HRA006132
Title:
ITDFinder: Detecting and quantifying FLT3-ITD based on clustering and random forest algorithm
Release date:
2023-11-30
Description:
We developed a software called ITDFinder that uses the clustering of candidate mutant reads, which encompass soft-clip, hard-clip and insertion in cigar string ,to ensure qualitative accuracy. Additionally, random forest regression model was performed to correct the quantitative result. This ensures the qualitative and quantitative precision of FLT3-ITD detection as demanded in clinical practice.
Data Accessibility:   
Controlled access Request Data
BioProject:
Study type:
Disease Study
Disease name:
acute myeloid leukemia
Data Access Committee

For each controlled access study, there is a corresponding Data Access Committee(DAC) to determine the access permissions. Access to actual data files is not managed by NGDC.


DAC NO.:
DAC name:
ITDFinder
Contact person:
Qin Jiayue
Email:
jyqin@live.cn
Description:
ITDFinder: Detecting and quantifying FLT3-ITD based on clustering and random forest algorithm
Individuals & samples
Submitter:   Qin Jiayue / jyqin@live.cn
Organization:   Acornmed Biotechnology Co., Ltd.
Submission date:   2023-11-29
Requests:   -