Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revision
Previous revision
Next revisionBoth sides next revision
gene_networks_inference [2018/12/14 15:34] – [Related work] admingene_networks_inference [2019/05/22 03:41] – [Data] admin
Line 43: Line 43:
   - 200 AML cases from TCGA (LAML dataset). Available data types include gene expression , DNA-methylation, CNV, mutation, etc. TCGA data moved to [[https://gdc-portal.nci.nih.gov/|GDC]] but DNA-methylation is not there. Instead, it can be retrieved from GDC Legacy Archive or the original [[https://tcga-data.nci.nih.gov/docs/publications/laml_2012/|paper]].   - 200 AML cases from TCGA (LAML dataset). Available data types include gene expression , DNA-methylation, CNV, mutation, etc. TCGA data moved to [[https://gdc-portal.nci.nih.gov/|GDC]] but DNA-methylation is not there. Instead, it can be retrieved from GDC Legacy Archive or the original [[https://tcga-data.nci.nih.gov/docs/publications/laml_2012/|paper]].
   - German [[https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37642|AMLCG]] 1999 provides microarray data of 562 AML samples.   - German [[https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37642|AMLCG]] 1999 provides microarray data of 562 AML samples.
-  - Papaemmanuil, Elli, et al. "Genomic classification and prognosis in acute myeloid leukemia." [[http://www.nejm.org/doi/full/10.1056/NEJMoa1516192#t=article|NEJM]] 374.23 (2016): 2209-2221. \\  The mutations of 111 genes in over **1,500 AML**  cases are reported. The authors used this information to classify cases into groups and showed these groups have different prognosis. I.,e., [[https://www.mskcc.org/sites/default/files/node/2246/documents/discrete-cpe.pdf|concordance]] (probability estimates) improves from 64% using only the European LeukemiaNet criteria to 71%. Using the alternative allele frequency, they estimated the time of occurrence for the driver mutations. The data are available through the links in the corresponding [[http://www.nature.com/ng/journal/v49/n3/full/ng.3756.html|Nature]] paper [[[:ng.3756.pdf?media=ng.3756.pdf|pdf]]]. Information on downloading these data is contained in the readme file found in genetwork:~/proj/genetwork/data/AML/gerstung/readme.txt. In particular, we have access to [[https://www.ebi.ac.uk/ega/studies/EGAS00001000275|EGAS00001000275]] through [[https://ega-archive.org/|EGA]] Archives. See [[:habils_lab_notebook|Habil's]] note on 2017/09/05 for more detail. Any member of Oncinfo Lab who touches (analyzes or views) these data from Sanger Institute must read and abide to the [[:sanger_data_agreement_2017-08-09.pdf?media=sanger_data_agreement_2017-08-09.pdf|agreement]].+  - Papaemmanuil, Elli, et al. "Genomic classification and prognosis in acute myeloid leukemia." [[http://www.nejm.org/doi/full/10.1056/NEJMoa1516192#t=article|NEJM]] 374.23 (2016): 2209-2221. \\  The mutations of 111 genes in over **1,500 AML**  cases are reported. The authors used this information to classify cases into groups and showed these groups have different prognosis. I.,e., [[https://www.mskcc.org/sites/default/files/node/2246/documents/discrete-cpe.pdf|concordance]] (probability estimates) improves from 64% using only the European LeukemiaNet criteria to 71%. Using the alternative allele frequency, they estimated the time of occurrence for the driver mutations. The data are available through the links in the corresponding [[http://www.nature.com/ng/journal/v49/n3/full/ng.3756.html|Nature]] paper [[:ng.3756.pdf?media=ng.3756.pdf|pdf]]]. Information on downloading these data is contained in the readme file found in genetwork:~/proj/genetwork/data/AML/gerstung/readme.txt. In particular, we have access to [[https://www.ebi.ac.uk/ega/studies/EGAS00001000275|EGAS00001000275]] through [[https://ega-archive.org/|EGA]] Archives. See [[:habils_lab_notebook|Habil's]] note on 2017/09/05 for more detail. Any member of Oncinfo Lab who touches (analyzes or views) these data from Sanger Institute must read and abide to the [[:sanger_data_agreement_2017-08-09.pdf?media=sanger_data_agreement_2017-08-09.pdf|agreement]].
   - RNA, DNA methylation, whole genome, etc. data of 960 (pediatric?) AML cases are available from [[https://ocg.cancer.gov/programs/target/acute-myeloid-leukemia|TARGET]] AML study.   - RNA, DNA methylation, whole genome, etc. data of 960 (pediatric?) AML cases are available from [[https://ocg.cancer.gov/programs/target/acute-myeloid-leukemia|TARGET]] AML study.
   - AML-NK gene expression data (RNA-Seq) from three datasets (TCGA, Leucegene, and PMP/BCCA). [[https://docs.google.com/a/princeton.edu/document/d/1tB75BDAoG6-ggkoKzxF_f8anTnaP0lOAZ4MG-wEWCyk/edit?usp=sharing|Full description]].   - AML-NK gene expression data (RNA-Seq) from three datasets (TCGA, Leucegene, and PMP/BCCA). [[https://docs.google.com/a/princeton.edu/document/d/1tB75BDAoG6-ggkoKzxF_f8anTnaP0lOAZ4MG-wEWCyk/edit?usp=sharing|Full description]].
Line 49: Line 49:
   - Genomic Data Commons ([[https://portal.gdc.cancer.gov/repository|GDC]]), which contains TCGA data and more.   - Genomic Data Commons ([[https://portal.gdc.cancer.gov/repository|GDC]]), which contains TCGA data and more.
   - [[https://amp.pharm.mssm.edu/archs4/|ARCHS4]], which was developed at the Icahn School of Medicine at Mount Sinai, and provides tools to download and analyze RNA-Seq data including single-cell gene expression.   - [[https://amp.pharm.mssm.edu/archs4/|ARCHS4]], which was developed at the Icahn School of Medicine at Mount Sinai, and provides tools to download and analyze RNA-Seq data including single-cell gene expression.
 +  - The [[https://www.nature.com/articles/s41586-018-0623-z#Sec38|BEAT]] ALM dataset of ~300 cases including gene expression, survival, ELN17, etc.
 +  - [[https://www.leukemiaatlas.org/adultaml|Leukemia Protein Atlas]]: Expression of hundreds of proteins were measured in bone marrow and PB samples of ~200 AML cases. A good publicly available resource to validate findings based on gene expression assays.
  
-=====   ===== 
  
 ===== Related work ===== ===== Related work =====
Line 136: Line 137:
   - Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma, [[http://www.cell.com/cell/abstract/S0092-8674(17)30639-6?innerTabgraphical_S0092867417306396|Cell]], 2017 [{{:ally-copmprehensive_and_integrative_genomic_char_of_hcc-cell-2017.pdf|pdf}}  ]. \\  TCGA's HCC data and subtyping using DNA copy number, DNA methylation, mRNA expression, miRNA expression and RPPA (protein expression). Links to the MDACC dataset with 100 HCC samples.   - Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma, [[http://www.cell.com/cell/abstract/S0092-8674(17)30639-6?innerTabgraphical_S0092867417306396|Cell]], 2017 [{{:ally-copmprehensive_and_integrative_genomic_char_of_hcc-cell-2017.pdf|pdf}}  ]. \\  TCGA's HCC data and subtyping using DNA copy number, DNA methylation, mRNA expression, miRNA expression and RPPA (protein expression). Links to the MDACC dataset with 100 HCC samples.
   - Guillamot, Maria, Luisa Cimmino, and Iannis Aifantis. "The impact of DNA methylation in hematopoietic malignancies." [[http://www.cell.com/trends/cancer/pdf/S2405-8033(15)00089-8.pdf|Trends in cancer]] 2.2 (2016): 70-83. \\  Reviews and references DNA methylation studies and datasets on AML. E.g., [[http://www.sciencedirect.com/science/article/pii/S1535610809004206|Figueroa]] et al. used DNA methylation for classification of 344 AML cases. [[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002781|Akalin]] et al. related DNA methylation patterns with mutations in 5 AML cases. "The methylation status of specific genes can predict the future survival of AML patients, suggesting that DNA methylation is a biomarker for clinical outcome" see e.g., Figueroa et al, [[http://www.bloodjournal.org/content/bloodjournal/113/6/1315.full.pdf?sso-checked=true|Jiang]] 2009 (studied MDS to AML progression in 184 cases), and [[http://www.bloodjournal.org/content/115/3/636.long?sso-checked=true|Bullinger]] 2010 (analyzed 92 genomic regions in 182 patients).   - Guillamot, Maria, Luisa Cimmino, and Iannis Aifantis. "The impact of DNA methylation in hematopoietic malignancies." [[http://www.cell.com/trends/cancer/pdf/S2405-8033(15)00089-8.pdf|Trends in cancer]] 2.2 (2016): 70-83. \\  Reviews and references DNA methylation studies and datasets on AML. E.g., [[http://www.sciencedirect.com/science/article/pii/S1535610809004206|Figueroa]] et al. used DNA methylation for classification of 344 AML cases. [[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002781|Akalin]] et al. related DNA methylation patterns with mutations in 5 AML cases. "The methylation status of specific genes can predict the future survival of AML patients, suggesting that DNA methylation is a biomarker for clinical outcome" see e.g., Figueroa et al, [[http://www.bloodjournal.org/content/bloodjournal/113/6/1315.full.pdf?sso-checked=true|Jiang]] 2009 (studied MDS to AML progression in 184 cases), and [[http://www.bloodjournal.org/content/115/3/636.long?sso-checked=true|Bullinger]] 2010 (analyzed 92 genomic regions in 182 patients).
 +  - John [[https://www.youtube.com/watch?v=Vyhq7GZFnes|Quackenbush's]] talk entitled: "Using Networks to Understand the Genotype-Phenotype Connection" \\
  
  \\ **Related software**  \\ **Related software**