Automated Author ProfileErickson, Shay F.
University of North Dakota
Erickson, Shay F.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.8 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
High-throughput sequencing has been proposed as a method to genotype microsatellites and overcome the four main technical drawbacks of capillary electrophoresis: amplification artifacts, imprecise sizing, length homoplasy, and limited multiplex capability. The objective of this project was to test a high-throughput amplicon sequencing approach to fragment analysis of short tandem repeats and characterize its advantages and disadvantages against traditional capillary electrophoresis. We amplified and sequenced 12 muskrat microsatellite loci from 180 muskrat specimens and analyzed the sequencing data for precision of allele calling, propensity for amplification or sequencing artifacts, and for evidence of length homoplasy. Of the 294 total alleles, we detected by sequencing, only 164 alleles would have been detected by capillary electrophoresis as the remaining 130 alleles (44%) would have been hidden by length homoplasy. The ability to detect a greater number of unique alleles resulted in the ability to resolve greater population genetic structure. The primary advantages of fragment analysis by sequencing are the ability to precisely size fragments, resolve length homoplasy, multiplex many individuals and many loci into a single high-throughput run, and compare data across projects and across laboratories (present and future) with minimal technical calibration. A significant disadvantage of fragment analysis by sequencing is that the method is only practical and cost-effective when performed on batches of several hundred samples with multiple loci. Future work is needed to optimize throughput while minimizing costs and to update existing microsatellite allele calling and analysis programs to accommodate sequence-aware microsatellite data.
Authors
- Darby, Brian J. ;
- Erickson, Shay F. ;
- Hervey, Samuel D. ;
- Ellis-Felege, Susan N.