Defining Loci in Restriction-Based Reduced Representation Genomic Data from Nonmodel Species : Sources of Bias and Diagnostics for Optimal Clustering
المؤلفون المشاركون
Nydam, Marie L.
Hare, Matthew P.
Ilut, Daniel C.
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-06-25
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Next generation sequencing holds great promise for applications of phylogeography, landscape genetics, and population genomics in wild populations of nonmodel species, but the robustness of inferences hinges on careful experimental design and effective bioinformatic removal of predictable artifacts.
Addressing this issue, we use published genomes from a tunicate, stickleback, and soybean to illustrate the potential for bioinformatic artifacts and introduce a protocol to minimize two sources of error expected from similarity-based de-novo clustering of stacked reads: the splitting of alleles into different clusters, which creates false homozygosity, and the grouping of paralogs into the same cluster, which creates false heterozygosity.
We present an empirical application focused on Ciona savignyi, a tunicate with very high SNP heterozygosity (~0.05), because high diversity challenges the computational efficiency of most existing nonmodel pipelines while also potentially exacerbating paralog artifacts.
The simulated and empirical data illustrate the advantages of using higher sequence difference clustering thresholds than is typical and demonstrate the utility of our protocol for efficiently identifying an optimum threshold from data without prior knowledge of heterozygosity.
The empirical Ciona savignyi data also highlight null alleles as a potentially large source of false homozygosity in restriction-based reduced representation genomic data.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ilut, Daniel C.& Nydam, Marie L.& Hare, Matthew P.. 2014. Defining Loci in Restriction-Based Reduced Representation Genomic Data from Nonmodel Species : Sources of Bias and Diagnostics for Optimal Clustering. BioMed Research International،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-489567
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ilut, Daniel C.…[et al.]. Defining Loci in Restriction-Based Reduced Representation Genomic Data from Nonmodel Species : Sources of Bias and Diagnostics for Optimal Clustering. BioMed Research International No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-489567
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ilut, Daniel C.& Nydam, Marie L.& Hare, Matthew P.. Defining Loci in Restriction-Based Reduced Representation Genomic Data from Nonmodel Species : Sources of Bias and Diagnostics for Optimal Clustering. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-489567
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-489567
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر