data-raw/TRED/README.md

In slowkow/tftargets: Human Transcription Factor Targets

TRED: a Transcriptional Regulatory Element Database and a platform for in silico gene regulation studies

Fang Zhao, Zhenyu Xuan, Lihua Liu, Michael Q. Zhang

http://dx.doi.org/10.1093/nar/gki004

In order to understand gene regulation, accurate and comprehensive knowledge of transcriptional regulatory elements is essential. Here, we report our efforts in building a mammalian Transcriptional Regulatory Element Database (TRED) with associated data analysis functions. It collects cis- and trans-regulatory elements and is dedicated to easy data access and analysis for both single-gene-based and genome-scale studies. Distinguishing features of TRED include: (i) relatively complete genome-wide promoter annotation for human, mouse and rat; (ii) availability of gene transcriptional regulation information including transcription factor binding sites and experimental evidence; (iii) data accuracy is ensured by hand curation; (iv) efficient user interface for easy and flexible data retrieval; and (v) implementation of on-the-fly sequence analysis tools. TRED can provide good training datasets for further genome-wide cis-regulatory element prediction and annotation, assist detailed functional studies and facilitate the decipher of gene regulatory networks (http://rulai.cshl.edu/TRED).

TRED Website

https://cb.utdallas.edu/cgi-bin/TRED/tred.cgi?process=home

Introduction

In order to understand gene regulation, accurate and comprehensive knowledge of transcriptional regulatory elements is essential. Transcriptional Regulatory Element Database (TRED) has been built in response to increasing needs of an integrated repository for both cis- and trans- regulatory elements in mammals, and the lack of such resources at present.

Genome-wide human, mouse and rat promoter annotation in TRED was realized by an automated pipeline to extract known promoters from databases such as Genbank, EPD and DBTSS, and employ promoter finding program FirstEF combined with mRNA/EST information and cross-species comparisons. We have also carried out hand curation to assess computational prediction and ensure data accuracy. A quality level is assigned to each promoter based on the reliability of the supporting evidence.

Curation has also been done for transcriptional regulation information, including transcription factor binding motifs and experimental evidence. Binding motifs are mapped on promoters of the corresponding genes and binding quality levels are assigned based on definitiveness of the binding evidence. Curation is currently focusing on target genes of 36 cancer-related TF families.

Distinguishing features of TRED include:

• relatively complete genome wide promoter annotation for human, mouse and rat
• availability of transcription factor binding and regulation information
• data accuracy is ensured by curation, which continues to expand
• easy and flexible data retrieval
• availability of on-the-fly sequence analysis tools

TRED can provide good training datasets for further genome wide cis-regulatory element prediction, assist detailed functional studies, and facilitate to decipher the gene regulatory networks.

Michael Zhang Lab, Cold Spring Harbor Laboratory, all rights reserved Questions/suggestions email: Ashwinikumar Kulkarni [e-mail]

slowkow/tftargets documentation built on May 30, 2019, 3:06 a.m.