Back

MAGScoT - a fast, lightweight, and accurate bin-refinement software

Ruehlemann, M. C.; Wacker, E. M.; Ellinghaus, D.; Franke, A.

2022-05-17 bioinformatics
10.1101/2022.05.17.492251 bioRxiv
Show abstract

We introduce MAGScoT, a fast, lightweight and accurate implementation for the reconstruction of highest-quality metagenome-assembled genomes (MAGs) from the output of multiple genome-binning softwares. MAGScoT outperforms popular bin-refinement solutions in terms of quality and quantity of MAGs as well as computation time and resource consumption. MAGScoT is available via GitHub (https://github.com/ikmb/MAGScoT) and as an easy-to-use Docker container (https://hub.docker.com/repository/docker/ikmb/magscot).

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Bioinformatics
◐ 1204 papers in training set
Top 0.6%
30.4%
Similar papers in this journal
2
Nature Communications
○ 5641 papers in training set
Top 17%
10.8%
Similar papers in this journal
3
Nature Methods
○ 385 papers in training set
Top 2%
6.6%
Similar papers in this journal
4
Genome Biology
○ 637 papers in training set
Top 3%
4.7%
Similar papers in this journal
50% of probability mass above
5
BMC Bioinformatics
○ 457 papers in training set
Top 2%
4.7%
Similar papers in this journal
6
Microbiome
○ 154 papers in training set
Top 0.8%
4.2%
7
mSystems
● 394 papers in training set
Top 2%
4.0%
8
Briefings in Bioinformatics
◐ 354 papers in training set
Top 3%
3.2%
9
Bioinformatics Advances
◐ 203 papers in training set
Top 2%
2.7%
10
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 2%
2.6%
11
Nature Biotechnology
○ 172 papers in training set
Top 2%
2.3%
12
GigaScience
◐ 212 papers in training set
Top 2%
2.3%
13
iMeta
○ 10 papers in training set
Top 0.1%
2.3%
14
Nucleic Acids Research
◐ 1281 papers in training set
Top 8%
1.9%
15
Communications Biology
○ 993 papers in training set
Top 16%
1.6%
16
Nature Computational Science
○ 55 papers in training set
Top 0.7%
1.6%
17
Genome Research
● 468 papers in training set
Top 4%
1.5%
18
Cell Reports Methods
○ 165 papers in training set
Top 3%
1.0%
19
Scientific Reports
○ 3612 papers in training set
Top 74%
0.8%
20
PLOS Computational Biology
● 1863 papers in training set
Top 20%
0.8%
21
Molecular Ecology Resources
○ 171 papers in training set
Top 2%
0.8%
22
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 8%
0.6%
23
iScience
○ 1154 papers in training set
Top 42%
0.6%
24
Microbial Genomics
● 225 papers in training set
Top 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.