Differences in the experimental conditions (i.e. cells, antibody, drug treatment) and methodologies (ChIP-chip versus ChIP-PET) between the studies may account for the limited overlaps.
In particular, the use of DNA microarray methodology (ChIP-on-chip) allows for high-throughput analysis of thousands of genomic sequences simultaneously [ 3].
We present a new architecture level unified reliability evaluation methodology for chip multiprocessors (CMPs).
With the development of high throughput methodologies such as ChIP-chip (reviewed in [17]) and more recently ChIP-seq (e.g. [18], [19]), it has become possible to comprehensively map regions in the genome of mammalian cells that are occupied by TFs of interest.
We have selected this regulon to validate our methodology for ChIP-seq data analysis.
We describe a robust, simple and scalable methodology for ChIP-seq of low-abundant cell populations, verified down to 10,000 cells.
This is the closest methodology to ChIP-seq, but its mapping precision is lower, and the dynamic range of the readout is significantly less.
To investigate if our methodology allows ChIP-seq on limited cell numbers, we transplanted a new cohort of mice with the leukemic strain also used in the above and FACS-isolated batches of 10,000 GMP-blasts.
Our results also provide a comparison of ChIP methodologies that can overcome limitations commonly encountered in these types of studies while highlighting the complications of assigning in vivo functions to identified target sites.
Indeed with the surge in the use of ChIP methodologies, many companies now sell ChIP-validated antibodies.
The comparison of the ChIP methodologies described above demonstrates that the modified ChIP method is less sensitive.
