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Open Access Research article

Comprehensive meta-analysis of Signal Transducers and Activators of Transcription (STAT) genomic binding patterns discerns cell-specific cis-regulatory modules

Keunsoo Kang1*, Gertraud W Robinson1 and Lothar Hennighausen12*

Author Affiliations

1 Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 8 Center Drive, Bethesda, MD, 20892-0822, USA

2 National Department of Nanobiomedical Science and WCU Research Center of Nanobiomedical Science, Dankook University, Cheonan, Chungnam, 330-714, Republic of Korea

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BMC Genomics 2013, 14:4  doi:10.1186/1471-2164-14-4

Published: 16 January 2013

Additional files

Additional file 1:

Peak-calling analysis pipeline used in this study. A figure showing the peak-calling analysis pipeline.

Format: PDF Size: 40KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional file 2:

Summary of processed ChIP-seq data sets. A table summarizing processed ChIP-seq data sets.

Format: XLS Size: 41KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 3:

Functional annotations of cell-specific STAT binding sites. A figure showing the functional annotations of cell-specific STAT binding sites.

Format: PDF Size: 298KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional file 4:

Genes near the CSCCs. A table of genes near the CSCCs.

Format: XLS Size: 42KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 5:

Motif prediction with STAT4 and STAT6 binding sites. De novo motif prediction with top 600 binding sites of STAT4 and STAT6.

Format: PDF Size: 68KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional file 6:

Custom perl script predicting co-transcription factors. A custom perl script using the MOODS algorithm.

Format: ZIP Size: 12KB Download file

Open Data