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rhAmpSeq Sample ID Panel

Easy, reliable human sample identification in targeted sequencing workflows

The rhAmpSeq Sample ID Panel is a high-performance, easy-to-use solution for tracking and managing human samples in NGS analysis workflows. With 76 polymorphic target SNPs, including 5 gender markers, this panel provides discrimination power greater than 1 in 25 million.

  • Ensure correct sample identity in your human DNA sample workflows
  • Quickly generate highly reproducible targeted sequencing data
  • Work confidently with difficult sample inputs, including formalin-fixed paraffin-embedded (FFPE) DNA and cell-free DNA (cfDNA)


To complete your rhAmpSeq workflow, you will also need the rhAmpSeq Library Kit and rhAmpSeq Index Primers. Additional details about the rhAmpSeq workflow can be found on the overview page.

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 that are used in our xGen Human ID Research Panel and that 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.

Technical details

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 sitesProbability 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.

ConsiderationsRegular protocolHigh-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 hr1–1.5 hr
Total workflow time*4–6 hr4–4.5 hr
* Estimated time to process 12–96 samples using manual pipetting, including reaction setup, cleanup, library quantification, and normalization steps

Robust, reproducible on-target rates and uniform coverage

The rhAmpSeq Sample ID Panel has been developed for maximum on-target specificity and coverage uniformity to enable generating SNP allele calls across a broad range of sample types and inputs.

Figure 1. Robust, reproducible on-target rates and uniform coverage is independent of input amount and users. Multiple Coriell samples were tested using the high-throughput protocol by 2 users at both 10 and 50 ng of input DNA (138 replicates per user per input condition). (Top) 100% of test replicates demonstrated on-target levels >90%. (Bottom) 99.6% of test replicates showed excellent coverage uniformity: >85% of targets (excluding gender markers) have ≥0.2X average target coverage.

Useful for challenging sample input types

We have also tested the rhAmpSeq Sample ID Panel on donor tissue inputs, including FFPE DNA and cfDNA samples. Figure 2 shows example data obtained using the regular rhAmpSeq library preparation protocol and samples from 5 donors, while Table 3 presents genotype concordance rates of these samples. As is always the case when working with challenging sample input types, please note that greater variations in performance are possible, and your results may vary.

Figure 2. Example rhAmpSeq Sample ID Panel performance with difficult sample types. DNA was isolated from 3 sources (cfDNA from plasma, gDNA from FFPE lung tumor tissue, and gDNA from adjacent normal cells) for each of 5 different donors. All samples were processed using DNA inputs from 1–5 ng according to the regular rhAmpSeq library preparation protocol. Shown are the percentage of mapped reads, percentage of on-target reads, coverage uniformity between assays (percentage of assays with coverage ≥0.2X of mean assay coverage), and assay call rate.

Table 3. Genotype concordance rates. Within an individual donor (i.e., Donors 1–5 from Figure 2), the concordance rates between the same DNA types (FFPE, gDNA, and cfDNA) were ≥98%.

FFPE = FFPE gDNA (lung tumor), gDNA = gDNA (adjacent normal), cfDNA = cfDNA (plasma).

Panel information

The target file contains SNP targets for the assays. The assay file includes locus-specific primer information. The insert file does not include primers in the BED coordinates.

rhAmpSeq Sample ID Panel for hg19

rhAmpSeq Sample ID Panel for hg38 (GRCh38)

User guides and protocols

Sample data

For more information, refer to the analysis guidelines in the User guides and protocols section.

Brochure and flyers

Frequently asked questions

Certificates of analysis (COAs)

Find COAs by batch or lot number