Machines for bioinformatics analysis | TEGAKARI, an information dissemination media for research and development

A customer involved in genome research contacted us about introducing a Linux workstation for bioinformatics analysis. The main use is for data analysis of Hi-C data, scRNAseq, scATACseq, etc., and it is expected to use Bowtie2, STAR, BWA, samtools, Juicer/juicebox, R (Seurat, Singac, etc...).

Specifically, they had the following conditions in mind, so they asked us if it could be realized within their budget.

CPU: Not specified (number of cores is more important than clock speed. Number of cores is about 20-36)
Memory: 128GB-256GB (memory capacity is important) I am considering a configuration of 32 x 6GB cards.
Storage: Not specified (2TB or more)
OS:Linux OS (Ubuntu24.04 or 22.04)
Location: Living room
Budget: Within 100 yen

Based on these conditions, we proposed the following configuration.

CPU	Intel Xeon W5-2565X 3.20GHz (up to 3.0GHz at TB4.8) 18C/36T
memory	Total 192GB DDR5 5600 REG ECC 32GB x 6
storage	2TB SSD M.2 NVMe Gen4
Video	NVIDIA RTX A400 4GB (MiniDisplayPort x4)
network	on board (2.5GbE x1 /10GbE x1)
Housing + power supply	Mid tower case + 1000W 80PLUS PLATINUM
OS	Ubuntu 24.04

We will tailor the plan to meet your needs as much as possible within your budget of 100 million yen.

GPU has low priority, so CPU and memory are prioritized.

Since none of the software you have contacted us about requires GPU performance, we have adopted the RTX A400 as the video card for screen output. Please contact us if you plan to use GPU calculations.

Memory configuration

We have configured it to be 32GB x 6 as per your request, but it is best to install modules in multiples of 4 to match the memory channels of this configuration. Therefore, please note that two of the six memory modules will be slightly slower than the original maximum speed achieved when four modules are installed.

■ Keywords

・What is Hi-C?

Hi-C (High-throughput Chromosome Conformation Capture) is an innovative technique for analyzing the three-dimensional structure of genomes by sequencing. It was developed in 2009 and can reveal the spatial arrangement of DNA within the cell nucleus at high resolution.

What is scRNAseq?

Single-cell RNA-seq (scRNA-seq) is a technology that allows the analysis of gene expression at the individual cell level. By performing transcriptome mapping of cells, differences between cells are revealed. This type of analysis method is necessary because even cells of the same species have minute differences. Potential applications include elucidating the heterogeneity within cancer cells and the process of cell differentiation. In addition, analysis is possible from small amounts of RNA, and it is used for detailed analysis.

What is scATACseq?

Single-cell ATAC-seq (scATACseq) is a technique for comprehensively analyzing chromatin accessibility at the individual cell level. It allows detailed investigation of epigenetic diversity within a cell population. scATAC-seq, when combined with scRNA-seq, allows for a more comprehensive understanding of cell states.

・What is Bowtie2?

Bowtie2 is a tool for aligning sequence reads to reference sequences.It excels at aligning relatively long genomes such as those of mammals.

reference: Bowtie 2: fast and sensitive read alignment *Jumps to an external site

What is STAR?

STAR is a program that maps reads (raw data) obtained by RNA-Seq to reference sequences. It is available on Github, and although it requires high specifications, it has a fast mapping speed.

reference:GitHub – alexdobin/STAR: RNA-seq aligner *Jumps to an external site

・What is BWA?

BWA is a software package for mapping low divergence sequences against large reference genomes such as the human genome. It consists of three algorithms: BWA-backtrack, BWA-SW, and BWA-MEM.

reference:Burrows-Wheeler Aligner *Jumps to an external site

・What is Samtools?

Samtools is a group of programs for manipulating data output from next-generation sequencers.
Samtools (read/write/edit/index/view SAM/BAM/CRAM formats)
BCFtools (read/write BCF2/VCF/gVCF files and call/filter/summarize SNP and mutation data) HTSlib (AC library for reading/writing next generation sequencing data)

reference:Samtools (Genome Research Limited) *Jumps to an external site

What is Juicer?

An open source tool for analyzing Hi-C data. It can create normalized contact maps from raw sequence data and process terabyte-sized Hi-C datasets.

reference:GitHub – aidenlab/juicer: A One-Click System for Analyzing Loop-Resolution Hi-C Experiments *Jumps to an external site

・What is JuiceBox?

An application for visualizing .hic files generated by Juicer. You can intuitively view and analyze the generated Hi-C maps.

reference:GitHub – aidenlab/Juicebox: Visualization and analysis software for Hi-C data – *Jumps to an external site

・What is R?

R is an open source, free software programming language/development environment for statistical analysis. It is used for calculations and graphing for statistical processing. Since there are many libraries, complex methods can be handled simply by calling the libraries.