Introduction to Hematology Land Content

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Contents

Hematology_B37

OncoLand Hematology is a collection of data sets related to blood related cancers, including Myelodysplastic Syndrome (MDS), Multiple Myeloma (MM), Chronic Myeloid Leukemia (CML), Chronic Lymphocytic Leukemia, Acute Myeloid Leukemia (LAML), and Acute Lymphocytic Leukemia (ALL).

Data Source

Hematology Land data are from multiple MM studies, including from GEO and Multiple Myeloma Genomics Portal (MMGP): MMPG

Land Version Genome Build Gene Model
Hematology_B37 Human.B37.3 OmicsoftGene20130723

Data Type

  • CNV
  • DNA-Seq Somatic Mutation
  • DNA-Seq Mutation
  • Expression Intensity Probes (Affymetrix)
  • RNA-Seq, including:
    • Single-end and Paired-end fusion calling
    • RNA-Seq mutation
    • Exon Junction and Exon Usage
    • Expression (Gene- and Transcript- level quantification)


Laboratory Methods

Affymetrix Expression Arrays

Illumina HiSeq RNA sequencing

Agilent aCGH Arrays

Agilent SureSelect exome captures

Processing Methods

Expression Data: Omicsoft Affymetrix Microarray Preprocessing

RNA-Seq data: OmicScript Pipeline and Building Land From RNA-Seq Data

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

Key Meta Data Columns

  • DiseaseState (controlled vocabulary) : Curated at sample level from each project.
  • Land Tissue: The tissue from which the cell line was derived, using OmicSoft's curation Controlled Vocabulary
  • TissueCategory (controlled vocabulary) : Tissue category such as skin, muscle, heart, kidney etc.
  • 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.

Primary Grouping

HematologyLand samples are grouped by DiseaseState:

Hematology samples.png

Key Views

Gene Expression

A common way to examine gene expression levels is the GeneFPKM view. Here, users can browse expression and group using sample meta data or other genomic features, such as mutation or copy number variation status. In this example, SOX11 expression is shown, with samples grouped by IGHV mutation status:

SOX11ExpressionGroupbyMutationStatusIGHV.png

SOX11 gene expression levels grouped by IGHV mutation status in mantle cell lymphoma (MCL) samples shows that IGHV-negative samples have significantly higher SOX11 expression.
It suggests a correlation between IGHV mutations and SOX11 expression in MCL. A similar result was shown in an article in Cancer Research: Navarro, Alba et al. "Molecular subsets of mantle cell lymphoma defined by the IGHV mutational status and SOX11 expression have distinct biologic and clinical features." Cancer research 72.20 (2012): 5307-5316.
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