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Open AccessJournal ArticleDOI

Target analysis by integration of transcriptome and ChIP-seq data with BETA

TLDR
BETA is a software package that integrates ChIP-seq of TFs or chromatin regulators with differential gene expression data to infer direct target genes and identifies the motif of the factor and its collaborators, which might modulate the factor's activating or repressive function.
Abstract
The combination of ChIP-seq and transcriptome analysis is a compelling approach to unravel the regulation of gene expression. Several recently published methods combine transcription factor (TF) binding and gene expression for target prediction, but few of them provide an efficient software package for the community. Binding and expression target analysis (BETA) is a software package that integrates ChIP-seq of TFs or chromatin regulators with differential gene expression data to infer direct target genes. BETA has three functions: (i) to predict whether the factor has activating or repressive function; (ii) to infer the factor's target genes; and (iii) to identify the motif of the factor and its collaborators, which might modulate the factor's activating or repressive function. Here we describe the implementation and features of BETA to demonstrate its application to several data sets. BETA requires ~1 GB of RAM, and the procedure takes 20 min to complete. BETA is available open source at http://cistrome.org/BETA/.

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Journal ArticleDOI

A survey of best practices for RNA-seq data analysis

TL;DR: All of the major steps in RNA-seq data analysis are reviewed, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping.
Journal ArticleDOI

Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis.

TL;DR: The Cistrome DB has a new Toolkit module with several features that allow users to better utilize the large-scale ChIP-seq, DNase-seq and ATAC-seq data, and the new tools will greatly benefit the biomedical research community.
Journal ArticleDOI

Cistrome Data Browser: a data portal for ChIP-Seq and chromatin accessibility data in human and mouse

TL;DR: The Cistrome database is built, a collection of ChIP-seq and chromatin accessibility data published before January 1, 2016, including 13 366 human and 9953 mouse samples that are expected to become a valuable resource for transcriptional and epigenetic regulation studies.
Journal ArticleDOI

Cross-tissue organization of the fibroblast lineage.

TL;DR: In this paper, a cross-species and pan-tissue approach to transcriptomics at single-cell resolution has identified key organizing principles of the fibroblast lineage in health and disease.
References
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Journal ArticleDOI

Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

TL;DR: Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches and can be used simultaneously to achieve even greater alignment speeds.
Journal ArticleDOI

Model-based Analysis of ChIP-Seq (MACS)

TL;DR: This work presents Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer, and uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions.
Journal ArticleDOI

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks

TL;DR: This protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results, which takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
Journal ArticleDOI

The Human Genome Browser at UCSC

TL;DR: A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu.
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