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What is the sharp weapon of Hi-C data processing and analysis Juicer? in view of this problem, this article introduces the corresponding analysis and solution in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible method.

Through Hi-C data, we can analyze the basic units of chromatin spatial structure such as TAD,chromatin loops and enhance our understanding of the three-dimensional structure of chromatin. In the face of massive Hi-C data, how to efficiently complete data analysis has become a challenge.

At present, there are many softwares available for the analysis of Hi-C data, and juicer is undoubtedly one of the most widely used software. The source code of the software is hosted on github

As the following figure shows, juicer, like its name, is like a juicer that inputs the raw fastq data generated by Hi-C and goes through layers of processing until a valid data analysis result is produced. In the whole process of data analysis, users do not need advanced programming skills, only some basic operating specifications, everyone can use the software to analyze Hi-C data.

As a powerful analysis software, juicer has the following characteristics

It can analyze and process massive data at TB level, and can effectively make use of hardware resources such as FPGA, GPU, cluster, etc., to accelerate processing speed.

Some complete series of pipeline are provided, such as data preprocessing, interactive graph creation and visualization, TAD and chromatin ring structure prediction.

Easy to use and does not require complex background knowledge

According to the function, the software is divided into three major analysis steps, and the final analysis results can be obtained by running in turn.

Data preprocessing, aligning the original fastq sequence with the reference genome, identifying the valid pairs in it, and generating a file with the suffix hic

Read the hic file, create a visual interactive graph, also known as contact map, and normalize it

Using algorithm to predict the structure of TAD and chromatin ring

The full functionality is as follows

Juicer uses ArrowHead algorithm to transform the original interaction matrix, predicts the topological association domain of TAD, and uses HiCUUPS algorithm to identify chromatin ring chromatin loops. Compared with other Hi-C data processing software, juicer has more complete functions.

Juicer has created an original file format called hic, which is used to store information about Hi-C data, which is a highly compressed binary file format. You can see the details of this format in the following link

Https://github.com/theaidenlab/juicebox/blob/master/HiC_format_v8.docx

The usage of the software will be described in detail in subsequent articles.

This is the answer to the question about how Juicer is a sharp tool for Hi-C data processing and analysis. I hope the above content can be of some help to you. If you still have a lot of doubts to be solved, you can follow the industry information channel to learn more about it.

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