JAMIE: joint analysis of multiple ChIP-chip experiments

Abstract

Motivation: Chromatin immunoprecipitation followed by genome tiling array hybridization (ChIP-chip) is a powerful approach to identify transcription factor binding sites (TFBSs) in target genomes. When multiple related ChIP-chip datasets are available, analyzing them jointly allows one to borrow information across datasets to improve peak detection. This is particularly useful for analyzing noisy datasets.

Results: We propose a hierarchical mixture model and develop an R package JAMIE to perform the joint analysis. The genome is assumed to consist of background and potential binding regions (PBRs). PBRs have context-dependent probabilities to become bona fide binding sites in individual datasets. This model captures the correlation among datasets, which provides basis for sharing information across experiments. Real data tests illustrate the advantage of JAMIE over a strategy that analyzes individual datasets separately.

Availability: JAMIE is freely available from http://www.biostat.jhsph.edu/~hji/jamie

Fig. 1.

Motivation and model structure of JAMIE. (a) Four Gli ChIP-chip datasets show co-occurrence of binding sites at the same genomic locus. This correlation may help to distinguish real and false TFBSs. Each bar in the plot corresponds to a probe. Height of the bar is the log₂ ratio between ChIP and control intensities. Med, medulloblastoma; GNP, granule neuron precursor cells. (b) An example that shows context dependency of TF-DNA binding. (c) An illustration of the JAMIE model.

Fig. 2.

Comparisons of peak detection results of different methods (JAMIE pooling, JAMIE single, TileMap and MAT) in simulated data. (a) Peak detection accuracy. X-axis is number of top-ranked peaks. Y-axis is the percentage of peaks being true positives. (b) Sensitivity at various nominal FDR cutoffs. X-axis is the nominal FDR. Y-axis is the number of peaks reported under the corresponding nominal FDR. (c) Observed true FDR versus nominal FDR.

Fig. 3.

Comparisons of peak detection accuracies of JAMIE pooling, JAMIE single, TileMap and MAT in real ChIP-chip data. X-axis is the number of top-ranked peaks. Y-axis is the average percentage of correct detections. The first row shows the results for Agilent data, the second row is for Gli data and the third row is for DREAM data.

Fig. 4.

Comparisons of motif enrichment in top peaks detected by different algorithms. (a) Oct4 motif in Oct4 data, (b) Gli motif in Gil1_Limb data and (c) E2F4 motif in LIN54_G0 data. X-axis is the number of top-ranked peaks. Y-axis is the percentage of peaks with at least one motif site.