"The Wild West of Spike-in Normalization": Benchmarking the ChIP-seq spike-in normalization method
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ABSTRACT:
PROVIDER: PRJNA1144087 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR30125600.fastq.gz | Fastqsanger.gz | |||
| SRR30125601.fastq.gz | Fastqsanger.gz | |||
| SRR30125602.fastq.gz | Fastqsanger.gz | |||
| SRR30125603.fastq.gz | Fastqsanger.gz | |||
| SRR30125604.fastq.gz | Fastqsanger.gz |
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Project description:Epigenomic profiling by ChIP-seq is a prevailing methodology used to investigate chromatin-based regulation in biological systems, such as human disease, yet the lack of an empirical methodology to normalize amongst experiments has limited the usefulness of this technique. Here we describe a “spike-in” normalization method that allows the quantitative comparison of histone modification status across cell populations using defined quantities of a reference epigenome. We demonstrate the utility of this method in measuring epigenomic changes following chemical perturbations and show how control normalization of ChIP-seq experiments enables discovery of disease-relevant changes in histone modification occupancy.
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Project description:Epigenomic profiling by ChIP-seq is a prevailing methodology used to investigate chromatin-based regulation in biological systems, such as human disease, yet the lack of an empirical methodology to normalize amongst experiments has limited the usefulness of this technique. Here we describe a “spike-in” normalization method that allows the quantitative comparison of histone modification status across cell populations using defined quantities of a reference epigenome. We demonstrate the utility of this method in measuring epigenomic changes following chemical perturbations and show how control normalization of ChIP-seq experiments enables discovery of disease-relevant changes in histone modification occupancy. ChIP-Seq of histone modifications H3K79me2 and H3K4me3 in human samples treated with EPZ-5676 with/without reference epigenome spike-in.
2014-10-30 | E-GEOD-60104 | biostudies-arrayexpress
Project description:This study aims to assess the reliability of spike-in normalization for analyzing single-cell RNA sequencing data. This is done by performing mixture experiments where two different sets of spike-in RNA (ERCC and SIRV) are added separately to a single mouse cell (416B or trophoblast stem cells (TSCs)), followed by generation of sequencing libraries using a modified version of the Smart-seq2 protocol. The aim is to measure the variance of the log-ratio of the total counts between the two spike-in sets. This will quantify how precisely the spike-in RNA was added to each well. As a control, addition was also performed with a premixed solution of both spike-ins, to quantify the variability in the log-ratios due to the experimental protocol. The same data can also be used to measure the well-to-well variability in the differences in behaviour between the two spike-in sets. The data contain four batches of libraries (block), using different batches of cells that were processed and sequenced separately. Each batch contains libraries with all three types of spike-in addition (ERCC+SIRV, SIRV+ERCC or Premixed). The 416B cells also contain a CBFB-MYH11 oncogene, which is expressed in half of the cells (Induced) and silent in the other half (Control).
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