Name: | Alias:

Cellosaurus RRID: | COSMIC ID: | Cell Model Passport: | DepMap ID: | CCLE Name:

Source: | Catalogue:

Overview

Basic Information

Disease: | Disease subtype: | Details:

Lineage: | Lineage Subtype: | Lineage Sub-subtype: | Lineage molecular subytype:

Gender: | Age at sampling:

Sample collection site: | Tissue status:

Culture type: | Culture medium:

Cell Culture Images
Model Genomics

HLA:

MSI:

ploidy_snp6:

ploidy_wes:

ploidy_wgs:

Viral infection :

Data availability:

STR Markers

Genomics

1.Visualize genomics information including mRNA expression, mutations, copy number alterations, gene fusions, etc.

2.Driver Genes provides an overview of cancer driver gene status in the query model.

3.In All Genes, you can search for genes of interest.

Note: Displays genes acting as cancer drivers in this model.

Mutations (Driver Gene Method of Action)
Gain of function
Loss of function
Ambiguous Function
Fusion

Copy Number Alterations (CN Call)
Amplification of a driver gene (CN>=4.0)
Loss/Deletion of a driver gene (CN<=0.5)

Gene Fusion
Gene fusion


Legend: For mutations, font size is proportional to mutation frequency ranging from 0.05 to 1. For CNA, font size is inversely proportional to CN if CN <=0.5 and is proportional to CN if CN>=4.0. For gene fusions, font size is always 1. When a gene has both mutation and CNA, the mutation color coding and font size are used.
Mutation types are as follows:
  • Missense_Mutation(putative driver)
  • Frame_Shift_Del(unknown significance)
  • Frame_Shift_Ins(putative driver): Nonsense, Nonstop, Frameshift deletion, Frameshift insertion, Splice site
  • In_Frame_Del(unknown significance): Nonsense, Nonstop, Frameshift deletion, Frameshift insertion, Splice site
  • In_Frame_Ins(putative driver): Inframe deletion, Inframe insertion
  • Nonsense_Mutation(putative driver)
  • Nonstop_Mutation(putative driver)
  • Splice_Site(putative driver)
  • Start_Codon_SNP(putative driver)

Pharmacology

Visualization of pharmacological data collected from various reference databases. You can select one source for data visualization. Drug efficacy is represented by IC50 and AUC for in vitro CTG assays.

Select source:

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Analytics

1.Overview of models based on gene expression landscape, visualized through UMAP analysis of the entire transcriptome.

2.Genetic Analysis shows: (a) the query model's genome ancestry; (b) its genetic similarity to other models, with highly identical ones marked in red; (c) the variant allele frequency (VAF) by cancer type.

3.Efficacy Similarity identifies models with drug response patterns highly similar to the query model.

4.Pathway Activation highlights pathways that are either highly activated or suppressed in the query model.

Select source:

Pathway status:

Pathway database:

Ranking metascore (descending) in all cell lines:

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