Back

Whole Genome Methylation Sequencing via Enzymatic Conversion (EM-seq): Protocol, Data Processing and Analysis

Olova, N. N.; Andrews, S.

2023-10-10 genomics
10.1101/2023.10.07.561361 bioRxiv
Show abstract

Whole genome bisulfite sequencing (WGBS) has been the gold standard technique for base resolution analysis of DNA methylation for the last 15 years. It has been, however, associated with technical biases, which lead to overall overestimation of global and regional methylation values, and significant artifacts in extreme cytosine-rich DNA sequence contexts. Enzymatic conversion of cytosine is the newest approach, set to replace entirely the use of the damaging bisulfite conversion of DNA. The EM-seq technique utilises TET2, T4-BGT and APOBEC in a two-step conversion process, where the modified cytosines are first protected by oxidation and glucosylation, followed by deamination of all unmodified cytosines to uracil. As a result, EM-seq is degradation-free and bias-free, requires low DNA input, and produces high library yields with longer reads, little batch variation, less duplication, uniform genomic coverage, accurate methylation over a larger number of captured CpGs, and no sequence-specific artifacts.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
BMC Genomics
○ 406 papers in training set
Top 0.2%
12.6%
Similar papers in this journal
2
BMC Bioinformatics
○ 457 papers in training set
Top 1%
6.6%
Similar papers in this journal
3
GigaScience
◐ 212 papers in training set
Top 0.4%
6.1%
Similar papers in this journal
4
PLOS ONE
● 5266 papers in training set
Top 26%
6.1%
Similar papers in this journal
5
Nucleic Acids Research
◐ 1281 papers in training set
Top 4%
5.4%
Similar papers in this journal
6
Genome Biology
○ 637 papers in training set
Top 3%
4.8%
7
Nature Protocols
○ 33 papers in training set
Top 0.1%
4.0%
8
G3: Genes, Genomes, Genetics
◐ 252 papers in training set
Top 2%
3.2%
9
Current Protocols
○ 15 papers in training set
Top 0.1%
3.2%
50% of probability mass above
10
Methods
○ 34 papers in training set
Top 0.1%
3.2%
11
Molecular Ecology Resources
○ 171 papers in training set
Top 0.7%
3.2%
12
Bioinformatics
◐ 1204 papers in training set
Top 6%
2.3%
13
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 2%
2.3%
14
Genomics
○ 64 papers in training set
Top 0.5%
2.3%
15
Briefings in Bioinformatics
◐ 354 papers in training set
Top 4%
2.3%
16
Nature Communications
○ 5641 papers in training set
Top 42%
2.1%
17
eLife
● 5828 papers in training set
Top 46%
2.1%
18
F1000Research
○ 88 papers in training set
Top 1%
1.7%
19
Bioinformatics Advances
◐ 203 papers in training set
Top 3%
1.7%
20
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 3%
1.7%
21
Cell Reports Methods
○ 165 papers in training set
Top 2%
1.5%
22
Genes
○ 144 papers in training set
Top 2%
1.4%
23
Genome Research
● 468 papers in training set
Top 4%
1.4%
24
Scientific Reports
○ 3612 papers in training set
Top 60%
1.3%
25
Analytical Biochemistry
○ 26 papers in training set
Top 0.4%
1.1%
26
Wellcome Open Research
○ 67 papers in training set
Top 0.8%
1.1%
27
Life Science Alliance
● 285 papers in training set
Top 8%
0.8%
28
Epigenetics
○ 50 papers in training set
Top 0.7%
0.8%
29
Nature Biotechnology
○ 172 papers in training set
Top 4%
0.8%
30
STAR Protocols
○ 18 papers in training set
Top 0.3%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.