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MultiVirusConsensus: An accurate and efficient open-source pipeline for identification and consensus sequence generation of multiple viruses from mixed samples.

Moshiri, N.

2026-03-26 infectious diseases
10.64898/2026.03.24.26349218 medRxiv
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Motivation: Viral surveillance from mixed samples (e.g. wastewater) has become critical in public health efforts to track and contain pathogens. However, existing open-source bioinformatics tools for viral consensus sequence generation are optimized for individual viruses (rather than multiple potential viruses of interest). Results: MultiVirusConsensus is an accurate and efficient open-source pipeline for identification and consensus sequence generation of multiple viruses from mixed samples. It utilizes the memory-efficient ViralConsensus tool via bash process substitution to simultaneously perform consensus sequence calling on all viruses of interest (1) completely in parallel, and (2) by piping datastreams between tools without writing/reading intermediate files (thus eliminating slowdowns related to slow disk accesses). Availability: MultiVirusConsensus is freely available as an open-source software project at: https://github.com/niemasd/MultiVirusConsensus

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

1
Virus Evolution
◐ 155 papers in training set
Top 0.3%
7.8%
Similar papers in this journal
2
Nature Biotechnology
○ 172 papers in training set
Top 0.5%
6.6%
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3
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◐ 1204 papers in training set
Top 4%
5.4%
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4
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 0.7%
5.4%
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5
PLOS Computational Biology
● 1863 papers in training set
Top 7%
5.4%
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6
BMC Bioinformatics
○ 457 papers in training set
Top 2%
5.1%
7
Genome Biology
○ 637 papers in training set
Top 3%
4.8%
8
GigaScience
◐ 212 papers in training set
Top 0.9%
4.0%
9
Nature Communications
○ 5641 papers in training set
Top 34%
3.4%
10
Cell Reports Methods
○ 165 papers in training set
Top 0.6%
3.2%
50% of probability mass above
11
Viruses
○ 332 papers in training set
Top 2%
3.2%
12
PeerJ
◐ 308 papers in training set
Top 3%
2.7%
13
iScience
○ 1154 papers in training set
Top 14%
2.1%
14
Biology Methods and Protocols
◐ 61 papers in training set
Top 0.6%
2.1%
15
Briefings in Bioinformatics
◐ 354 papers in training set
Top 4%
1.9%
16
Life Science Alliance
● 285 papers in training set
Top 3%
1.9%
17
Frontiers in Microbiology
○ 427 papers in training set
Top 5%
1.7%
18
Wellcome Open Research
○ 67 papers in training set
Top 0.5%
1.7%
19
F1000Research
○ 88 papers in training set
Top 2%
1.5%
20
Nature Computational Science
○ 55 papers in training set
Top 0.8%
1.5%
21
PLOS ONE
● 5266 papers in training set
Top 49%
1.5%
22
Scientific Reports
○ 3612 papers in training set
Top 60%
1.3%
23
BMC Genomics
○ 406 papers in training set
Top 5%
1.3%
24
Microbial Genomics
● 225 papers in training set
Top 2%
1.1%
25
Genome Research
● 468 papers in training set
Top 5%
1.0%
26
Open Research Europe
○ 14 papers in training set
Top 0.1%
1.0%
27
Frontiers in Genetics
○ 230 papers in training set
Top 4%
1.0%
28
Bioinformatics Advances
◐ 203 papers in training set
Top 4%
1.0%
29
Peer Community Journal
● 281 papers in training set
Top 5%
1.0%
30
Molecular Biology and Evolution
◐ 542 papers in training set
Top 5%
0.8%

"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.