Omics analysis machine | Information dissemination media for research and development TEGAKARI

A customer involved in drug research and development consulted us about a PC for Omics analysis.
Up until now, we have been calculating with a general notebook PC, but there are problems with the amount of data that can be analyzed and the time it takes to process, so we would like to switch to a dedicated PC.

In addition, since sample analysis of the data to be handled is outsourced, I hear that the PC to be introduced will mainly analyze from raw data.
As a specific request, we have the following conditions.

・CPU: Core i7 or Core i9
・ Memory: 64GB
・Storage: 2TB
Video: Decent card that supports dual displays with Geforce
・OS: Windows
・Software used: R (R Studio), Python, Jupyter
・Budget: About 60 million yen
・Display: About 32-inch display
・Others: I would like to use it on dual displays, but please let me know if there is a display environment suitable for users who use it in a similar way.

Based on the contents of the consultation, we proposed the following configuration.

【Main Specifications】

CPU	Core i9-13900K (3.00GHz 8-core + 2.20GHz 16-core)
memory	64GB
storage	2TB M.2 SSD
Video	NVIDIA Geforce RTX4070 12GB
network	on board (2.5GBase-T x1) Wi-Fi x1
Housing + power supply	Middle tower case + 850W
OS	Microsoft Windows 11 Professional 64bit
Other	32-inch wide display WQHD

This is a configuration proposal that assumes processing by the CPU.
The Core i9-13900K has more cores than the Core i7-13700K and also a higher Boost limit per core, so there is an advantage in speed per computation.

GPUBack-calculating from the budget, GPU acceleration is also possible, but if the purpose is only screen output, it is possible to change to a low-end model and lower the cost.

We have selected a WQHD compatible monitor considering the balance between physical size and display area.

The configuration of this case study is based on the conditions given by the customer.
Please feel free to contact us even if you are considering different conditions from what is posted.

■ Keywords

・What is Omics analysis?
Omics analysis is a data-driven approach widely used in biology and medicine. Omics is a general term for technologies for collecting and analyzing biological data, such as genomics, proteomics, and transcriptomics.
Omics analysis utilizes advanced technologies such as high-throughput experimental techniques and next-generation sequencing.The large amount of data generated by this is analyzed using statistical techniques and data mining techniques, enabling analysis of disease mechanisms, identification of new biomarkers, and application to personalized medicine.

・What is R?
R is an open source and free software programming language/development execution environment for statistical analysis.Used in calculations and graphing for statistical processing.
Since many libraries exist, complex techniques can be handled by simply calling the library.

reference:The R Project for Statistical Computing *Jumps to an external site

・What is Rstudio?
Rstudio is an integrated development environment for using R.It offers an intuitive and easy-to-use user interface, including project management features, code editor, code auto-completion, syntax highlighting, debugger, profiler, support for markdown documents, package management features, interactive graphics viewing, and more. It has a variety of functions.

reference:RSTUDIO IDE (Posit) *Jumps to an external site

・What is Python?
Python is an object-oriented programming language copyrighted by the Python Software Foundation (PSF).Its programming syntax is simple, making it highly readable, and it also features a wide variety of components, such as libraries and frameworks, that are suitable for different purposes.A popular language for programming beginners to advanced users.

reference:Python *Jumps to an external site

reference:[Feature Article] Programming language Python Why is it so popular? --Tools to accelerate Python programming * Jump to our owned media "TEGAKARI"

・What is Jupyter?

Jupyter is open source software for interactive computing.The name comes from the three core programming languages supported by Jupyter: Julia, Python, and R.There are two main variations, Jupyter Notebook and JupyterLab.