#HOMER ANNOTATE PEAKS CODE#

Plot Homer peak annotation results files = list.files(path = '/group/card2/Evangelyn_Sim/Collaboration_Kev_UoM/Sequencing_ATAC_RNA/20190530_ATAC_run1/R/2.pks/4.pkstats/', pattern = '.stats.txt', full.names = T)įiles '/group/card2/Evangelyn_Sim/Collaboration_Kev_UoM/Sequencing_ATAC_RNA/20190530_ATAC_run1/R/2.pks/4.pkstats//edgeR_atac_cov2_.' Res]= mutate(res], FDRdn= nrow(mxFDR_Dn)) Res]= mutate(res], FDRup= nrow(mxFDR_Up)) Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes. Untracked: output/mrna_fulllen_pe_strrev.mx.fix_filt Untracked: output/mouseATAC_peaks_.mx.fix_filt Therefore, it is reasonable to use annotatePeakInBatch or annoPeaks to annotate the peaks to the promoter regions of Hg19 genes. Untracked: output/logCPM_mrna_fulllen_pe_strrev.mx.fix_filt.csv As shown from the distribution of aggregated peak numbers around TSS and the distribution of peaks in different of chromosome regions, most of the peaks locate around TSS. Untracked: output/edgeR_rna_LacZvsYap.xls Untracked: output/edgeR_atac_cov2_LacZvsYap.xls Untracked: output/YAP_shRNA_D28_Proteomics_results.xls Untracked: Mus_musculus.GRCm38.96.fulllength.saf Below is the status of the Git repository when the results were generated: workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). See the Past versions tab to see a history of the changes made to the R Markdown and HTML files. The results in this page were generated with repository version 704a4cf.

#HOMER ANNOTATE PEAKS CODE#

Tracking code development and connecting the code version to the results is critical for reproducibility. 版权声明：本文为博主原创文章，遵循 CC 4.Great! You are using Git for version control. Total continuous domains: 26 (Up) and 24 (Down) Using limma to calculate differential expression/enrichment. Will report raw counts in output table (no normalization) Treating input as file generated by (-peaks) Removed 0 with missing data (out of 103857) To capture annotation stats in a file, use '-annStats ' next timeĪnnotating. Your machine ran out of memory: consider hitting ctrl+C and rerunning NOTE: If this part takes more than 2 minutes, there is a good chance Peaks with misformatted strand: 0 (should be either +/- or 0/1)Īnnotation Number of peaks Total size (bp) Log2 Ratio (obs/exp) LogP enrichment (+values depleted) The output file is a HOMER-style peak file that contains several columns of annotation, normalized read counts, and differential enrichment statistics from DESeq2 for each peak. Peaks with misformatted coordinates: 0 (should be integer) -t Oct4-r1/ Oct4-r2/ -i Input-r1/ Input-r2/ -genome hg19 > outputPeaks.txt. Peaks lacking information: 0 (need at least 5 columns per peak) data/zhangyong/yyp/yypold/hic/hicdata/pca/WT_GM_BL-HiC_1.bedGraph data/zhangyong/yyp/yypold/hic/hicdata/pca/WT_DM_BL-HiC_1.bedGraph

Will remove rows with data values of '' or 'NA' outputstep3.txt DM DM GM GM -pc1 -export outputPrefix > output2Diff.txt Peak file = /data/zhangyong/yyp/yypold/hic/hicdata/validpairs/valid/WT_DM_BL-HiC_Rep1.allValidPairs-HiC/WT_DM_BL-HiC_1.txt # input is matrix data - first column is TAD id, others are TAD inclusion scores

# basic script for running limma for PC1/TADs (generated by HOMER) # !!! Warnining - something likely failed during R execution.

Homer annotate peaks