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Open Access Highly Accessed Research article

Epigenetic features are significantly associated with alternative splicing

Yuanpeng Zhou, Yulan Lu and Weidong Tian*

Author Affiliations

State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Science, Fudan University, 220 Handan Rd, Shanghai 2004333, China

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BMC Genomics 2012, 13:123  doi:10.1186/1471-2164-13-123

Published: 29 March 2012

Additional files

Additional file 1:

The procedures on recognizing the AS events. (a) Junction site annotation and alternative splicing recognition process. (b) The recognition code of AS events and the number of each type of splicing event.

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Open Data

Additional file 2:

All p-values indicating the association of epigenetic features investigated in this study with AS.

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Additional file 3:

The association of mCG with AS in different cell types. The distributions of mCG in H1 hESC and IMR90 cell types are showed; the color scheme and the plotting method is the same as that of mCG in Figure 1b.

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Additional file 4:

Available data of cell lines for all epigenetic feature and the used file name of the download file in ENCODE and Roadmap Epigenomics.

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Additional file 5:

The association of additional histone acetylations with AS. This figure shows the distributions of histone acetylations not included in Figure 2.

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Additional file 6:

The association of additional protein features with AS. This figure shows the profiles of protein features not included in Figure 3.

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Additional file 7:

The association of histone modifications and protein features with AS in different cell types. The level of each feature in four bins around the accepter and donor splice sites are shown for different cell lines; the error bars are drawn for 5% confidence interval.

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Additional file 8:

Classical multidimensional scaling plot of epigenetic features on the basis of their association with AS. The color and point type of each epigenetic features is the same with the cluster index of the k-means clustering result (Figure 4). The distance of two features indicates the closeness of their relationships. Note that cluster 1 and cluster 2 features are distantly to each other while cluster 3 and cluster 4 features are more closely related. Some features, such as nucleosome occupancy and NRSF, are located in between clusters. Classical multidimensional scaling is done using "cmdscale" function in GNU R.

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Open Data

Additional file 9:

The distribution of ChIP-seq input data in different types of ASEs and CNEs.

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Additional file 10:

The distribution of ChIP-seq data surrounding the splice sites of ASEs and CNEs in GM12878 and K562 cell lines. The patterns of most features are not changed after the correction. Only GM12878 and K562 cell lines are selected because they have available data for most of our significantly associated feature.

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Open Data

Additional file 11:

Heatmap of epigenetic features corrected by ChIP-seq input. Un-adjusted P-values are shown. The method is the same as that in Figure 4.

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Additional file 12:

Heatmap of epigenetic features corrected by nucleosome occupancy. Un-adjusted P-values are shown. The method is the same as that in Figure 4.

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Open Data

Additional file 13:

The distribution of exon length.

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Additional file 14:

Statistic test of the difference between the fourth exon and third exon, for each ASE(CNE) and each feature.

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Additional file 15:

Additional scripts for the recognitions of AS event.

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