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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

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Related Experiment Video

Updated: May 9, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
13:24

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

CPAP: Cancer Panel Analysis Pipeline.

Po-Jung Huang1, Yuan-Ming Yeh, Ruei-Chi Gan

  • 1Bioinformatics Center, Chang Gung University, Taoyuan, Taiwan; Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan.

Human Mutation
|July 30, 2013
PubMed
Summary
This summary is machine-generated.

A new bioinformatics tool, the Cancer Panel Analysis Pipeline (CPAP), automates the analysis and visualization of multiple targeted sequencing datasets. This enables rapid comparative analysis for cancer marker tests and other clinical sequencing applications.

Keywords:
Circoscancer panelion torrenttarget sequencing

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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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Area of Science:

  • Bioinformatics
  • Genomics
  • Cancer Research

Background:

  • Targeted sequencing is increasingly used in clinical settings for cancer marker tests.
  • Existing bioinformatics tools lack capabilities for analyzing and visualizing multiple targeted sequencing datasets simultaneously.

Purpose of the Study:

  • To develop an automated pipeline for comparative analysis and visualization of multiple targeted sequencing datasets.
  • To address the need for efficient analysis of cancer panel sequencing data.

Main Methods:

  • Developed the Cancer Panel Analysis Pipeline (CPAP) using standard output files from variant calling software.
  • Utilized Circos for generating a circular diagram of Single Nucleotide Polymorphisms (SNPs) across samples.
  • Integrated an SQL database with multiple SNP-related databases (dbSNP, 1000 Genomes, COSMIC, dbNSFP) for additional SNP information.
  • Created a hyperlinked HTML table for interactive SNP filtering and identification.

Main Results:

  • CPAP successfully automates the comparative analysis of multiple targeted sequencing datasets.
  • The pipeline generates a visual distribution map of SNPs and an interactive HTML table for data exploration.
  • CPAP demonstrated high efficiency, completing the analysis of 500 datasets in just 17 minutes.

Conclusions:

  • CPAP provides an efficient and automated solution for analyzing multiple cancer panel sequencing datasets.
  • The developed pipeline can serve as a model for customized targeted sequencing projects.
  • This tool facilitates comparative analyses crucial for clinical sequencing and cancer marker discovery.