| Chapter title |
Practical Analysis of Hi-C Data: Generating A/B Compartment Profiles
|
|---|---|
| Chapter number | 16 |
| Book title |
X-Chromosome Inactivation
|
| Published in |
Methods in molecular biology, September 2018
|
| DOI | 10.1007/978-1-4939-8766-5_16 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-8765-8, 978-1-4939-8766-5
|
| Authors |
Hisashi Miura, Rawin Poonperm, Saori Takahashi, Ichiro Hiratani, Miura, Hisashi, Poonperm, Rawin, Takahashi, Saori, Hiratani, Ichiro |
| Abstract |
Recent advances in next-generation sequencing (NGS) and chromosome conformation capture (3C) analysis have led to the development of Hi-C, a genome-wide version of the 3C method. Hi-C has identified new levels of chromosome organization such as A/B compartments, topologically associating domains (TADs) as well as large megadomains on the inactive X chromosome, while allowing the identification of chromatin loops at the genome scale. Despite its powerfulness, Hi-C data analysis is much more involved compared to conventional NGS applications such as RNA-seq or ChIP-seq and requires many more steps. This presents a significant hurdle for those who wish to implement Hi-C technology into their laboratory. On the other hand, genomics data repository sites sometimes contain processed Hi-C data sets, allowing researchers to perform further analysis without the need for high-spec workstations and servers. In this chapter, we provide a detailed description on how to calculate A/B compartment profiles from processed Hi-C data on the autosomes and the active/inactive X chromosomes. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 58 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 26% |
| Researcher | 8 | 14% |
| Student > Master | 7 | 12% |
| Student > Doctoral Student | 5 | 9% |
| Student > Bachelor | 3 | 5% |
| Other | 6 | 10% |
| Unknown | 14 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 29 | 50% |
| Agricultural and Biological Sciences | 7 | 12% |
| Medicine and Dentistry | 3 | 5% |
| Unspecified | 1 | 2% |
| Sports and Recreations | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 13 | 22% |