Back

KmerSV: a visualization and annotation tool for structural variants using Human Pangenome derived k-mers

Meng, Q.; Ji, H. P.; Lee, H.

2023-10-15 bioinformatics
10.1101/2023.10.11.561941 bioRxiv
Show abstract

SummaryKmerSV is a visualization and annotation tool for structural variants (SVs). It can be applied to assembly contigs or long-read sequences. Using k-mers it rapidly generates images and provides genome features of SVs. As an important feature, it utilizes the new Human Pangenome reference which provide haploid specific assemblies, addresses limitations in prior references and improves the discovery of SVs. Availability and implementationKmerSV is implemented in Python and available at github.com/sgtc-stanford/kmerSV

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
Bioinformatics
◐ 1061 papers in training set
Top 0.4%
39.2%
2
BMC Bioinformatics
○ 383 papers in training set
Top 0.5%
14.3%
50% of probability mass above
3
Bioinformatics Advances
◐ 184 papers in training set
Top 0.2%
8.4%
4
Journal of Open Source Software
● 22 papers in training set
Top 0.1%
6.3%
5
GigaScience
◐ 172 papers in training set
Top 0.4%
4.1%
6
Nucleic Acids Research
◐ 1128 papers in training set
Top 6%
3.6%
7
Genome Biology
○ 555 papers in training set
Top 3%
3.1%
8
PLOS Computational Biology
● 1633 papers in training set
Top 15%
1.8%
9
Database
◐ 51 papers in training set
Top 0.4%
1.8%
10
PLOS ONE
● 4510 papers in training set
Top 55%
1.7%
11
NAR Genomics and Bioinformatics
◐ 214 papers in training set
Top 2%
1.5%
12
Frontiers in Genetics
○ 197 papers in training set
Top 6%
1.3%
13
Scientific Reports
○ 3102 papers in training set
Top 71%
0.9%
14
F1000Research
○ 79 papers in training set
Top 4%
0.8%
15
Briefings in Bioinformatics
◐ 326 papers in training set
Top 7%
0.7%
16
BioData Mining
○ 15 papers in training set
Top 0.9%
0.7%
17
Nature Communications
○ 4913 papers in training set
Top 64%
0.7%
18
Nature Methods
○ 336 papers in training set
Top 7%
0.6%