Provjera procjene efektivne veličine populacije putem simuliranih genomskih podataka

master's thesis

• Title (english): Review of estimation of effective population size through simulated genetic data
• Author: Filip Soro
• Mentor: Maja Ferenčaković (mentor)
• Committee member: Maja Ferenčaković (predsjednik povjerenstva)
• Committee member: Vlatka Čubrić Čurik (član povjerenstva)
• Committee member: Ino Čurik (član povjerenstva)
• Committee member: Vladimir Brajković (član povjerenstva)
• Granter: University of Zagreb; Faculty of Agriculture; (Animal Science); Zagreb
• Defense date and country: 2019-09-30, Croatia

Abstract

Razvojem i dostupnošću sve većeg broja genetskih markera procjena efektivne veličine populacije (Ne) sve se češće vrši korištenjem informacije o vezanim genima. Rezultati pojedinih programskih paketa za procjenu efektivne veličine populacije nisu sukladni stoga će se u ovom radu simulirati genomski podatci i na njima izvršiti procjena efektivne veličine te tako utvrditi točnost procjene. Simulirano je 150 populacija s različitom efektivnom veličinom populacije (Ne=50, Ne=100, Ne=250, Ne=500 i... More Ne=1000) u programskom paketu AplhaSimR. Na svim populacijama je izvršena procjena Ne programskim paketom SNeP. Na rezultatima procjene su napravljene dvije grupe regresija i t-test. Rezultati t-testa su pokazali kako je SNeP procjena zadovoljavajuća za populacije s manjom Ne (do Ne=100), no rezultati regresija su pokazali kako je procjena nepouzdana za sve populacije, tj. pojavio se problem razlike između praktične i statističke značajnosti. Na temelju rezultata regresija se zaključilo da SNeP procjena efektivne veličine nije zadovoljavajuća za situacije gdje je potrebna velika preciznost. Less

Abstract (english)

With development and availability more and more genetic markers, estimation of effective population size (Ne) is done by using information on linked genes. The results of some programs for estimation of effective population size are not compatible so in this thesis genetic data will be simulated and on them effective population size will be estimated in order to determine the accuracy of estimation. 150 population was simulated with different effective size (Ne=50, Ne=100, Ne=250, Ne=500 and... More Ne=1000) in software AlphaSimR. On all populations effective population size was estimated in SNeP software. Two groups of regressions and t-test were performed on the results of estimation. The results of the t-test showed that SNeP estimation is satisfactory for population with lower Ne (up to Ne=100) but the results of regressions showed that estimation is unreliabe for all populations, ie. the problem of difference between practical and statistical signifiance showed up. On the basis of the results of the regressions it was concluded that SNeP estimation of effective population size was unreliabe for situations were great precision is needed. Less

• Keywords: efektivna veličina populacije; AlphaSimR; SNeP; simulirani podatci; neravnoteža vezanih gena
• Keywords (english): effective population size; AlphaSimR; SNeP; simulated data; linkage disequilibrium
• Language: croatian
• URN:NBN: urn:nbn:hr:204:543086
• Study programme: Title: Animal Genetics and Breeding; Study programme type: university; Study level: graduate; Academic / professional title: magistar/ magistra inženjer/inženjerka genetike i oplemenjivanja životinja (magistar/ magistra inženjer/inženjerka genetike i oplemenjivanja životinja)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Access restricted to students and staff of home institution
• Created on: 2019-11-18 10:38:56