Last updated: 2022-03-16
Checks: 7 0
Knit directory: chipseq-cross-species/
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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/mouse_dunnart_data_processing_for_comparison.Rmd) and HTML (docs/mouse_dunnart_data_processing_for_comparison.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
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| Rmd | 040a6a7 | lecook | 2022-03-16 | wflow_publish(“analysis/mouse_dunnart_data_processing_for_comparison.Rmd”) |
| html | f593bed | lecook | 2022-03-16 | Build site. |
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| Rmd | faabd95 | lecook | 2022-03-03 | updated |
| Rmd | 2103ae7 | lecook | 2022-03-03 | updates |
| Rmd | 323d8b6 | lecook | 2022-03-03 | copied scripts over |
| Rmd | ae523af | lecook | 2022-03-02 | fix code formatting for bam coverage rule |
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| Rmd | 784c4ec | lecook | 2022-03-01 | update |
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| Rmd | 5fb3661 | lecook | 2022-03-01 | clean up |
| Rmd | c2eeed7 | lecook | 2022-02-28 | debugged |
See mouse_data_ENCODE for details on these samples.
xargs -L 1 curl -O -J -L < ENCODE_files.txt
xargs -L 1 curl -O -J -L < control_files.txt
Uses samtools and picards MarkDuplicates to remove low quality reads. This is based on and in accordance with the ENCODE Guidelines and pipeline (https://github.com/ENCODE-DCC/chip-seq-pipeline2)
Library Complexity ChIP-seq Standards:
| PBC1 | PBC2 | Bottlenecking level | NRF | Complexity | Flag colors |
|---|---|---|---|---|---|
| < 0.5 | < 1 | Severe | < 0.5 | Concerning | Orange |
| 0.5 ≤ PBC1 < 0.8 | 1 ≤ PBC2 < 3 | Moderate | 0.5 ≤ NRF < 0.8 | Acceptable | Yellow |
| 0.8 ≤ PBC1 < 0.9 | 3 ≤ PBC2 < 10 | Mild | 0.8 ≤ NRF < 0.9 | Compliant | None |
| ≥ 0.9 | ≥ 10 | None | > 0.9 | Ideal | None |
See full snakemake script for details: code/mouse_peak_calling/mouse_H3K4me3 and code/mouse_peak_calling/mouse_H3K27ac
Table. Read alignment quality metrics before and aftering filtering steps
| read counts | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| replicate | antibody | stage | accession ID | bwa alignment |
filtered readŝ |
remove duplicates |
NRF* | PBC1* | PBC2* |
| 1 | H3K27ac | E10.5 | ENCFF213EBC | 86919825 | 74296920 | 61061524 | 0.83 | 0.83 | 5.53 |
| 2 | H3K27ac | E10.5 | ENCFF548BRR | 49113729 | 43572898 | 38069875 | 0.88 | 0.88 | 8.03 |
| 1 | H3K27ac | E11.5 | ENCFF512SFE | 1714339 | 12827968 | 11879316 | 0.93 | 0.93 | 13.76 |
| 2 | H3K27ac | E11.5 | ENCFF515PKL | 18419756 | 13753883 | 11961286 | 0.88 | 0.88 | 7.7 |
| 2 | H3K27ac | E12.5 | ENCFF011NFM | 41510259 | 32754035 | 28442356 | 0.88 | 0.88 | 7.55 |
| 1 | H3K27ac | E13.5 | ENCFF194ORC | 47508791 | 39115139 | 23235076 | 0.64 | 0.62 | 2.49 |
| 2 | H3K27ac | E13.5 | ENCFF290ZNF | 46476048 | 37416425 | 26624266 | 0.74 | 0.73 | 3.52 |
| 1 | H3K27ac | E14.5 | ENCFF327VAO | 37480089 | 30104464 | 19228162 | 0.66 | 0.64 | 2.53 |
| 2 | H3K27ac | E14.5 | ENCFF902HAR | 27840473 | 22156787 | 15203030 | 0.69 | 0.67 | 2.68 |
| 1 | H3K27ac | E15.5 | ENCFF584JFB | 51675307 | 40125566 | 35551034 | 0.9 | 0.9 | 9.61 |
| 2 | H3K27ac | E15.5 | ENCFF707WKL | 38499223 | 30334974 | 27522173 | 0.92 | 0.92 | 11.76 |
| 1 | H3K4me3 | E10.5 | ENCFF124UYX | 74283697 | 65480729 | 47429840 | 0.73 | 0.76 | 4.51 |
| 2 | H3K4me3 | E10.5 | ENCFF045IPK | 39305102 | 34283317 | 27327155 | 0.8 | 0.82 | 5.7 |
| 1 | H3K4me3 | E11.5 | ENCFF760QYZ | 24048599 | 17547752 | 16515484 | 0.95 | 0.95 | 20.21 |
| 2 | H3K4me3 | E11.5 | ENCFF717QDV | 19425608 | 14136366 | 13504654 | 0.96 | 0.97 | 26.71 |
| 1 | H3K4me3 | E12.5 | ENCFF182ZPF | 37674883 | 30140587 | 26489691 | 0.89 | 0.89 | 9.29 |
| 2 | H3K4me3 | E12.5 | ENCFF941QJZ | 38463605 | 29985012 | 26459778 | 0.89 | 0.9 | 9.44 |
| 1 | H3K4me3 | E13.5 | ENCFF485UDC | 47478873 | 38287309 | 33094082 | 0.89 | 0.9 | 10.81 |
| 2 | H3K4me3 | E13.5 | ENCFF124TAB | 47598002 | 38139564 | 33020017 | 0.89 | 0.91 | 11.12 |
| 1 | H3K4me3 | E14.5 | ENCFF724DMU | 25402316 | 18964886 | 17278836 | 0.92 | 0.93 | 13.9 |
| 2 | H3K4me3 | E14.5 | ENCFF665QBJ | 28852674 | 22484958 | 19804325 | 0.9 | 0.9 | 10.56 |
| 1 | H3K4me3 | E15.5 | ENCFF258KCR | 55588923 | 44138244 | 38278946 | 0.89 | 0.91 | 12.05 |
| 2 | H3K4me3 | E15.5 | ENCFF401BKM | 42617927 | 34005723 | 29687861 | 0.9 | 0.91 | 12.13 |
| 1 | input control | E10.5 | ENCFF157KEH | 75962416 | 57382820 | 55915261 | 0.98 | 0.98 | 45.2 |
| 2 | input control | E10.5 | ENCFF825AVI | 70250734 | 53358758 | 51796823 | 0.98 | 0.98 | 38.64 |
| 1 | input control | E11.5 | ENCFF184CUE | 14581637 | 10190363 | 10031334 | 0.99 | 0.99 | 69.67 |
| 2 | input control | E11.5 | ENCFF376FGM | 16001082 | 11239845 | 11033934 | 0.99 | 0.99 | 59.63 |
| 1 | input control | E12.5 | ENCFF203JQV | 74367126 | 54966177 | 52895081 | 0.97 | 0.97 | 29.47 |
| 2 | input control | E12.5 | ENCFF058AUT | 68220307 | 50400902 | 48480815 | 0.97 | 0.97 | 29.1 |
| 1 | input control | E13.5 | ENCFF117QRC | 77084648 | 56275163 | 53582563 | 0.97 | 0.97 | 30.93 |
| 2 | input control | E13.5 | ENCFF248PGK | 66492732 | 48343406 | 46564874 | 0.98 | 0.98 | 38.51 |
| 1 | input control | E14.5 | ENCFF784ORI | 35480589 | 25431770 | 24573359 | 0.97 | 0.97 | 32.34 |
| 2 | input control | E14.5 | ENCFF002HZV | 33021720 | 23658223 | 23199516 | 0.99 | 0.99 | 57.52 |
| 1 | input control | E15.5 | ENCFF727QTS | 72318210 | 51828288 | 50444903 | 0.98 | 0.99 | 52.73 |
| 2 | input control | E15.5 | ENCFF182XFG | 86322714 | 63335464 | 60305840 | 0.97 | 0.97 | 28.35 |
̂ excluded low quality (MAPQ30) and orphaned reads
This is so we can compare to mouse peaks.
Based on https://davemcg.github.io/post/easy-bam-downsampling/ script for doing this.
Run script in the directory with the files you want to subsample.
cd output/bam_files/
bash subsample.sh
plotCorrelation computes the overall similarity between two or more files based on read coverage (or other scores) within genomic regions.
This helps to determine whether the different sample types can be separated, i.e., samples of different conditions are expected to be more dissimilar to each other than replicates within the same condition.
This tool samples indexed BAM files and plots a profile of cumulative read coverages for each. All reads overlapping a window (bin) of the specified length are counted; these counts are sorted and the cumulative sum is finally plotted.
It determines how well the signal in the ChIP-seq sample can be differentiated from the background distribution of reads in the control sample.
An ideal input with perfect uniform distribution of reads along the genome (i.e. without enrichments in open chromatin etc.) and infinite sequencing coverage should generate a straight diagonal line. A very specific and strong ChIP enrichment will be indicated by a prominent and steep rise of the cumulative sum towards the highest rank. This means that a big chunk of reads from the ChIP sample is located in few bins which corresponds to high, narrow enrichments typically seen for transcription factors.
Information from: https://docs.google.com/document/d/1lG_Rd7fnYgRpSIqrIfuVlAz2dW1VaSQThzk836Db99c/edit
This set of programs operate on mapped Illumina single-end read datasets in tagAlign or BAM format. Because my data is paired-end I need to only use the forward read.
A high-quality ChIP-seq experiment will produce significant clustering of enriched DNA sequence tags/reads at locations bound by the protein of interest; the expectation is that we can observe a bimodal enrichment of reads (sequence tags) on both the forward and the reverse strands.
Cross-correlation analysis is done on a filtered (but not-deduped) and subsampled BAM. There is a special fastq trimming for cross-correlation analysis. Read1 fastq is trimmed to 50bp first using trimfastq.py (last modified 2017/11/08, https://github.com/ENCODE-DCC/chip-seq-pipeline2/blob/master/src/trimfastq.py). And then it is separately mapped as SE. Reads are filtered but duplicates are not removed. Then 15 million reads are randomly sampled and used for cross-correlation analysis.
ENCODE standards:
| col. | abbreviation | description |
|---|---|---|
| 1 | Filename | tagAlign/BAM filename |
| 2 | numReads | effective sequencing depth i.e. total number of mapped reads in input file |
| 3 | estFragLen | comma separated strand cross-correlation peak(s) in decreasing order of correlation. |
| 4 | corr_estFragLen | comma separated strand cross-correlation value(s) in decreasing order (COL2 follows the same order) |
| 5 | phantomPeak | Read length/phantom peak strand shift |
| 6 | corr_phantomPeak | Correlation value at phantom peak |
| 7 | argmin_corr | strand shift at which cross-correlation is lowest |
| 8 | min_corr | minimum value of cross-correlation |
| 9 | NSC | Normalized strand cross-correlation coefficient (NSC) = COL4 / COL8 |
| 10 | RSC | Relative strand cross-correlation coefficient (RSC) = (COL4 - COL8) / (COL6 - COL8) |
| 11 | QualityTag | Quality tag based on thresholded RSC (codes= -2:veryLow, -1:Low, 0:Medium, 1:High, 2:veryHigh) |
NSC; NSC>1.1 (higher values indicate more enrichment; 1 = no enrichment)
RSC; RSC>0.8 (0 = no signal; <1 low quality ChIP; >1 high enrichment
Quality tag based on thresholded RSC (codes: -2:veryLow,-1:Low,0:Medium,1:High; 2:veryHigh)
Table. Peak calling quality metrics for mouse ChIP-seq peaks after peak calling with MACS2
replicate |
antibody | stage | accession ID | number of peaks |
FRiP ̂ | NSC* | RSC* | Quality Tag* |
% replicate reproducibility |
number of consensus peaks |
FRiP^ for consensus peaks |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | H3K27ac | E10.5 | ENCFF213EBC | 61169 | 0.12 | 1.11 | 1.15 | 1 | 45.27 | 27688 | 0.14 |
| 2 | H3K27ac | E10.5 | ENCFF548BRR | 80654 | 0.19 | 1.19 | 1.23 | 1 | 34.33 | ||
| 1 | H3K27ac | E11.5 | ENCFF512SFE | 25352 | 0.07 | 1.08 | 1.61 | 2 | 47.93 | 12149 | 0.06 |
| 2 | H3K27ac | E11.5 | ENCFF515PKL | 23732 | 0.06 | 1.09 | 1.97 | 2 | 51.2 | ||
| 1 | H3K27ac | E12.5 | ENCFF394TZN | 27242 | 0.07 | 1.08 | 1.59 | 2 | 58.17 | 15845 | 0.08 |
| 2 | H3K27ac | E12.5 | ENCFF011NFM | 62319 | 0.11 | 1.09 | 1.49 | 1 | 25.43 | ||
| 1 | H3K27ac | E13.5 | ENCFF194ORC | 85874 | 0.18 | 1.19 | 2.14 | 2 | 35.72 | 30671 | 0.13 |
| 2 | H3K27ac | E13.5 | ENCFF290ZNF | 71246 | 0.13 | 1.13 | 2.05 | 2 | 43.05 | ||
| 1 | H3K27ac | E14.5 | ENCFF327VAO | 45785 | 0.15 | 1.19 | 1.65 | 2 | 48.56 | 22232 | 0.14 |
| 2 | H3K27ac | E14.5 | ENCFF902HAR | 44042 | 0.14 | 1.16 | 1.72 | 2 | 50.48 | ||
| 1 | H3K27ac | E15.5 | ENCFF584JFB | 35724 | 0.09 | 1.08 | 1.49 | 1 | 51.08 | 18246 | 0.09 |
| 2 | H3K27ac | E15.5 | ENCFF707WKL | 37600 | 0.1 | 1.1 | 1.54 | 2 | 48.53 | ||
| 1 | H3K4me3 | E10.5 | ENCFF124UYX | 29478 | 0.44 | 2.28 | 1.12 | 1 | 70.77 | 20860 | 0.47 |
| 2 | H3K4me3 | E10.5 | ENCFF045IPK | 26820 | 0.49 | 2.47 | 1.15 | 1 | 77.78 | ||
| 1 | H3K4me3 | E11.5 | ENCFF760QYZ | 28388 | 0.34 | 1.86 | 1.25 | 1 | 66.43 | 18857 | 0.33 |
| 2 | H3K4me3 | E11.5 | ENCFF717QDV | 28368 | 0.33 | 1.81 | 1.24 | 1 | 66.48 | ||
| 1 | H3K4me3 | E12.5 | ENCFF182ZPF | 29466 | 0.33 | 1.93 | 1.21 | 1 | 66.35 | 19549 | 0.32 |
| 2 | H3K4me3 | E12.5 | ENCFF941QJZ | 30868 | 0.31 | 1.67 | 1.21 | 1 | 63.34 | ||
| 1 | H3K4me3 | E13.5 | ENCFF485UDC | 29715 | 0.4 | 2.16 | 1.24 | 1 | 69.78 | 20734 | 0.41 |
| 2 | H3K4me3 | E13.5 | ENCFF124TAB | 29547 | 0.41 | 2.19 | 1.24 | 1 | 70.18 | ||
| 1 | H3K4me3 | E14.5 | ENCFF724DMU | 24250 | 0.5 | 2.34 | 1.26 | 1 | 81.08 | 19660 | 0.53 |
| 2 | H3K4me3 | E14.5 | ENCFF665QBJ | 25084 | 0.55 | 2.54 | 1.26 | 1 | 78.38 | ||
| 1 | H3K4me3 | E15.5 | ENCFF258KCR | 23365 | 0.36 | 2.25 | 1.29 | 1 | 80.11 | 18717 | 0.39 |
| 2 | H3K4me3 | E15.5 | ENCFF401BKM | 23920 | 0.42 | 2.47 | 1.33 | 1 | 78.25 |
* computed from 15M reads subsampled ̂ fraction of reads in peaks
echo "Number of peaks A3 H3K27ac dunnart"
less output/peaks/A-3_H3K27ac_vs_A-1_input_macs2_default_dunnart_downSampled_peaks.narrowPeak | wc -l
echo "Number of peaks A2 H3K4me3 dunnart"
less output/peaks/A-2_H3K4me3_vs_A-1_input_macs2_default_dunnart_downSampled_peaks.narrowPeak | wc -l
echo "Number of peaks B3 H3K27ac dunnart"
less output/peaks/B-3_H3K27ac_vs_B-1_input_macs2_default_dunnart_downSampled_peaks.narrowPeak | wc -l
echo "Number of peaks B2 H3K4me3 dunnart"
less output/peaks/B-2_H3K4me3_vs_B-1_input_macs2_default_dunnart_downSampled_peaks.narrowPeak | wc -l
Number of peaks A3 H3K27ac dunnart
74012
Number of peaks A2 H3K4me3 dunnart
51122
Number of peaks B3 H3K27ac dunnart
78381
Number of peaks B2 H3K4me3 dunnart
52680
H3K4me3
echo "Number of peaks rep 1 E10.5 H3K4me3"
less output/peaks/ENCFF124UYX_vs_ENCFF157KEH_E10.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E10.5 H3K4me3"
less output/peaks/ENCFF045IPK_vs_ENCFF825AVI_E10.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E11.5 H3K4me3"
less output/peaks/ENCFF760QYZ_vs_ENCFF184CUE_E11.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E11.5 H3K4me3"
less output/peaks/ENCFF717QDV_vs_ENCFF376FGM_E11.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E12.5 H3K4me3"
less output/peaks/ENCFF941QJZ_vs_ENCFF058AUT_E12.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E12.5 H3K4me3"
less output/peaks/ENCFF182ZPF_vs_ENCFF203JQV_E12.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E13.5 H3K4me3"
less output/peaks/ENCFF485UDC_vs_ENCFF117QRC_E13.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E13.5 H3K4me3"
less output/peaks/ENCFF124TAB_vs_ENCFF248PGK_E13.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E14.5 H3K4me3"
less output/peaks/ENCFF665QBJ_vs_ENCFF002HZV_E14.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E14.5 H3K4me3"
less output/peaks/ENCFF724DMU_vs_ENCFF784ORI_E14.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E15.5 H3K4me3"
less output/peaks/ENCFF401BKM_vs_ENCFF182XFG_E15.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E15.5 H3K4me3"
less output/peaks/ENCFF258KCR_vs_ENCFF727QTS_E15.5_H3K4me3_macs2_peaks.narrowPeak | wc -l
Number of peaks rep 1 E10.5 H3K4me3
55445
Number of peaks rep 2 E10.5 H3K4me3
38397
Number of peaks rep 1 E11.5 H3K4me3
22460
Number of peaks rep 2 E11.5 H3K4me3
24565
Number of peaks rep 1 E12.5 H3K4me3
31761
Number of peaks rep 2 E12.5 H3K4me3
30108
Number of peaks rep 1 E13.5 H3K4me3
31939
Number of peaks rep 2 E13.5 H3K4me3
31198
Number of peaks rep 1 E14.5 H3K4me3
29300
Number of peaks rep 2 E14.5 H3K4me3
27830
Number of peaks rep 1 E15.5 H3K4me3
29726
Number of peaks rep 2 E15.5 H3K4me3
30338
H3K27ac
echo "Number of peaks rep 1 E10.5 H3K27ac"
less output/peaks/ENCFF213EBC_vs_ENCFF157KEH_E10.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E10.5 H3K27ac"
less output/peaks/ENCFF548BRR_vs_ENCFF825AVI_E10.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E11.5 H3K27ac"
less output/peaks/ENCFF512SFE_vs_ENCFF184CUE_E11.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E11.5 H3K27ac"
less output/peaks/ENCFF515PKL_vs_ENCFF376FGM_E11.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E12.5 H3K27ac"
less output/peaks/ENCFF011NFM_vs_ENCFF058AUT_E12.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E12.5 H3K27ac"
less output/peaks/ENCFF394TZN_vs_ENCFF203JQV_E12.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E13.5 H3K27ac"
less output/peaks/ENCFF194ORC_vs_ENCFF117QRC_E13.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E13.5 H3K27ac"
less output/peaks/ENCFF290ZNF_vs_ENCFF248PGK_E13.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E14.5 H3K27ac"
less output/peaks/ENCFF902HAR_vs_ENCFF002HZV_E14.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E14.5 H3K27ac"
less output/peaks/ENCFF327VAO_vs_ENCFF784ORI_E14.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 1 E15.5 H3K27ac"
less output/peaks/ENCFF707WKL_vs_ENCFF182XFG_E15.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
echo "Number of peaks rep 2 E15.5 H3K27ac"
less output/peaks/ENCFF584JFB_vs_ENCFF727QTS_E15.5_H3K27ac_macs2_peaks.narrowPeak | wc -l
Number of peaks rep 1 E10.5 H3K27ac
85382
Number of peaks rep 2 E10.5 H3K27ac
129598
Number of peaks rep 1 E11.5 H3K27ac
34848
Number of peaks rep 2 E11.5 H3K27ac
24298
Number of peaks rep 1 E12.5 H3K27ac
93296
Number of peaks rep 2 E12.5 H3K27ac
93314
Number of peaks rep 1 E13.5 H3K27ac
108905
Number of peaks rep 2 E13.5 H3K27ac
109580
Number of peaks rep 1 E14.5 H3K27ac
85604
Number of peaks rep 2 E14.5 H3K27ac
85427
Number of peaks rep 1 E15.5 H3K27ac
106242
Number of peaks rep 2 E15.5 H3K27ac
107377
echo "Number of consensus H3K4me3 dunnart peaks"
less output/peaks/H3K4me3_overlap_default_dunnart_downSampled_peaks.narrowPeak | wc -l
echo "Number of consensus H3K27ac dunnart peaks"
less output/peaks/H3K27ac_overlap_default_dunnart_downSampled_peaks.narrowPeak | wc -l
Number of consensus H3K4me3 dunnart peaks
27902
Number of consensus H3K27ac dunnart peaks
40610
echo "Number of consensus H3K4me3 mouse E10.5 peaks"
less output/peaks/H3K4me3_E10.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K4me3 mouse E11.5 peaks"
less output/peaks/H3K4me3_E11.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K4me3 mouse E12.5 peaks"
less output/peaks/H3K4me3_E12.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K4me3 mouse E13.5 peaks"
less output/peaks/H3K4me3_E13.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K4me3 mouse E14.5 peaks"
less output/peaks/H3K4me3_E14.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K4me3 mouse E15.5 peaks"
less output/peaks/H3K4me3_E15.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K27ac mouse E10.5 peaks"
less output/peaks/H3K27ac_E10.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K27ac mouse E11.5 peaks"
less output/peaks/H3K27ac_E11.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K27ac mouse E12.5 peaks"
less output/peaks/H3K27ac_E12.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K27ac mouse E13.5 peaks"
less output/peaks/H3K27ac_E13.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K27ac mouse E14.5 peaks"
less output/peaks/H3K27ac_E14.5_overlap.narrowPeak | wc -l
echo "Number of consensus H3K27ac mouse E15.5 peaks"
less output/peaks/H3K27ac_E15.5_overlap.narrowPeak | wc -l
Number of consensus H3K4me3 mouse E10.5 peaks
28512
Number of consensus H3K4me3 mouse E11.5 peaks
18112
Number of consensus H3K4me3 mouse E12.5 peaks
21756
Number of consensus H3K4me3 mouse E13.5 peaks
23929
Number of consensus H3K4me3 mouse E14.5 peaks
22102
Number of consensus H3K4me3 mouse E15.5 peaks
23375
Number of consensus H3K27ac mouse E10.5 peaks
52138
Number of consensus H3K27ac mouse E11.5 peaks
13996
Number of consensus H3K27ac mouse E12.5 peaks
40281
Number of consensus H3K27ac mouse E13.5 peaks
51183
Number of consensus H3K27ac mouse E14.5 peaks
40264
Number of consensus H3K27ac mouse E15.5 peaks
52152
Find uniquely H3K4me3 sites (i.e. peaks that don’t overlap with H3K27ac):
conda activate chip
bedtools intersect -v -a output/peaks/H3K4me3_E10.5_overlap.narrowPeak -b output/peaks/H3K27ac_E10.5_overlap.narrowPeak > output/peaks/H3K4me3_E10.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K4me3_E11.5_overlap.narrowPeak -b output/peaks/H3K27ac_E11.5_overlap.narrowPeak > output/peaks/H3K4me3_E11.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K4me3_E12.5_overlap.narrowPeak -b output/peaks/H3K27ac_E12.5_overlap.narrowPeak > output/peaks/H3K4me3_E12.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K4me3_E13.5_overlap.narrowPeak -b output/peaks/H3K27ac_E13.5_overlap.narrowPeak > output/peaks/H3K4me3_E13.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K4me3_E14.5_overlap.narrowPeak -b output/peaks/H3K27ac_E14.5_overlap.narrowPeak > output/peaks/H3K4me3_E14.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K4me3_E15.5_overlap.narrowPeak -b output/peaks/H3K27ac_E15.5_overlap.narrowPeak > output/peaks/H3K4me3_E15.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K4me3_overlap_default_dunnart_downSampled_peaks.narrowPeak -b output/peaks/H3K27ac_overlap_default_dunnart_downSampled_peaks.narrowPeak > output/peaks/H3K4me3_only_dunnart_downSampled.narrowPeak
Find unique H3K27ac sites (i.e. peaks that don’t overlap with H3K4me3):
bedtools intersect -v -a output/peaks/H3K27ac_E10.5_overlap.narrowPeak -b output/peaks/H3K4me3_E10.5_overlap.narrowPeak > output/peaks/H3K27ac_E10.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K27ac_E11.5_overlap.narrowPeak -b output/peaks/H3K4me3_E11.5_overlap.narrowPeak > output/peaks/H3K27ac_E11.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K27ac_E12.5_overlap.narrowPeak -b output/peaks/H3K4me3_E12.5_overlap.narrowPeak > output/peaks/H3K27ac_E12.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K27ac_E13.5_overlap.narrowPeak -b output/peaks/H3K4me3_E13.5_overlap.narrowPeak > output/peaks/H3K27ac_E13.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K27ac_E14.5_overlap.narrowPeak -b output/peaks/H3K4me3_E14.5_overlap.narrowPeak > output/peaks/H3K27ac_E14.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K27ac_E15.5_overlap.narrowPeak -b output/peaks/H3K4me3_E15.5_overlap.narrowPeak > output/peaks/H3K27ac_E15.5_only.narrowPeak
bedtools intersect -v -a output/peaks/H3K27ac_overlap_default_dunnart_downSampled_peaks.narrowPeak -b output/peaks/H3K4me3_overlap_default_dunnart_downSampled_peaks.narrowPeak > output/peaks/H3K27ac_only_dunnart_downSampled.narrowPeak
Find peaks common between H3K27ac & H3K4me3 with a reciprocal overlap of at least 50%.
bedtools intersect -f 0.5 -r -a output/peaks/H3K4me3_E10.5_overlap.narrowPeak -b output/peaks/H3K27ac_E10.5_overlap.narrowPeak > output/peaks/H3K4me3_and_H3K27ac_E10.5.narrowPeak
bedtools intersect -f 0.5 -r -a output/peaks/H3K4me3_E11.5_overlap.narrowPeak -b output/peaks/H3K27ac_E11.5_overlap.narrowPeak > output/peaks/H3K4me3_and_H3K27ac_E11.5.narrowPeak
bedtools intersect -f 0.5 -r -a output/peaks/H3K4me3_E12.5_overlap.narrowPeak -b output/peaks/H3K27ac_E12.5_overlap.narrowPeak > output/peaks/H3K4me3_and_H3K27ac_E12.5.narrowPeak
bedtools intersect -f 0.5 -r -a output/peaks/H3K4me3_E13.5_overlap.narrowPeak -b output/peaks/H3K27ac_E13.5_overlap.narrowPeak > output/peaks/H3K4me3_and_H3K27ac_E13.5.narrowPeak
bedtools intersect -f 0.5 -r -a output/peaks/H3K4me3_E14.5_overlap.narrowPeak -b output/peaks/H3K27ac_E14.5_overlap.narrowPeak > output/peaks/H3K4me3_and_H3K27ac_E14.5.narrowPeak
bedtools intersect -f 0.5 -r -a output/peaks/H3K4me3_E15.5_overlap.narrowPeak -b output/peaks/H3K27ac_E15.5_overlap.narrowPeak > output/peaks/H3K4me3_and_H3K27ac_E15.5.narrowPeak
bedtools intersect -f 0.5 -r -a output/peaks/H3K4me3_overlap_default_dunnart_downSampled_peaks.narrowPeak -b output/peaks/H3K27ac_overlap_default_dunnart_downSampled_peaks.narrowPeak > output/peaks/H3K4me3_H3K27ac_dunnart_downSampled.narrowPeak
Combine peak files
cat output/peaks/H3K4me3_E10.5_only.narrowPeak output/peaks/H3K4me3_and_H3K27ac_E10.5.narrowPeak | sort -k 4,4 > output/peaks/E10.5_promoter_peaks.narrowPeak
cat output/peaks/H3K4me3_E11.5_only.narrowPeak output/peaks/H3K4me3_and_H3K27ac_E11.5.narrowPeak | sort -k 4,4 > output/peaks/E11.5_promoter_peaks.narrowPeak
cat output/peaks/H3K4me3_E12.5_only.narrowPeak output/peaks/H3K4me3_and_H3K27ac_E12.5.narrowPeak | sort -k 4,4 > output/peaks/E12.5_promoter_peaks.narrowPeak
cat output/peaks/H3K4me3_E13.5_only.narrowPeak output/peaks/H3K4me3_and_H3K27ac_E13.5.narrowPeak | sort -k 4,4 > output/peaks/E13.5_promoter_peaks.narrowPeak
cat output/peaks/H3K4me3_E14.5_only.narrowPeak output/peaks/H3K4me3_and_H3K27ac_E14.5.narrowPeak | sort -k 4,4 > output/peaks/E14.5_promoter_peaks.narrowPeak
cat output/peaks/H3K4me3_E15.5_only.narrowPeak output/peaks/H3K4me3_and_H3K27ac_E15.5.narrowPeak | sort -k 4,4 > output/peaks/E15.5_promoter_peaks.narrowPeak
cat output/peaks/H3K4me3_only_dunnart_downSampled.narrowPeak output/peaks/H3K4me3_H3K27ac_dunnart_downSampled.narrowPeak| sort -k 4,4 > output/peaks/dunnart_downSampled_promoter_peaks.narrowPeak
cat output/peaks/H3K27ac_E10.5_only.narrowPeak | sort -k 4,4 > output/peaks/E10.5_enhancer_peaks.narrowPeak
cat output/peaks/H3K27ac_E11.5_only.narrowPeak | sort -k 4,4 > output/peaks/E11.5_enhancer_peaks.narrowPeak
cat output/peaks/H3K27ac_E12.5_only.narrowPeak | sort -k 4,4 > output/peaks/E12.5_enhancer_peaks.narrowPeak
cat output/peaks/H3K27ac_E13.5_only.narrowPeak | sort -k 4,4 > output/peaks/E13.5_enhancer_peaks.narrowPeak
cat output/peaks/H3K27ac_E14.5_only.narrowPeak | sort -k 4,4 > output/peaks/E14.5_enhancer_peaks.narrowPeak
cat output/peaks/H3K27ac_E15.5_only.narrowPeak | sort -k 4,4 > output/peaks/E15.5_enhancer_peaks.narrowPeak
cat output/peaks/H3K27ac_only_dunnart_downSampled.narrowPeak | sort -k 4,4 > output/peaks/dunnart_downSampled_enhancer_peaks.narrowPeak
sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux
Matrix products: default
BLAS/LAPACK: /usr/local/easybuild-2019/easybuild/software/compiler/gcc/10.2.0/openblas/0.3.12/lib/libopenblas_haswellp-r0.3.12.so
locale:
[1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8
[5] LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8
[7] LC_PAPER=en_AU.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.8 jquerylib_0.1.4 pillar_1.6.1 compiler_4.1.0
[5] bslib_0.2.5.1 later_1.2.0 git2r_0.28.0 tools_4.1.0
[9] getPass_0.2-2 digest_0.6.27 jsonlite_1.7.2 evaluate_0.14
[13] lifecycle_1.0.1 tibble_3.1.2 pkgconfig_2.0.3 rlang_1.0.2
[17] cli_2.5.0 rstudioapi_0.13 yaml_2.2.1 xfun_0.23
[21] httr_1.4.2 stringr_1.4.0 knitr_1.33 sass_0.4.0
[25] fs_1.5.0 vctrs_0.3.8 rprojroot_2.0.2 glue_1.4.2
[29] R6_2.5.0 processx_3.5.2 fansi_0.5.0 rmarkdown_2.8
[33] callr_3.7.0 magrittr_2.0.1 whisker_0.4 ps_1.6.0
[37] promises_1.2.0.1 ellipsis_0.3.2 htmltools_0.5.1.1 httpuv_1.6.1
[41] utf8_1.2.1 stringi_1.6.2 crayon_1.4.1