627316.pdf
The combinatorial number of possible methylomes in biological time and space is astronomical. Consequently, the computational analysis of methylomes needs to cater for a variety of data, throughput and resolution. Here, we review recent advances in 2nd generation sequencing (2GS) with a focus on the...
| Γλώσσα: | English |
|---|---|
| Έκδοση: |
InTechOpen
2019
|
| id |
oapen-20.500.12657-31543 |
|---|---|
| record_format |
dspace |
| spelling |
oapen-20.500.12657-315432021-11-12T16:22:09Z Chapter 5 Computational Analysis and Integration of MeDIP-seq Methylome Data Wilson, Gareth A. Beck, Stephan sequencing biochemistry bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PSB Biochemistry The combinatorial number of possible methylomes in biological time and space is astronomical. Consequently, the computational analysis of methylomes needs to cater for a variety of data, throughput and resolution. Here, we review recent advances in 2nd generation sequencing (2GS) with a focus on the different methods used for the analysis of MeDIP-seq data. The challenges and opportunities presented by the integration of methylation data with other genomic data types are discussed as is the potential impact of emerging 3rd generation sequencing (3GS) based technologies on methylation analysis. 2019-10-04 14:42:20 2020-04-01T13:39:01Z 2017-04-12 23:55 2019-10-04 14:42:20 2020-04-01T13:39:01Z 2017-03-01 23:55:55 2019-10-04 14:42:20 2020-04-01T13:39:01Z 2020-04-01T13:39:01Z 2016 chapter 627316 OCN: 1030819225 http://library.oapen.org/handle/20.500.12657/31543 eng application/pdf n/a 627316.pdf InTechOpen Next Generation Sequencing - Advances, Applications and Challenges 10.5772/61207 10.5772/61207 09f6769d-48ed-467d-b150-4cf2680656a1 a37acbe5-fa0f-4e03-8449-5716595869a4 d859fbd3-d884-4090-a0ec-baf821c9abfd Wellcome 1 99148 Wellcome Trust Wellcome open access |
| institution |
OAPEN |
| collection |
DSpace |
| language |
English |
| description |
The combinatorial number of possible methylomes in biological time and space is astronomical. Consequently, the computational analysis of methylomes needs to cater for a variety of data, throughput and resolution. Here, we review recent advances in 2nd generation sequencing (2GS) with a focus on the different methods used for the analysis of MeDIP-seq data. The challenges and opportunities presented by the integration of methylation data with other genomic data types are discussed as is the potential impact of emerging 3rd generation sequencing (3GS) based technologies on methylation analysis. |
| title |
627316.pdf |
| spellingShingle |
627316.pdf |
| title_short |
627316.pdf |
| title_full |
627316.pdf |
| title_fullStr |
627316.pdf |
| title_full_unstemmed |
627316.pdf |
| title_sort |
627316.pdf |
| publisher |
InTechOpen |
| publishDate |
2019 |
| _version_ |
1771297383748993024 |
