Systematic evaluation of factors influencing ChIP-seq fidelity.
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SUBMITTER: Chen Y
PROVIDER: S-EPMC3477507 | biostudies-literature | 2012 Jun
REPOSITORIES: biostudies-literature
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Systematic evaluation of factors influencing ChIP-seq fidelity.
Chen Yiwen Y Negre Nicolas N Li Qunhua Q Mieczkowska Joanna O JO Slattery Matthew M Liu Tao T Zhang Yong Y Kim Tae-Kyung TK He Housheng Hansen HH Zieba Jennifer J Ruan Yijun Y Bickel Peter J PJ Myers Richard M RM Wold Barbara J BJ White Kevin P KP Lieb Jason D JD Liu X Shirley XS
Nature methods 20120422 6
We evaluated how variations in sequencing depth and other parameters influence interpretation of chromatin immunoprecipitation-sequencing (ChIP-seq) experiments. Using Drosophila melanogaster S2 cells, we generated ChIP-seq data sets for a site-specific transcription factor (Suppressor of Hairy-wing) and a histone modification (H3K36me3). We detected a chromatin-state bias: open chromatin regions yielded higher coverage, which led to false positives if not corrected. This bias had a greater effe ...[more]
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Project description:Next-generation DNA sequencing coupled with chromatin immunoprecipitation (ChIP-seq) is revolutionizing our ability to interrogate whole genome protein-DNA interactions. Identification of protein binding sites from ChIP-seq data has required novel computational tools, distinct from those used for the analysis of ChIP-Chip experiments. The growing popularity of ChIP-seq spurred the development of many different analytical programs (at last count, we noted 31 open source methods), each with some purported advantage. Given that the literature is dense and empirical benchmarking challenging, selecting an appropriate method for ChIP-seq analysis has become a daunting task. Herein we compare the performance of eleven different peak calling programs on common empirical, transcription factor datasets and measure their sensitivity, accuracy and usability. Our analysis provides an unbiased critical assessment of available technologies, and should assist researchers in choosing a suitable tool for handling ChIP-seq data.
| S-EPMC2900203 | biostudies-other
Project description:BackgroundBlunt chest wall injuries can lead to complications, especially without early intervention. A blunt Chest Injury Protocol (ChIP) was developed to help improve the consistency of evidence-based care following admission to the emergency department. Implementation strategy fidelity is the extent to which the strategies of implementation are delivered in line with the intended plan. The aim of this study was to assess fidelity to the strategies of the implementation plan developed for ChIP.MethodsA retrospective evaluation of strategies used for implementation was performed, specifically the behaviour change techniques (BCTs). BCTs were used as part of an implementation plan derived based on the Behaviour Change Wheel from results from a staff survey at two hospitals. Levels of implementation or adaptation for BCTs were scored by implementers as follows: 'Were the behaviour change interventions implemented?' (0 = 'not implemented', 1 = partially implemented, and 2 = fully implemented); 'Were adaptations made to the implementation plan?', scored 1 (many changes from plan) to 4 (just as planned). Free text explanation to their responses was also collected with supporting evidence and documentation (such as emails, implementation checklists, audit reports, and incident reports).ResultsThere was high overall fidelity of 97.6% for BCTs partially or fully implemented. More than three quarters (32/42, 76.2%) of the BCTs were fully implemented with an additional 9/42 (21.4%) partially implemented. BCTs that were not fully implemented were social support, feedback on behaviour, feedback on outcomes of behaviour, adding objects to the environment, and restructuring the environment. The modes of delivery with poorer implementation or increased adaptations were clinical champions and audit/feedback.ConclusionsThis study describes the evaluation of implementation strategy fidelity in the acute care context. The systematic use and application of the behaviour change wheel was used to develop an implementation plan and was associated with high implementation strategy fidelity. A fidelity checklist developed during the implementation process may help implementers assess fidelity.Trial registrationTrial registered on ANZCTR. Registration number ACTRN12618001548224 , date approved 17/09/2018.
| S-EPMC8353870 | biostudies-literature
Project description:Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) or microarray hybridization (ChIP-chip) has been widely used to determine the genomic occupation of transcription factors (TFs). We have previously developed a probabilistic method, called TIP (Target Identification from Profiles), to identify TF target genes using ChIP-seq/ChIP-chip data. To achieve high specificity, TIP applies a conservative method to estimate significance of target genes, with the trade-off being a relatively low sensitivity of target gene identification compared to other methods. Additionally, TIP's output does not render binding-peak locations or intensity, information highly useful for visualization and general experimental biological use, while the variability of ChIP-seq/ChIP-chip file formats has made input into TIP more difficult than desired.To improve upon these facets, here we present are fined TIP with key extensions. First, it implements a Gaussian mixture model for p-value estimation, increasing target gene identification sensitivity and more accurately capturing the shape of TF binding profile distributions. Second, it enables the incorporation of TF binding-peak data by identifying their locations in significant target gene promoter regions and quantifies their strengths. Finally, for full ease of implementation we have incorporated it into a web server ( http://syslab3.nchu.edu.tw/iTAR/ ) that enables flexibility of input file format, can be used across multiple species and genome assembly versions, and is freely available for public use. The web server additionally performs GO enrichment analysis for the identified target genes to reveal the potential function of the corresponding TF.The iTAR web server provides a user-friendly interface and supports target gene identification in seven species, ranging from yeast to human. To facilitate investigating the quality of ChIP-seq/ChIP-chip data, the web server generates the chart of the characteristic binding profiles and the density plot of normalized regulatory scores. The iTAR web server is a useful tool in identifying TF target genes from ChIP-seq/ChIP-chip data and discovering biological insights.
| S-EPMC4983039 | biostudies-literature
Project description:The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip See manuscript for details
2010-05-14 | E-GEOD-10112 | biostudies-arrayexpress
Project description:The most widely-used method for detecting and measuring genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Many tiling array platforms, amplification methods, and analysis algorithms exist for ChIP-chip, but a rigorous assessment of the relative performance of these factors has not been reported. In a multi-lab simulation of a ChIP-chip experiment, we conducted the first objective analysis of tiling array platforms and analysis algorithms. We designed a complex mixture of human genomic DNA with a "spike-in" comprised of nearly 100 human sequences at various concentrations. Eight independent groups hybridized these mixtures to four different tiling array platforms. The groups were blind to the composition of the spike-in mix, the range of concentrations covered, or how many sequences it contained. Still blind to the key, each group made predictions of the spike-in locations based on their measurements. The results reveal that all commercial tiling array platforms perform well, although each platform and analysis algorithm has distinct performance characteristics. Simple sequence repeats and genome redundancy tend to result in false positives on oligonucleotide platforms. We also compare genome-wide platforms with regard to performance and cost. The spike-in DNA samples and the resulting array data presented in our study provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: Spike in Control For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf With the availability of sequenced genomes and whole-genome tiling microarrays, many researchers have conducted experiments using ChIP-chip and related methods to study genome-wide protein-DNA interactions1-9. These are powerful yet challenging techniques, which are comprised of many steps that can introduce variability in the final results. One potentially important factor is the relative performance of different types of tiling arrays. Currently the most popular platforms for performing ChIP-chip experiments are PCR-product based tiling arrays spotted in academic laboratories and commercial oligonucleotide-based tiling arrays from Affymetrix, NimbleGen, and Agilent. A second factor known to introduce variation is the DNA amplification protocol, which is often required because the low DNA yield from a ChIP experiment prevents direct detection on microarrays. A third factor is the algorithm used for detecting regions of enrichment from the tiling array data. A number of algorithms have been developed, but until this report there was no benchmark dataset to systematically evaluate them. In this study, we used a spike-in experiment to systematically evaluate the effects of tiling microarrays, amplification protocols, and data analysis algorithms on ChIP-chip results. There are other potentially important factors that from a practical standpoint are more difficult to systematically control and evaluate, and are not assessed here. These include the experimenter, the amount of starting material used, size of DNA fragments after shearing, DNA labeling method, and hybridization conditions. There have been several studies evaluating the performance of gene expression microarrays and analysis algorithms10-13. However, because tiling arrays must cover large genomic regions, they have different probe properties and high probe densities, and therefore present different biochemical and informatics challenges. Thus the results from the expression array spike-in experiments are not necessarily directly relevant to tiling array experiments. One recent study compared the performance of array-based (ChIP-chip) and sequence-based (ChIP-PET) technologies on a real ChIP experiment14. However, because this was an exploratory experiment, the list of absolute “true positive” targets was and is unknown. Since this experiment was performed without a key, the sensitivity and specificity of each technology had to be estimated retrospectively by qPCR validation of targets predicted from each platform. In our experiment, eight independent research groups at locations worldwide hybridized two different mixtures of DNA to one of four tiling array platforms, and predicted genome location and concentration of the spike-in sequences using a total of 13 different algorithms. Throughout the process, the research groups were entirely blind to the contents of the spike-in mixtures. Using the spike-in key, we analyzed several performance parameters for each platform, algorithm, and amplification method. While all commercial platforms performed well, we found that each had unique performance characteristics. We examined the implications of these results in planning human genome-wide experiments, in which trade-offs between probe density and cost are important.
2008-01-31 | E-GEOD-9842 | biostudies-arrayexpress
Project description:Chromatin immunoprecipitation and sequencing (ChIP-seq) has been widely used to map DNA-binding proteins, histone proteins and their modifications. ChIP-seq data contains redundant reads termed duplicates, referring to those mapping to the same genomic location and strand. There are two main sources of duplicates: polymerase chain reaction (PCR) duplicates and natural duplicates. Unlike natural duplicates that represent true signals from sequencing of independent DNA templates, PCR duplicates are artifacts originating from sequencing of identical copies amplified from the same DNA template. In analysis, duplicates are removed from peak calling and signal quantification. Nevertheless, a significant portion of the duplicates is believed to represent true signals. Obviously, removing all duplicates will underestimate the signal level in peaks and impact the identification of signal changes across samples. Therefore, an in-depth evaluation of the impact from duplicate removal is needed. Using eight public ChIP-seq datasets from three narrow-peak and two broad-peak marks, we tried to understand the distribution of duplicates in the genome, the extent by which duplicate removal impacts peak calling and signal estimation, and the factors associated with duplicate level in peaks. The three PCR-free histone H3 lysine 4 trimethylation (H3K4me3) ChIP-seq data had about 40% duplicates and 97% of them were within peaks. For the other datasets generated with PCR amplification of ChIP DNA, as expected, the narrow-peak marks have a much higher proportion of duplicates than the broad-peak marks. We found that duplicates are enriched in peaks and largely represent true signals, more conspicuous in those with high confidence. Furthermore, duplicate level in peaks is strongly correlated with the target enrichment level estimated using nonredundant reads, which provides the basis to properly allocate duplicates between noise and signal. Our analysis supports the feasibility of retaining the portion of signal duplicates into downstream analysis, thus alleviating the limitation of complete deduplication.
| S-EPMC6447195 | biostudies-literature
Project description:BackgroundThe Online Remote Behavioral Intervention for Tics (ORBIT) study was a multicenter randomized controlled trial of a complex intervention that consisted of a web-based behavioral intervention for children and young people with tic disorders. In the first part of a two-stage process evaluation, we conducted a mixed methods study exploring the reach, dose, and fidelity of the intervention and contextual factors influencing engagement.ObjectiveThis study aims to explore the fidelity of delivery and contextual factors underpinning the ORBIT trial.MethodsBaseline study data and intervention usage metrics from participants in the intervention arm were used as quantitative implementation data (N=112). The experiences of being in the intervention were explored through semistructured interviews with children (n=20) and parent participants (n=20), therapists (n=4), and referring clinicians (n=6). A principal component analysis was used to create a comprehensive, composite measure of children and young people's engagement with the intervention. Engagement factor scores reflected relative uptake as assessed by a range of usage indices, including chapters accessed, number of pages visited, and number of log-ins. The engagement factor score was used as the dependent variable in a multiple linear regression analysis with various contextual variables as independent variables to assess if there were any significant predictors of engagement.ResultsThe intervention was implemented with high fidelity, and participants deemed the intervention acceptable and satisfactory. The engagement was high, with child participants completing an average of 7.5 of 10 (SD 2.7) chapters, and 88.4% (99/112) of participants completed the minimum of the first four chapters-the predefined threshold effective dose. Compared with the total population of children with tic disorders, participants in the sample tended to have more educated parents and lived in more economically advantaged areas; however, socioeconomic factors were not related to engagement factor scores. Factors associated with higher engagement factor scores included participants enrolled at the London site versus the Nottingham site (P=.01), self-referred versus clinic referred (P=.04), higher parental engagement as evidenced by the number of parental chapters completed (n=111; ρ=0.73; P<.001), and more therapist time for parents (n=111; ρ=0.46; P<.001). A multiple linear regression indicated that parents' chapter completion (β=.69; t110=10.18; P<.001) and therapist time for parents (β=.19; t110=2.95; P=.004) were the only significant independent predictors of child engagement factor scores.ConclusionsOverall, the intervention had high fidelity of delivery and was evaluated positively by participants, although reach may have been constrained by the nature of the randomized controlled trial. Parental engagement and therapist time for parents were strong predictors of intervention implementation, which has important implications for designing and implementing digital therapeutic interventions in child and adolescent mental health services.International registered report identifier (irrid)RR2-10.1186/s13063-019-3974-3.
| S-EPMC8277316 | biostudies-literature
Project description:The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf 3 spike-in replicates and 3 genomic input control replicates
2007-12-12 | E-GEOD-9849 | biostudies-arrayexpress
Project description:The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf 9 spike-in replicates and 9 genomic input control replicates
2007-12-12 | E-GEOD-9848 | biostudies-arrayexpress
Project description:BackgroundNon-adherence is widespread problem. Adherence is a crucial point for the success and the safe use of therapies. The objective of this overview (review of reviews) was to identify factors that influence adherence in chronic physical conditions.MethodsA systematic literature search was performed in Medline and Embase (1990 to July 2013). Publications were screened according to predefined inclusion criteria. The study quality was assessed using AMSTAR. Both process steps were carried out independently by two reviewers. Relevant data on study characteristics and results were extracted in piloted standardized tables by one reviewer and checked by a second. Data were synthesized using a standardized quantitative approach by two reviewers.ResultsSeven systematic reviews were included. Higher education and employment seem to have a positive effect on adherence. Ethnic minorities seem to be less adherent. Co-payments and higher medication cost seems to have negative effect on adherence. In contrast financial status/income and marital status seem to have no influence on adherence. The effect of therapy related factors was mostly unclear or had no effect. Only the number of different medications in heart failure patients showed the tendency of an effect. Indicators of regime complexity showed consistently a negative effect direction. Duration of disease seems to have no effect on adherence. There is the tendency that higher or middle age is associated with higher adherence. But in more than half of the reviews the effect was unclear. There is no clear effect of physical as well as mental comorbidity. Only one review showed the tendency of an effect for mental comorbidity. Also for gender the effect is not clear because the effect direction was heterogenic between and within the systematic reviews.ConclusionThe presented overview shows factors than can potentially have influence on adherence. Only for a few factors the influence on adherence was consistent. Most factors showed heterogeneous results regarding statistical significance and/or effect direction. However, belonging to an ethnic minority, unemployment and cost for the patient for their medications showed consistently a negative effect on adherence which indicates that there is a social gradient.
| S-EPMC4323150 | biostudies-literature