Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA308201 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3090660.fastq.gz | Fastqsanger.gz | |||
| SRR3090670.fastq.gz | Fastqsanger.gz | |||
| SRR3090680.fastq.gz | Fastqsanger.gz | |||
| SRR3090661.fastq.gz | Fastqsanger.gz | |||
| SRR3090671.fastq.gz | Fastqsanger.gz |
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Project description:We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the original genome-aligned sequence reads. Comparison with a QCi database for >28,000 ChIP-seq assays were used to attribute quality grades (ranging from âAAAâ to âDDDâ) to a given dataset. In the present report we used the numerical QC system to assess the factors influencing the quality of ChIP-seq assays, including the nature of the target, the sequencing depth and the commercial source of the antibody. We have used this approach specifically to certify mono and polyclonal antibodies obtained from Active Motif directed against the histone modification marks H3K4me3, H3K27ac and H3K9ac for ChIP-seq. The antibodies received the grades AAA to BBA (www.ngs-qc.org). We propose to attribute such quantitative grading of all antibodies attributed with the label âChIP-seq gradeâ. The NGS-QC team has setup a certification procedure for Antibodies dedicated to ChIP-seq applications based on (1)a highly reproducible pipeline for performing ChIP-seq assays including the use of an automated liquid handling platform (TECAN EVO75) for ChIP and sequencing library preparation steps and (2) the use of the NGS-QC Generator tool for providing a ChIP-seq quality grade and to evaluate other parameters like the Optimal sequencing depth, the degree of reproducibility among biological replicates and the comparison of the quality grades of the certified antibody with datasets retrieved in the public domain. This quality certification structure makes possible to assign a measured Quality Stamp to ChIP-seq grade Antibodies.
2016-01-07 | E-GEOD-76618 | biostudies-arrayexpress
Project description:We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the original genome-aligned sequence reads. Comparison with a QCi database for >28,000 ChIP-seq assays were used to attribute quality grades (ranging from ‘AAA’ to ‘DDD’) to a given dataset. In the present report we used the numerical QC system to assess the factors influencing the quality of ChIP-seq assays, including the nature of the target, the sequencing depth and the commercial source of the antibody. We have used this approach specifically to certify mono and polyclonal antibodies obtained from Active Motif directed against the histone modification marks H3K4me3, H3K27ac and H3K9ac for ChIP-seq. The antibodies received the grades AAA to BBA (www.ngs-qc.org). We propose to attribute such quantitative grading of all antibodies attributed with the label “ChIP-seq grade”.
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Project description:Background: As the most stable and experimentally accessible epigenetic mark, DNA methylation is of great interest to the research community. The landscape of DNA methylation across tissues, through development and in disease pathogenesis is not yet well characterised. Thus there is a need for rapid and cost effective methods for assessing genome-wide levels of DNA methylation. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a very useful addition to the available methods but its complex design, incorporating two different assay methods, requires careful consideration. Accordingly, several normalization schemes have been published. We have taken advantage of known DNA methylation patterns associated with genomic imprinting and X-chromosome inactivation (XCI), in addition to the performance of SNP genotyping assays present on the array, to derive three independent metrics which we use to test alternative schemes of correction and normalization. These metrics also have potential utility as quality scores for datasets. Results: The standard index of DNA methylation at any specific CpG site is ? = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities. Betas calculated from raw signal intensities (the default GenomeStudio behaviour) perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. More elaborate manipulation of quantiles proves to be counterproductive. Conclusions: Careful selection of preprocessing steps can minimise variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes. For the convenience of the research community we have created an R software package called wateRmelon, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilise the same normalization methods and data quality tests on 450K data. Bisulfite converted DNA from the 11 cohorts (N=695, including 36 technical replicates) were hybridised to the Illumina Infinium 450k Human Methylation Beadchip v1.2
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Project description:Antibodies are used in multiple cell biology applications but there are methods to assess antibody quality, riskingdata integrity and repr developed a standard operating procedure using HEK293 cells to score and antibodies for suitability in immunoprecipitation. This method, validated in in fourindependent laboratories, was developed using 1124 novel recomb for152 chromatin-related human proteins. We used mass spectrometry abundanceof all the proteinsin eachimmunoprecipitateand compared spectral abundance factors from the target antigen with those of all Antibodies for which the targetantigen or a member of its known protein most abundant protein were classified as “IP gold standard”. This m quantitative outputs that can be stored and archived in public databases, step towards a platform for community benchmarking of antibody quality.
2015-07-15 | PXD002534 | Pride
Project description:ChIP-exo/nexus experiments present modifications on the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a statistical quality control pipeline and accompanying R package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics calculated over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from E. coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. Finally, although ChIP-exo experiments have been compared to ChIP-seq experiments with single-end (SE) sequencing, we provide, for the first time, comparisons with paired-end (PE) ChIP-seq experiments. We illustrate that, at fixed sequencing depths, ChIP-exo provides higher sensitivity, specificity, and spatial resolution than PE ChIP-seq and both significantly outperform their SE ChIP-seq counterpart.
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