Introduction to CCLE Land Content

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*16S Microbial data: [http://www.arrayserver.com/wiki/index.php?title=ServerDataMatrix.16SMicrobial.Variable Bacterial counts from 16S rRNA]
 
*16S Microbial data: [http://www.arrayserver.com/wiki/index.php?title=ServerDataMatrix.16SMicrobial.Variable Bacterial counts from 16S rRNA]
  
HLA (Class I) identification using the RnaSeq aligned reads. The HLA OptiType program aligns RNA-seq reads to the HLA Reference genome, and then performs an optimization to determine the most likely HLA Class I allele. See [[file:OptiType - precision HLA typing from next-generation sequencing data.pdf]] for a description of the algorithm.
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HLA (Class I) identification using the RnaSeq aligned reads. The HLA OptiType program aligns RNA-seq reads to the HLA Reference genome, and then performs an optimization to determine the most likely HLA Class I allele. See [[OptiType - precision HLA typing from next-generation sequencing data.pdf]] for a description of the algorithm.
  
 
Omicsoft does not reprocess other genomic data, but extracts data directly from original datasets.
 
Omicsoft does not reprocess other genomic data, but extracts data directly from original datasets.

Revision as of 11:46, 14 April 2020


Contents

CCLE_B37 and CCLE_B38

The Cancer Cell Line Encyclopedia (CCLE) project is an effort to conduct a detailed genetic characterization of a large panel of human cancer cell lines. OmicSoft's CCLE_B37 Land release provides analysis and visualization of DNA copy number, mRNA expression, mutation data and more, for 1000 cancer cell lines. These data can also provide the link between pharmacologic vulnerabilities and genomic/expression patterns, with Land Measurement Queries.

Land Version Genome Build Gene Model
CCLE_B37 Human.B37.3 OmicsoftGene20130723
CCLE_B38 Human.B38 OmicsoftGenCode_V24

CCLE_DepMap_Preview_B37 and CCLE_DepMap_Preview_B38

Starting with the 2019R3 release, we integrated DepMap CRISPR and RNAi dependency data into CCLE Lands, which can be found in CCLE_DepMap_Preview_B37 and CCLE_DepMap_Preview_B38.

Data Source

CCLE DepMap

Data Types

  • CNV, based on segmented CNV files (downloaded)
  • CNV Call, GISTIC2 calls
  • DNASeq_Mutation
  • DNASeq_Mutation_Exome
  • Expression Intensity Probes (Affymetrix)
  • RNA-Seq, including:
    • Single-end and Paired-end fusion calling
    • RNA-Seq somatic mutation, from matched tumor/normal pairs
    • Exon Junction and Exon Usage
    • Expression (Gene- and Transcript- level quantification)
  • Gene Dependency (CCLE_DepMap_Preview)
    • CRISPR
    • RNAi

Laboratory Methods

  • Affymetrix Expression Array (Affymetrix.HG-U133_Plus_2)
  • Illumina HiSeq RNA sequencing (HiSeq 2000)
  • Hybrid capture sequencing

Processing Methods

Expression Data: Omicsoft Affymetrix Microarray Preprocessing

RNA-Seq data: OmicScript RNAseq Pipeline and Building Lands From RNA-Seq Data

HLA (Class I) identification using the RnaSeq aligned reads. The HLA OptiType program aligns RNA-seq reads to the HLA Reference genome, and then performs an optimization to determine the most likely HLA Class I allele. See OptiType - precision HLA typing from next-generation sequencing data.pdf for a description of the algorithm.

Omicsoft does not reprocess other genomic data, but extracts data directly from original datasets.

  • CRISPR data: Achilles Gene Effect (2019R3)
  • RNAi data: DEMETER2 Data v5 (combined)

Key Meta Data Columns

  • Primary Site: The body site where the cell line sample is derived from.
  • Histology: Histological types of cancer, such as carcinoma, glioma and sarcoma.
  • Land Tissue: The tissue from which the cell line was derived, using OmicSoft's curation Controlled Vocabulary
  • Land Sample Type: A detailed description of the cell type from which the cell line was derived, using OmicSoft's curation Controlled Vocabulary
  • Tumor or Normal: Indicates whether a sample is from a tumor or normal sample.
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Primary Grouping

Primary Site

Sample Distribution by Primary Site

CCLESampleDistribution.png

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Key Views

Gene Expression

One of the most common ways to visualize gene expression data is a per-sample Scatter plot (e.g. Gene FPKM), with each sample grouped by Primary Site on the Y-axis, and expression level plotted on the X-axis:

GeneFPKMforEGFRCCLE.png

Additional Views include transcript-level and exon-level views, pairwise comparison plots, and direct visualization of RNAseq coverage with the OmicSoft Genome Browser.

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DNA Mutation

Multiple visualizations display frequency and locations of gene mutations in CCLE samples, including the Mutation Landscape View.

DNAMutationCCLE.png

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Copy Number Variation

Copy number data can be visualized for a gene of interest, grouped by any metadata column, such as Histology.

CNV BRAF CCLE.png


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Related Articles

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