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Solution Reagent Kit

Reference: 862545 Laboratory Medicine
ApplicationsFor Research, Blood Sample, For Pcr, Ngs, For Dna Sequencing, For Mutation Detection, Ffpe Tissues, For Cancers
Tested ParameterFor Genes
TypeSolution
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The AmpliSeq for Illumina Cancer Hotspot Panel v2 is a targeted resequencing assay that is designed to investigate somatic mutations in the hotspot regions of 50 genes that have been identified in the Catalogue of Somatic Mutations in Cancer (COSMIC)1 database. These genes are known to have associations with cancer. The primary characteristics are as follows:input:
output:Gene Content That Is RelevantTarget approximately 2800 COSMIC mutations from 50 oncogenes and tumor suppressor genes.Rapid, Efficient Processinput:
output:Sequencing-ready libraries can be generated in a single day from as few as 1 ng of high-quality or 10 ng of formalin-fixed, paraffin-embedded (FFPE) samples.Accurate Datainput:
output:Utilize local or cloud-based analysis to identify somatic mutations with a variant allele frequency of 5% or lower.input:
output:The Cancer HotSpot Panel is a component of an integrated workflow that encompasses automated analysis, Illumina sequencing by synthesis (SBS) next-generation sequencing (NGS) technology, and AmpliSeq for Illumina polymerase chain reaction (PCR)-based library preparation.input:
output:This panel enables the detection of highly sensitive variants in a variety of cancer types, such as lung, colon, breast, ovarian, melanoma, and prostate. The panel that is pre-configured for use saves you the time and effort required to identify targets, design primers, and optimize panels.input:
output:Detailsinput:
output:Assay time: 5 hours (library preparation only; does not include library quantification, normalization, or pooling time)input:
output:Cancer Type: Solid tumor, Pan-cancerinput:
output:Content specifications - Hotspot regions of 50 genes with known associations to cancerinput:
output:Description - Research on the hotspot regions of 50 cancer-related genes using somatic analysis.input:
output:Minimum 1.5 hours of hands-on experienceinput:
output:Input quantity: 1–100 ng (10 ng is recommended per pool)

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