DdPCR Gene Mutation Detection Kit

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Product Description

Tumor Gene Mutation Detection Kit (digital PCR method) is a series of kits that can quantitatively detect the frequency of human tumor gene mutations. Through the water-in-oil droplet digital PCR technology, the wild-type and mutant-specific primer probes are designed, and the target sequence is directly quantified according to the Poisson distribution principle through the proportion of positive droplets.


The kit contains ddPCR Supermix for Probes, primers, wild-type probes, mutant probes, positive controls and negative controls. It combines the superior product of Kebai Bio-molecular diagnostic reference materials with ddPCR probe primers to provide customers with Provide a more comprehensive and convenient ddPCR detection solution.


Applications

Tissues, slices, and blood DNA are mainly used as test samples to quantitatively detect the frequency of a certain gene mutation.


Product advantages

1. Wide coverage: it can be used for the detection of more than 250 different target gene loci

2. High sensitivity: the detection limit is as low as 0.1%

3. Wide range of applications: it can be used for different forms of sample detection such as: tissue, slice, blood DNA


Case show

Human EGFR Gene T790M Mutation Detection Kit (Digital PCR Method)

1. Accuracy

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Figure 1. Tested 3 weakly positive, moderately positive, and strongly positive reference samples, each repeated three times, the results were all T790M positive, and the positive coincidence rate was 100%.


2. Precision


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Figure 2. A weak positive reference product was tested 10 times with the same batch of kits, and the results were all positive for T790M, with a positive coincidence rate of 100% and a coefficient of variation of mutation frequency CV ≤ 30%, which was in line with expectations.


3. Detection limit


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Figure 3. Test LOD standard, repeated 20 times. The positive coincidence rate is ≥95%, which means that the concentration is the detection limit of the kit.


4. Linear


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Figure 4. Linear evaluation Y = 0.9386*X + 0.0023 R2=0.9984.


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