BioContainers/
• SLURM usage (batch/parallel/array/interactive): https://sc.ddbj.nig.ac.jp/guides/software/JobScheduler/Slurm/
• General-analysis-zone guide index: https://sc.ddbj.nig.ac.jp/guides/using_general_analysis_division/