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Additional file 3 of Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia

Autor: Onishi-Seebacher, M., Erikson, G., Sawitzki, Z., Ryan, D., Greve, G., Lübbert, M., Jenuwein, T.

Additional file 3: Figure S3: MA plots for distinct repeat element expression in M1, M2 and M4 AML patient samples (Uniklinik Freiburg). MA-plots (mean expression versus the log2 fold change) depicting changes in repeat expression in the CD34+ contro

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Additional file 10 of Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia

Autor: Onishi-Seebacher, M., Erikson, G., Sawitzki, Z., Ryan, D., Greve, G., Lübbert, M., Jenuwein, T.

Additional file 10: Figure S10. Correlation between recurring gene mutations and R/G ratios in TCGA AML patient samples. (A) Box plot showing the most frequent gene mutations (x axis) in the TCGA AML cohort (n=98), as they were identified using metad

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Additional file 7 of Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia

Autor: Onishi-Seebacher, M., Erikson, G., Sawitzki, Z., Ryan, D., Greve, G., Lübbert, M., Jenuwein, T.

Additional file 7: Figure S7. Coverage and distribution of repeat transcripts in Uniklinik Freiburg samples and in the Blueprint and TCGA data sets. (A) Fraction of all repeat transcripts (blue segment) versus the fraction of all protein coding trans

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Additional file 6 of Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia

Autor: Onishi-Seebacher, M., Erikson, G., Sawitzki, Z., Ryan, D., Greve, G., Lübbert, M., Jenuwein, T.

Additional file 6: Figure S6: Inter-patient variation plots for expression of 12 LTR/ERV repeat subtypes in TCGA AML samples. Inter-patient variation plots display normalized read counts of distinct LTR/ERV repeat transcripts that are above the expre

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Additional file 9 of Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia

Autor: Onishi-Seebacher, M., Erikson, G., Sawitzki, Z., Ryan, D., Greve, G., Lübbert, M., Jenuwein, T.

Additional file 9: Figure S9: Activation of Toll-like receptor and interferon signaling in ‘high-repeat’ and ‘low-repeat’ AML patient samples. Ingenuity pathway analysis (IPA) performed in High-repeat AML patient samples (n=16) vs. CD34+ Blue

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Additional file 5 of Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia

Autor: Onishi-Seebacher, M., Erikson, G., Sawitzki, Z., Ryan, D., Greve, G., Lübbert, M., Jenuwein, T.

Additional file 5: Figure S5: Inter-patient variation plots for expression of 12 Satellite repeat subtypes in TCGA AML samples. Inter-patient variation plots display normalized read counts of distinct Satellite repeat transcripts that are above the e

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Additional file 4 of Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia

Autor: Onishi-Seebacher, M., Erikson, G., Sawitzki, Z., Ryan, D., Greve, G., Lübbert, M., Jenuwein, T.

Additional file 4: Figure S4. Heatmaps for dysregulated repeat element expression in Uniklinik Freiburg and Blueprint AML samples. (A) Top 30 statistically significant (absolute value of log2FoldChange >1; adjusted p-value 1; adjusted p-value

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Additional file 8 of Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia

Autor: Onishi-Seebacher, M., Erikson, G., Sawitzki, Z., Ryan, D., Greve, G., Lübbert, M., Jenuwein, T.

Additional file 8: Figure S8: Inter-patient variation plots for expression of repeat element subclasses in ‘low-repeat’, ‘mid-repeat’ and ‘high-repeat’ AML patient samples. Inter-patient variation plots display normalized read counts in e

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