PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator

Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain....
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Liran Juan [verfasserIn] Yongtian Wang [verfasserIn] Jingyi Jiang [verfasserIn] Qi Yang [verfasserIn] Qinghua Jiang [verfasserIn] Yadong Wang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	personal genome genome simulation variant simulation genome variation computational tools

Übergeordnetes Werk:	In: Frontiers in Bioengineering and Biotechnology - Frontiers Media S.A., 2014, 8(2020)
Übergeordnetes Werk:	volume:8 ; year:2020

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fbioe.2020.00028

Katalog-ID:	DOAJ012825654

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520			\|a Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim.
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allfields	10.3389/fbioe.2020.00028 doi (DE-627)DOAJ012825654 (DE-599)DOAJ3aa25f1d318f4752aa94f3f2d0e96987 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Liran Juan verfasserin aut PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim. personal genome genome simulation variant simulation genome variation computational tools Biotechnology Yongtian Wang verfasserin aut Jingyi Jiang verfasserin aut Qi Yang verfasserin aut Qinghua Jiang verfasserin aut Yadong Wang verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 8(2020) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:8 year:2020 https://doi.org/10.3389/fbioe.2020.00028 kostenfrei https://doaj.org/article/3aa25f1d318f4752aa94f3f2d0e96987 kostenfrei https://www.frontiersin.org/article/10.3389/fbioe.2020.00028/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020
spelling	10.3389/fbioe.2020.00028 doi (DE-627)DOAJ012825654 (DE-599)DOAJ3aa25f1d318f4752aa94f3f2d0e96987 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Liran Juan verfasserin aut PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim. personal genome genome simulation variant simulation genome variation computational tools Biotechnology Yongtian Wang verfasserin aut Jingyi Jiang verfasserin aut Qi Yang verfasserin aut Qinghua Jiang verfasserin aut Yadong Wang verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 8(2020) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:8 year:2020 https://doi.org/10.3389/fbioe.2020.00028 kostenfrei https://doaj.org/article/3aa25f1d318f4752aa94f3f2d0e96987 kostenfrei https://www.frontiersin.org/article/10.3389/fbioe.2020.00028/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020
allfields_unstemmed	10.3389/fbioe.2020.00028 doi (DE-627)DOAJ012825654 (DE-599)DOAJ3aa25f1d318f4752aa94f3f2d0e96987 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Liran Juan verfasserin aut PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim. personal genome genome simulation variant simulation genome variation computational tools Biotechnology Yongtian Wang verfasserin aut Jingyi Jiang verfasserin aut Qi Yang verfasserin aut Qinghua Jiang verfasserin aut Yadong Wang verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 8(2020) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:8 year:2020 https://doi.org/10.3389/fbioe.2020.00028 kostenfrei https://doaj.org/article/3aa25f1d318f4752aa94f3f2d0e96987 kostenfrei https://www.frontiersin.org/article/10.3389/fbioe.2020.00028/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020
allfieldsGer	10.3389/fbioe.2020.00028 doi (DE-627)DOAJ012825654 (DE-599)DOAJ3aa25f1d318f4752aa94f3f2d0e96987 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Liran Juan verfasserin aut PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim. personal genome genome simulation variant simulation genome variation computational tools Biotechnology Yongtian Wang verfasserin aut Jingyi Jiang verfasserin aut Qi Yang verfasserin aut Qinghua Jiang verfasserin aut Yadong Wang verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 8(2020) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:8 year:2020 https://doi.org/10.3389/fbioe.2020.00028 kostenfrei https://doaj.org/article/3aa25f1d318f4752aa94f3f2d0e96987 kostenfrei https://www.frontiersin.org/article/10.3389/fbioe.2020.00028/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020
allfieldsSound	10.3389/fbioe.2020.00028 doi (DE-627)DOAJ012825654 (DE-599)DOAJ3aa25f1d318f4752aa94f3f2d0e96987 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Liran Juan verfasserin aut PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim. personal genome genome simulation variant simulation genome variation computational tools Biotechnology Yongtian Wang verfasserin aut Jingyi Jiang verfasserin aut Qi Yang verfasserin aut Qinghua Jiang verfasserin aut Yadong Wang verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 8(2020) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:8 year:2020 https://doi.org/10.3389/fbioe.2020.00028 kostenfrei https://doaj.org/article/3aa25f1d318f4752aa94f3f2d0e96987 kostenfrei https://www.frontiersin.org/article/10.3389/fbioe.2020.00028/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020
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authorswithroles_txt_mv	Liran Juan @@aut@@ Yongtian Wang @@aut@@ Jingyi Jiang @@aut@@ Qi Yang @@aut@@ Qinghua Jiang @@aut@@ Yadong Wang @@aut@@
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callnumber-first	T - Technology
author	Liran Juan
spellingShingle	Liran Juan misc TP248.13-248.65 misc personal genome misc genome simulation misc variant simulation misc genome variation misc computational tools misc Biotechnology PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator
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topic_title	TP248.13-248.65 PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator personal genome genome simulation variant simulation genome variation computational tools
topic	misc TP248.13-248.65 misc personal genome misc genome simulation misc variant simulation misc genome variation misc computational tools misc Biotechnology
topic_unstemmed	misc TP248.13-248.65 misc personal genome misc genome simulation misc variant simulation misc genome variation misc computational tools misc Biotechnology
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title	PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator
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title_full	PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator
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title_sort	pgsim: a comprehensive and highly customizable personal genome simulator
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title_auth	PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator
abstract	Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim.
abstractGer	Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim.
abstract_unstemmed	Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim.
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title_short	PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator
url	https://doi.org/10.3389/fbioe.2020.00028 https://doaj.org/article/3aa25f1d318f4752aa94f3f2d0e96987 https://www.frontiersin.org/article/10.3389/fbioe.2020.00028/full https://doaj.org/toc/2296-4185
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up_date	2024-07-03T14:14:58.029Z
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PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator

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