注：僅僅取用文章中我認(rèn)為重要的部分做出翻譯。

Choice of K

One question that arises when applying admixture models in practice is how to select the model complexity, or number of populations, K.
譯：實(shí)際中我們應(yīng)用admixture models時(shí)，會(huì)出現(xiàn)一個(gè)問題，那就是如何去選擇the model complexity(即群體數(shù)目)K。
It is important to note that in practice there will generally be no “true” value of K, because samples from real populations will never conform exactly to the assumptions of the model.
譯：需要重點(diǎn)注意的是，在實(shí)踐中，通常不會(huì)有“真實(shí)”的K值，因?yàn)檎鎸?shí)群體中的樣本永遠(yuǎn)不會(huì)符合模型的假設(shè)。(應(yīng)該說模型假設(shè)永遠(yuǎn)不會(huì)與群體真實(shí)情況一致)
Further, inferred values of K could be influenced by sampling ascertainment schemes (Engelhardt and Stephens 2010)(imagine sampling from g distinct locations in a continuous habitat exhibiting isolation by distance—any automated approach to select K will be influenced by g),and by the number of typed loci (as more loci are typed, more subtle structure can be picked up, and inferred values of K may increase).
譯：此外，抽樣方案也會(huì)影響K值的推斷(想象一下，依據(jù)距離從一個(gè)連續(xù)的生態(tài)環(huán)境中g(shù)個(gè)不同的地點(diǎn)取樣，而這些地點(diǎn)個(gè)體都是存在隔離的--任何自動(dòng)選擇K的方法都會(huì)受g的影響)，輸入基因座的數(shù)量也會(huì)影響K值的推斷(隨著輸入位點(diǎn)的增加，可能會(huì)尋找到更多精細(xì)的結(jié)構(gòu)，并且推斷出的K值也可能增加)。
Nonetheless, it can be helpful to have automated heuristic rules to help guide the analyst in making the appropriate choice for K, even if the resulting inferences need to be carefully interpreted within the context of prior knowledge about the data and sampling scheme.
譯：盡管如此，利用相應(yīng)的規(guī)則，自動(dòng)選擇出合適的K，這對分析人員還是有幫助的，即使還需要在有關(guān)數(shù)據(jù)和采樣方案的先驗(yàn)知識的背景下，仔細(xì)地解釋得出的結(jié)果。
Therefore, we here used simulation to assess several different heuristics for selecting K.
譯：因此，我們利用模擬數(shù)據(jù)去評估幾種選擇K的方法。