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HPC-based genome variant calling workflow (HPC-GVCW)

Zhou, Y.; Kathiresan, N.; Yu, Z.; Rivera, L. F.; Thimma, M.; Manickam, K.; Chebotarov, D.; Mauleon, R.; Chougule, K.; Wei, S.; Gao, T.; Green, C. D.; Zuccolo, A.; Zhang, J.; Ware, D.; McNally, K. L.; Wing, R. A.

2023-06-26 genomics
10.1101/2023.06.25.546420 bioRxiv
Show abstract

A high-performance computing genome variant calling workflow was designed to run GATK on HPC platforms. This workflow efficiently called an average of 27.3 M, 32.6 M, 168.9 M, and 16.2 M SNPs for rice, sorghum, maize, and soybean, respectively, on the most recently released high-quality reference sequences. Analysis of a rice pan-genome reference panel revealed 2.1 M novel SNPs that have yet to be publicly released.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 7%
21.5%
Similar papers in this journal
2
Genome Biology
○ 637 papers in training set
Top 1%
8.7%
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3
Cell Genomics
○ 172 papers in training set
Top 0.5%
6.6%
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4
Communications Biology
○ 993 papers in training set
Top 1.0%
6.6%
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5
Nature Genetics
○ 286 papers in training set
Top 1%
5.4%
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6
Nature Plants
○ 94 papers in training set
Top 0.5%
5.0%
50% of probability mass above
7
Nature Computational Science
○ 55 papers in training set
Top 0.1%
4.7%
8
Nature Methods
○ 385 papers in training set
Top 2%
4.7%
9
Scientific Data
○ 209 papers in training set
Top 0.7%
3.4%
10
GigaScience
◐ 212 papers in training set
Top 1%
3.2%
11
Scientific Reports
○ 3612 papers in training set
Top 35%
3.0%
12
Molecular Plant
○ 39 papers in training set
Top 0.5%
2.4%
13
Nature Biotechnology
○ 172 papers in training set
Top 3%
1.6%
14
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 3%
1.4%
15
Briefings in Bioinformatics
◐ 354 papers in training set
Top 5%
1.3%
16
Journal of Genetics and Genomics
○ 38 papers in training set
Top 0.5%
1.1%
17
Bioinformatics
◐ 1204 papers in training set
Top 8%
1.1%
18
Human Genetics and Genomics Advances
○ 84 papers in training set
Top 2%
1.0%
19
Plant Biotechnology Journal
○ 64 papers in training set
Top 1%
1.0%
20
Molecular Biology and Evolution
◐ 542 papers in training set
Top 5%
1.0%
21
eLife
● 5828 papers in training set
Top 64%
1.0%
22
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 42%
0.8%
23
Nature
○ 645 papers in training set
Top 11%
0.8%
24
Genome Research
● 468 papers in training set
Top 7%
0.6%
25
Plant Communications
○ 36 papers in training set
Top 1%
0.6%
26
Horticulture Research
◐ 47 papers in training set
Top 1%
0.6%
27
iScience
○ 1154 papers in training set
Top 42%
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.