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MOAL: Multi-Omic Analysis at Lab.A simplified methodology workflow to make reproducible omic bioanalysis.

Dumont, F.; Ponsardin, E.; Bernadat, G.; Cohen-Kaminsky, S.

2023-10-20 bioinformatics
10.1101/2023.10.17.562686 bioRxiv
Show abstract

Omic data research projects are still developing today, but analysis suffers from not having a standardized workflow for biostatistics and functional integration steps that we gather here as bioanalysis. To make bioanalysis more reproducible and accessible, we created MOAL (Multi-Omic Analysis at Lab), an R package including a omic() function that automates most classical tasks. We reproduced in one go the results of a published dataset starting from unfiltered available data confirming the capabilities to automate the production of omic bioanalysis using MOAL.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
BMC Bioinformatics
○ 457 papers in training set
Top 0.3%
15.2%
Similar papers in this journal
2
PLOS ONE
● 5266 papers in training set
Top 18%
9.7%
Similar papers in this journal
3
GigaScience
◐ 212 papers in training set
Top 0.2%
7.9%
Similar papers in this journal
4
Bioinformatics
◐ 1204 papers in training set
Top 4%
4.9%
Similar papers in this journal
5
International Journal of Molecular Sciences
○ 494 papers in training set
Top 2%
4.1%
6
Genes
○ 144 papers in training set
Top 0.6%
4.1%
Similar papers in this journal
7
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 1%
3.2%
8
Scientific Reports
○ 3612 papers in training set
Top 33%
3.2%
50% of probability mass above
9
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 1%
3.1%
10
Briefings in Bioinformatics
◐ 354 papers in training set
Top 3%
2.8%
11
PROTEOMICS
○ 43 papers in training set
Top 0.3%
2.5%
12
BMC Research Notes
○ 33 papers in training set
Top 0.2%
2.1%
13
BMC Medical Genomics
○ 50 papers in training set
Top 0.4%
1.9%
14
Database
◐ 61 papers in training set
Top 0.4%
1.7%
15
Biomedicines
○ 67 papers in training set
Top 1%
1.7%
16
Frontiers in Bioinformatics
○ 49 papers in training set
Top 0.4%
1.7%
17
Biology
○ 45 papers in training set
Top 0.2%
1.7%
18
Nucleic Acids Research
◐ 1281 papers in training set
Top 9%
1.7%
19
PLOS Computational Biology
● 1863 papers in training set
Top 15%
1.5%
20
BMC Genomics
○ 406 papers in training set
Top 5%
1.5%
21
Frontiers in Genetics
○ 230 papers in training set
Top 3%
1.3%
22
F1000Research
○ 88 papers in training set
Top 2%
1.3%
23
BioData Mining
○ 22 papers in training set
Top 0.4%
1.1%
24
Methods
○ 34 papers in training set
Top 0.5%
1.0%
25
PeerJ
◐ 308 papers in training set
Top 10%
0.9%
26
Journal of Proteome Research
● 234 papers in training set
Top 2%
0.8%
27
Gigabyte
● 62 papers in training set
Top 1%
0.6%
28
Computer Methods and Programs in Biomedicine
○ 28 papers in training set
Top 1%
0.6%
29
SoftwareX
○ 15 papers in training set
Top 0.3%
0.6%
30
Biology of Sex Differences
○ 32 papers in training set
Top 0.7%
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.