Ny sökning
PVS0161
Genomic analyses with emphasis on single-step
This is a course on implementing genomic selection in animal breeding. The same approaches can be used in plant breeding, too. The course includes modeling in genomic analyses, introduction to genomic selection, genomic data simulation and manipulation, methods based on SNP estimation, genomic relationship, theory of single step BLUP and validation methods, and use of BLUPF90 family of programs and training exercises. The course aims to build is a strong understanding in application of methods. During the exercises the one can perform data preparation and evaluation of genetic parameters. The attenders are able to builds a personal portfolio in use of statistical methods to use in research work or in commitment of breeding programs. Course will be given by prof Ignacy Misztal, PhD and doc. Daniela Lourenco, PhD, from University of Georgia, USA, assisted by Sreten Andonov, PhD, SLU.
The course is characterized by a very strong connection to the breeding programs commitment. The course will last 5 days. In the morning there will be 4 hours of lectures: theoretical, demonstrations and case studies. Each day 4 hours exercises will be held where each participant will learn how to apply the method explained before in real analyses. A short explanatory course (up to 2 hours) will be given to participants a week before in order to setup their laptops to run programs on Linux server.
The course will include sections on Introduction to BLUPF90 family of programs (animal multiple trait, maternal and genomic models); introduction to genomic selection (basis of SNP data, simulation genomic data, data manipulation – bash scripting); methods based on SNP estimation – SNP BLUP, BayesX (genomic relationship matrices; GBLUP, GREML, GGIBBS); single step GBLUP (forming equations, quality control for G; validation methods), estimation SNP effects (weighted GBLUP and ssGBLUP, genome-wide association and p values, experience and future with ssGBLUP).
The course is designed on a way that it is compulsory attendance of participants. Remote participation in this course will not reach the goal - to make the participants independent in applying methods in
their future individual projects. The reasons for it are laying in the theoretical content of the course where attendees should follow derivations in matrix algebra, when it is difficult follow details if one is not physically present. Also, during the exercises practical tips and hints will be given in applying methods in software. By experience, software learning is much ease by direct interaction among trainers and participants. Finally, the course aims to be NOVA course meaning that it is compulsory participation, since one of the aim is also enhancing network among participants and trainers.
The course is characterized by a very strong connection to the breeding programs commitment. The course will last 5 days. In the morning there will be 4 hours of lectures: theoretical, demonstrations and case studies. Each day 4 hours exercises will be held where each participant will learn how to apply the method explained before in real analyses. A short explanatory course (up to 2 hours) will be given to participants a week before in order to setup their laptops to run programs on Linux server.
The course will include sections on Introduction to BLUPF90 family of programs (animal multiple trait, maternal and genomic models); introduction to genomic selection (basis of SNP data, simulation genomic data, data manipulation – bash scripting); methods based on SNP estimation – SNP BLUP, BayesX (genomic relationship matrices; GBLUP, GREML, GGIBBS); single step GBLUP (forming equations, quality control for G; validation methods), estimation SNP effects (weighted GBLUP and ssGBLUP, genome-wide association and p values, experience and future with ssGBLUP).
The course is designed on a way that it is compulsory attendance of participants. Remote participation in this course will not reach the goal - to make the participants independent in applying methods in
their future individual projects. The reasons for it are laying in the theoretical content of the course where attendees should follow derivations in matrix algebra, when it is difficult follow details if one is not physically present. Also, during the exercises practical tips and hints will be given in applying methods in software. By experience, software learning is much ease by direct interaction among trainers and participants. Finally, the course aims to be NOVA course meaning that it is compulsory participation, since one of the aim is also enhancing network among participants and trainers.
Kursplan och övrig information
Kursplan
PVS0161 Genomic analyses with emphasis on single-step, 2,0 Hp
Ämnen
HusdjursvetenskapUtbildningens nivå
ForskarnivåFörkunskapskrav
General entry requirements: at least MSc in Animal/Plant Science or participant in a residency program in veterinary science, animal/plant breeding or animal/plant genetics.Specific entry requirements: Participants are expected to have understanding of animal or plant breeding and statistics, and genetic evaluation, and to be familiar with mixed model equations and quantitative genetics. Familiarity with Linux / Unix environments is expected in lab exercises.
Mål
The course gives the student advanced knowledge in genomic selection theory and practical implementation in animal breeding. After completion of the course, the student could: - describe modalities of different approaches in genomic selection; - by simulation of genomic data mimic real animal breeding of different species; - perform single step in genomic analysis; - measure predictability and validate models; - apply quality control of genomic relationship; - estimate and use SNPs in genomic best linear unbiased prediction (GBLUP) and genome wide association (GWA)Innehåll
This is a course on implementing genomic selection in animal breeding. The same approaches can be used in plant breeding, too. The course includes modeling in genomic analyses, introduction to genomic selection, genomic data simulation and manipulation, methods based on SNP estimation, genomic relationship, theory of single step BLUP and validation methods, and use of BLUPF90 family of programs and training exercises. The course aims to build is a strong understanding in application of methods. During the exercises the one can perform data preparation and evaluation of genetic parameters. The attenders are able to builds a personal portfolio in use of statistical methods to use in research work or in commitment of breeding programs. Course will be given by prof Ignacy Misztal, PhD and doc. Daniela Lourenco, PhD, from University of Georgia, USA, assisted by Sreten Andonov, PhD, SLU. The course is characterized by a very strong connection to the breeding programs commitment. The course will last 5 days. In the morning there will be 4 hours of lectures: theoretical, demonstrations and case studies. Each day 4 hours exercises will be held where each participant will learn how to apply the method explained before in real analyses. A short explanatory course (up to 2 hours) will be given to participants a week before in order to setup their laptops to run programs on Linux server. The course will include sections on Introduction to BLUPF90 family of programs (animal multiple trait, maternal and genomic models); introduction to genomic selection (basis of SNP data, simulation genomic data, data manipulation – bash scripting); methods based on SNP estimation – SNP BLUP, BayesX (genomic relationship matrices; GBLUP, GREML, GGIBBS); single step GBLUP (forming equations, quality control for G; validation methods), estimation SNP effects (weighted GBLUP and ssGBLUP, genome-wide association and p values, experience and future with ssGBLUP). The course is designed on a way that it is compulsory attendance of participants. Remote participation in this course will not reach the goal - to make the participants independent in applying methods in their future individual projects. The reasons for it are laying in the theoretical content of the course where attendees should follow derivations in matrix algebra, when it is difficult follow details if one is not physically present. Also, during the exercises practical tips and hints will be given in applying methods in software. By experience, software learning is much ease by direct interaction among trainers and participants. Finally, the course aims to be NOVA course meaning that it is compulsory participation, since one of the aim is also enhancing network among participants and trainers.Ytterligare information
Each participant should bring a laptop with installed remote computing software (putty, SSH secure shell, MobaXterm or similar). Number of participant will be limited to 30 in order to ensure smooth run of their analysis during the exercises. Priority will be given to SLU students, then seniors, but if there will be interest can be offered to participants from other Nordic countriesAnsvarig institution/motsvarande
Institutionen för husdjursgenetik