The rhAmpSeq Sample ID Panel consists of 76 unique
rhAmp primer pairs in a single tube to amplify corresponding SNP markers for accurate sample tracking and identification in targeted sequencing workflows. These are the same highly polymorphic SNPs used in our xGen Human ID Research Panel that, together, are capable of identifying a unique individual within a population of more than 25 million biological samples.
This panel has been tested on genomic DNA (gDNA), FFPE, and cfDNA input samples, and has been optimized for coverage uniformity and on-target specificity, as shown in the Performance section below.
The rhAmpSeq Sample ID Panel provides high discrimination power for worry-free sample tracking to avoid sample swaps or mix-ups during processing. Our computational models below (Table 1) show the probabilities of any 2 samples sharing the same genotypes
across a number of SNP sites (simulated from a Korean population).
Table 1. Calculated chances that any 2 people share genotypes across a given number of sites (out of 71 sites).
|Number of sites||Probability of shared genotype (out of 25 million simulations)|
|*None observed in 25M simulations|
The rhAmpSeq Sample ID Panel is compatible with both the regular and high-throughput rhAmpSeq library preparation protocols. Therefore, you can choose the best workflow for each experiment without having to buy different reagents. Table 2 summarizes our
observations regarding the respective performance attributes of each protocol. However, your results may vary—contact Application Support for more information.
Table 2. Choose the best rhAmpSeq library preparation protocol for your needs.
* Estimated time to process 12–96 samples using manual pipetting, including reaction setup, cleanup, library quantification, and normalization steps
|Considerations||Regular protocol||High-throughput protocol|
|Better sample-to-sample coverage uniformity||✔|| |
|Better performance with challenging sample types (e.g., FFPE, cfDNA)||✔|| |
|Ideal for high-throughput screening labs|| ||✔|
|No library quantification and normalization required|| ||✔|
|Hands-on time*||2.5–4.5 hr||1–1.5 hr|
|Total workflow time*||4–6 hr||4–4.5 hr|