Construction Of A Data Visualization Application And A Clinical Annotation Knowledge Database For Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia(ALL)is one of the common hematological malignancy diseases which is caused by accumulated genetic abnormalities in hematopoietic stem/progenitor cells and more prevalent in children.ALL demonstrates high genetic heterogeneity at the cytogenetic and molecular level including chromosome loss,translocations,inversions,and gene mutations.Due to a high heterogeneity of ALL,It is difficult to select individualized treatment.Thanks to recent advances in genomic technology,there has been a substantial amount of research on ALL,which provides the possibility for precision medicine in ALL.The comprehensive analysis of ALL data will be completed just through the simple interaction,which effectively shortens the distance between the terminal researchers and the ALL big data,and helps to release the value of the current huge data resource.Based on public data about ALL,along with information collected by text mining from open databases and papers,two knowledge bases are built using networking technology in this study.One of them is used for excavating and visualizing transcriptome data of ALL.With transcriptome data and survival data from 172 cases of B-ALL patients,this visual data knowledge base has been created and applied to real-time data analysis with customization parameters and drawing heat maps of gene expression profiles,comparison charts of differentially expressed genes,Circos plots of gene fusions,and heat maps of gene mutations.The other knowledge base is focused on gathering research about gene mutations and fusions frequently seen in ALL and related clinical annotation in order to assist clinical diagnosis and treatment.Referring to the cohort of genomic data from 1 223 ALL cases,a highly extendable ALL knowledge base for clinical reference is constructed by collecting web resources and text mining,which includes 246 entries of gene mutations and fusions related to ALL.Through curating such an ALL annotated knowledge base,it will provide a reference for the choice of treatment options for clinical doctors,and provide assistance for the application of “precise medical” in ALL.