EUPAN enables pan-genome studies of a large number of eukaryotic genomes
Pan-genome analyses are routinely carried out for bacteria to interpret the within-species
gene presence/absence variations (PAVs). However, pan-genome analyses are rare for
eukaryotes due to the large sizes and higher complexities of their genomes. Here we
proposed EUPAN, a eukaryotic pan-genome analysis toolkit, enabling automatic large-scale
eukaryotic pan-genome analyses and detection of gene PAVs at a relatively low sequencing
depth. In the previous studies, we demonstrated the effectiveness and high accuracy of …
gene presence/absence variations (PAVs). However, pan-genome analyses are rare for
eukaryotes due to the large sizes and higher complexities of their genomes. Here we
proposed EUPAN, a eukaryotic pan-genome analysis toolkit, enabling automatic large-scale
eukaryotic pan-genome analyses and detection of gene PAVs at a relatively low sequencing
depth. In the previous studies, we demonstrated the effectiveness and high accuracy of …
Summary
Pan-genome analyses are routinely carried out for bacteria to interpret the within-species gene presence/absence variations (PAVs). However, pan-genome analyses are rare for eukaryotes due to the large sizes and higher complexities of their genomes. Here we proposed EUPAN, a eukaryotic pan-genome analysis toolkit, enabling automatic large-scale eukaryotic pan-genome analyses and detection of gene PAVs at a relatively low sequencing depth. In the previous studies, we demonstrated the effectiveness and high accuracy of EUPAN in the pan-genome analysis of 453 rice genomes, in which we also revealed widespread gene PAVs among individual rice genomes. Moreover, EUPAN can be directly applied to the current re-sequencing projects primarily focusing on single nucleotide polymorphisms.
Availability and Implementation
EUPAN is implemented in Perl, R and C ++. It is supported under Linux and preferred for a computer cluster with LSF and SLURM job scheduling system. EUPAN together with its standard operating procedure (SOP) is freely available for non-commercial use (CC BY-NC 4.0) at http://cgm.sjtu.edu.cn/eupan/index.html.
Supplementary information
Supplementary data are available at Bioinformatics online.
Oxford University Press
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