Using RNA-Seq Data to Predict Large-scale Copy-number Alterations in AML

Group project for STAT540, Winter 2014.

Overview

Here is a general diagram of our workflow:

Project Proposal

• Proposal: here

Inputs

• RPKM data: here
• Patient metadata: here

Poster

• Poster pdf: here
• Poster text: here
• Poster figures: here
• Poster tables: here

Analysis scripts

• All code: here

Bibliography

1. National Comprehensive Cancer Network (2014). NCCN Clinical Practice Guidelines in Oncology - Acute Myeloid Leukemia. Version 2. NCCN

2. Grimwade, D et al. (2010). Refinement of cytogenetic classi�cation in acute myeloid leukemia: determination of prognostic signi�cance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood. Jul 22;116(3):354-65. PubMed

3. Prebet, T et al. (2004). Secondary Philadelphia chromosome after non-myeloablative peripheral blood stem cell transplantation for a myelodysplastic syndrome in transformation. Bone Marrow Transplantation. Jan;33(2):247-9. PubMed

4. The Cancer Genome Atlas Research Network (2013). Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia. New England Journal of Medicine. May 30;368(22):2059-74.PubMed

5. Law, CW et al. (2014). Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biology. Feb 3;15(2):R29. PubMed