|
| Status |
Public on Oct 20, 2014 |
| Title |
H3K27me3 Pse Rep1 |
| Sample type |
SRA |
| |
|
| Source name |
D. Pseudoobscura_H3K27me3
|
| Organism |
Drosophila pseudoobscura |
| Characteristics |
genotype/variation: wild type
tissue: embryos
age: 4-12 hrs
chip antibody: H3K27me3, Millipore, #07-449
|
| Extracted molecule |
genomic DNA |
| Extraction protocol |
Chromatin prepared from Drosophila embryos was immunoprecipitated with specific antibodies and precipitated DNA was isolated (see mat and methods for details)
Libraries were prepared according to Illumina's instructions
|
| |
|
| Library strategy |
ChIP-Seq |
| Library source |
genomic |
| Library selection |
ChIP |
| Instrument model |
Illumina Genome Analyzer IIx |
| |
|
| Description |
processed data file: dPse_binned_profiles.txt
|
| Data processing |
Mapping - For each ChIP-seq experiment, we mapped short reads (36/50 bps) to the appropriate reference genome using Bowtie-0.12.2 by specifying ‘-a –m 1 -best -strata’ options. Our reference genomes included the heterochromatic fraction of chromosomes and non-assembled contigs, and any read that could be mapped to more than one genomic locus was filtered from further processing.
Pile-up - Mapped tags were extended to 140bp and coverage statistics for 20bp bins over each of the genomes were computed. This was done following analysis of the correlation between coverage in the forward and reverse strands, which indicated peak correlation between the two at an offset of 140bp, suggesting the empirical fragment length assayed by ChIP-seq was 140bp.
Normalizing per-species' mappability - Each species genome contains regions that are non-unique and therefore cannot be profiled using short read tags. We generated a control profile for each species by applying the mapping and binning procedure as described above for all possible 36/50bp subsequences in each of the genomes. We derived mappability tracks for each species, indicating the fraction of fragments covering each 20bp genomic bin that could be mapped uniquely to the respective genome. We then normalized the coverage score of each experiment by dividing it with this mapability value. Regions with mappability lower than 50% were filtered out and marked as Not Mapable in subsequent analysis. Note that unmappable regions were different between the species due to duplications and deletions.
Coverage normalization - To control for ChIP-seq coverage and variable ChIP-seq specificity, we transformed raw coverage values to minus log2 of its (1 - quantile) value For example, a normalize value of 9 indicates coverage is in the top 1-2-9 quantile (e.g. – in the top (1/512)th of the distribution).
Genome_build: dm3,droSim1,droYak2,dp4,droVir3
Supplementary_files_format_and_content: For each species we have a tab-delimited file. Each row represents a position in the appropriate genome (1 value for each 20bp bin). The first and second columns are chromosome and position respectively. Columns 3 on represent different ChIP-Seq experiments. Values represent normalized coverage as described in the data processing step.
|
| |
|
| Submission date |
Aug 15, 2014 |
| Last update date |
May 15, 2019 |
| Contact name |
Bernd Schuettengruber |
| E-mail(s) |
bernd.schuttengruber@igh.cnrs.fr
|
| Organization name |
Institute de Génétique Humaine
|
| Lab |
Cavalli
|
| Street address |
141, rue de la cardonille
|
| City |
Montpellier |
| ZIP/Postal code |
34396 |
| Country |
France |
| |
|
| Platform ID |
GPL17883 |
| Series (1) |
| GSE60428 |
Cooperativity, specificity and evolutionary stability of Polycomb targeting in Drosophila |
|
| Relations |
| BioSample |
SAMN02991151 |
| SRA |
SRX681787 |
