![]() For Table 3, we pruned the list of top-ranked, enriched GO terms of closely related terms for presentation by removing terms whose parents, children or siblings in the ontology tree were present at a higher rank in the list. Using the 209 reported differentially expressed genes, we tested for GO term enrichment (over-representation) with the R package goseq (19). Finally, genes with False Discovery Rate (FDR) < 0.05 were called significant (34). A custom maximum likelihood approach was used to calculate P -values for the observed change in gene expression between DEX-treated and ethanol-treated cells. Briefly, in (47), gene expression levels were estimated using ERANGE to calculate reads per kilobase per million tags sequenced (RPKM) values, which were then adjusted for dependence of variance on expression level. (47) identified 209 genes as differentially expressed based on RNA-seq data from A549 cells that were treated for 1 h with 100 mM of Dexamethasone (DEX) or with 0.02% Ethanol control (EtOH). In (47), sequence reads of 36-mer length were generated from Illumina GA1, aligned using ELAND, and peaks were called using MACS. We applied ChIP-Enrich to ChIP-seq peaks for GR ␣ data from the A549 cell line from Reddy et al. This is similar to the first scenario, but preserves the relationship between locus length and GO term membership. bin’ scenario, we first order the data by locus length and then randomly permute peak count and locus length as a unit, but restrict this permutation within successive bins of gene locus length (100 genes per bin). The majority of GO terms that overlap between ‘ ≤ 1 kb from TSS’ and ‘nearest TSS’ are related to fatty acid metabolism, reactive oxygen species and unfolded proteins, or blood coagulation. Vasculature development and related GO terms (triangles). GO terms enriched and FDR ≤ 0.05: for Y-axis test only (green) for X-axis test only (blue) for X- and Y-axis tests (orange) for neither (black). (f) Many enriched RNA-seq terms would have been missed in the ChIP-seq data if only peaks in promoter regions were considered. ( d )–( f ) Comparison of –log 10 ( P -values) for GO term enrichment tests based on ChIP-seq data (ChIP-Enrich) and / or RNA-seq (GOseq) data. ( c ) Using the top 195 ranked terms for each test, FET and the binomial test have more overlap with ChIP-Enrich than with each other. ( b ) Using the ‘nearest TSS’ locus definition with GR ␣ results in more overlapping terms with RNA-seq results than using ‘ ≤ 1 kb from TSS’. See Figure 2(4a) and (b) for further details. ( a ) Observed spline fit for GR ␣ fits neither FET nor the binomial test assumption (orange) bar plot of the proportion of peaks at different distances from the TSS. Enriched GO terms for differentially expressed transcripts and GR ␣ binding following 100-nM DEX treatment show stronger overlap using the ‘nearest TSS’ locus definition than using the ‘ ≤ 1 kb from TSS’ definition. Comparison of GR ␣ enrichment results for ChIP-seq (using two locus definitions) and RNA-seq data from A549 cells. ( b ) Bar plot of the proportion of peaks found at various distances from the TSS. For visualization only, each point is the proportion of genes that are assigned a peak within sequential bins of 25 genes. Expected line if the number of peaks observed is proportional to locus length (light gray, binomial test assumption). Expected line if no relationship between log 10 locus length and proportion of genes with a peak (dark gray, satisfies Fisher’s exact test assumptions). ( a ) Plot of observed spline fit for log 10 locus length versus proportion of genes with a peak (orange). (3) Gene set enrichment is performed for each gene set using a logistic regression model, adjusting for locus length with a binomial cubic smoothing spline term (represented as f in the model equation). (2) It is determined whether ≥ 1 peak is present in each gene locus. Definitions include: ‘nearest gene’, ‘ ≤ 1kb from TSS’ and ‘nearest TSS’. (1) ChIP-seq peaks are assigned to genes using a chosen gene locus definition.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |