Comparison of sequence-specific transcription factor determinations by ChIP-seq and ChIP-qPCR.
			Gertz J, Reddy TE, Pauli F, and Myers RM
			
The key platform characterization finding is that there is good 
			agreement between ChIP-seq and ChIP-qPCR. For each of 12 transcription 
			factors, the enrichment of 44 binding sites was measured by qPCR. There 
			was a high concordance between enrichment results from qPCR and the 
			density of reads in ChIP-seq binding sites. These results indicate that 
			high-throughput DNA sequencing maintains a robust representation of 
			immunoprecipitated material.
			
			Synthetic spike-in standards for RNA-seq experiments.
			Jiang L, Schlesinger F, Davis CA, Zhang Y, Li R, Salit M, Gingeras TR, Oliver B.
			Genome Res. 2011 Aug 4. [Epub ahead of print]; PMID: 21816910
			
		
			Key platform characterization finding is that over a wide range, there is a linear correlation 
			between signal (read density) and RNA concentration (input) in RNA-seq experiments.  Another key 
			finding is excellent agreement between replicates.  A pool of RNA standards (96 different RNAs, 
			various lengths and GC content) spanning a million fold concentration range was used in this determination.
			Some bias was found with respect to GC content and fragment length; these biases were reproducible and protocol dependent.
			
		
			ChIP-chip versus ChIP-seq: lessons for experimental design and data analysis.
			Ho JW, Bishop E, Karchenko PV, Nègre N, White KP, Park PJ.
			BMC Genomics. 2011 Feb 28;12:134. PMID: 21356108; PMCID: PMC3053263
			
		
			Key platform characterization findings include ChIP-seq data are generally better than ChIP-chip 
			data with respect to signal-to-noise ratio, number of detected peaks and resolution. While there is 
			strong agreement between the two platforms, the peaks identified using these two platforms can be significantly 
			different, depending on the factor antibody and the analysis pipeline. Identification of binding regions is 
			dependent on the peak calling pipeline used, and more difficult for factors that are enriched in broad regions.  
			In addition, input DNA libraries used for ChIP-seq can vary, and high-quality input samples sequenced with 
			sufficient depth are important for accurate peak calling.
			
		
			An assessment of histone-modification antibody quality.
			Egelhofer TA, Minoda A, Klugman S, Lee K, Kolasinska-Zwierz P, Alekseyenko AA, Cheung MS, Day DS, Gadel S, 
			Gorchakov AA et al.
			Nat Struct Mol Biol. 2011 Jan;18(1):91-3. Epub 2010 Dec 5. PMID: 21131980; PMCID: PMC3017233
			
		
			
            Histone modification antibodies were characterized for specificity and 
            ChIP. More than 25% of the tested antibodies failed specificity tests 
            by dot blot or western blot. More than 20% of the antibodies that passed 
            the specificity test failed in ChIP experiments. A website was 
            developed for posting new results 
            (http://compbio.med.harvard.edu/antibodies/).
			
		
			Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets.
			Johnson DS, Li W, Gordon DB, Bhattacharjee A, Curry B, Ghosh J, Brizuela L, Carroll JS, Brown M, Flicek P et al.
			Genome Res. 2008 Mar;18(3):393-403. Epub 2008 Feb 7.PMID: 18258921; PMCID: PMC2259103
			
		
			A number of microarray platforms were tested using a spike-in positive control approach, and found to provide results that 
			were consistent with each other.  Variance specific to microarray platform was similar or smaller than the variance associated with 
			laboratory, protocols and analysis pipeline.  Sensitivity was good even at relatively low spike-in levels.  Simple repeats and 
			segmental duplication caused false positive errors in peak detection.