From 0b11f9dfdfbe5affdb8356f5b7e522cb730219a1 Mon Sep 17 00:00:00 2001 From: Jihe Liu <31855167+jihe-liu@users.noreply.github.com> Date: Fri, 27 Jan 2023 14:04:31 -0500 Subject: [PATCH] Add files via upload --- chipQC_diffbind_Jihe/ChIPQCreport/CCPlot.png | Bin 0 -> 238141 bytes .../ChIP QC report: WT and KO.RData | Bin 0 -> 5608 bytes .../ChIP QC report: WT and KO.html | 1187 +++ .../ChIPQCreport/CoverageHistogramPlot.png | Bin 0 -> 254418 bytes .../ChIPQCreport/GenomicFeatureEnrichment.png | Bin 0 -> 256803 bytes .../ChIPQCreport/PeakCorHeatmap.png | Bin 0 -> 25500 bytes chipQC_diffbind_Jihe/ChIPQCreport/PeakPCA.png | Bin 0 -> 26346 bytes .../ChIPQCreport/PeakProfile.png | Bin 0 -> 253828 bytes chipQC_diffbind_Jihe/ChIPQCreport/Rap.png | Bin 0 -> 154668 bytes chipQC_diffbind_Jihe/ChIPQCreport/Rip.png | Bin 0 -> 137777 bytes chipQC_diffbind_Jihe/KO_enriched.bed | 192 + chipQC_diffbind_Jihe/WT_enriched.bed | 7757 +++++++++++++++++ chipQC_diffbind_Jihe/binding_site_overlap.png | Bin 0 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file mode 100644 index 0000000..de35b90 --- /dev/null +++ b/chipQC_diffbind_Jihe/ChIPQCreport/ChIP QC report: WT and KO.html @@ -0,0 +1,1187 @@ + + + + +ChIPQC Report + + + + + +
+ + + + + + + + + + + + + +
+
+
ChIPQC Report
+
+
+Overview +
+
+

+This report was generated using ChIPQC +

+

+The report provides both general and ChIP-seq specific quality metrics and diagnostic graphics to allow for the quantitative assessment of ChIP-seq quality. +

+

+The report is split into three main sections: +

+
    +
  • +

    +QC Summary - Overview of results. +

    +
  • +
  • +

    +QC Results - Full QC results and figures. +

    +
  • +
  • +

    +QC files and versions - Files and program versions used in QC +

    +
  • +
+
+
+
+
+QC Summary +
+
+
+
+

+Table 1.  +Summary of ChIP-seq filtering and quality metrics. +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ID + +Tissue + +Factor + +Condition + +Replicate + +Reads + +Dup% + +ReadL + +FragL + +RelCC + +SSD + +RiP% +
+KO_1_chip + + + +KO + + + +1 + +2560660 + +0 + +50 + +110 + +0.13 + +0.63 + +0.25 +
+KO_1_input + +NA + +NA + +NA + +NA + +2562828 + +0 + +50 + +103 + +0.031 + +5.6 + +NA +
+KO_2_chip + + + +KO + + + +2 + +2254600 + +0 + +50 + +102 + +0.44 + +0.61 + +0.24 +
+KO_2_input + +NA + +NA + +NA + +NA + +2391888 + +0 + +50 + +101 + +0.11 + +0.57 + +NA +
+WT_1_chip + + + +WT + + + +1 + +664649 + +0 + +49 + +196 + +0.6 + +1.9 + +6.3 +
+WT_1_input + +NA + +NA + +NA + +NA + +2690313 + +0 + +50 + +106 + +0.16 + +0.58 + +NA +
+WT_2_chip + + + +WT + + + +2 + +1347881 + +0 + +50 + +189 + +1.5 + +0.72 + +5.3 +
+WT_2_input + +NA + +NA + +NA + +NA + +2780778 + +0 + +50 + +101 + +0.2 + +0.58 + +NA +
+
+

+Table 1contains a summary of filtering and quality metrics generated by + the ChIPQC package. Further information on these metrics, their associated figures and additional quality measures can be found + within the related QC Results subsections. +

+

+A short description of Table 1 metrics is provided below: +

+
    +
  • +

    +ID - Unique sample ID. +

    +
  • +
  • +

    +Tissue/Factor/Condition - Metadata associated to sample. +

    +
  • +
  • +

    +Replicate - Number of replicate within sample group +

    +
  • +
  • +

    +Reads - Number of sample reads within analysed chromosomes. +

    +
  • +
  • +

    +Dup% - Percentage of MapQ filter passing reads marked as duplicates +

    +
  • +
  • +

    +FragLen - Estimated fragment length by cross-coverage method +

    +
  • +
  • +

    +SSD - SSD score (htSeqTools) +

    +
  • +
  • +

    +FragLenCC - Cross-Coverage score at the fragment length +

    +
  • +
  • +

    +RelativeCC - Cross-coverage score at the fragment length over Cross-coverage at the read length +

    +
  • +
  • +

    +RIP% - Percentage of reads wthin peaks +

    +
  • +
  • +

    +RIBL% - Percentage of reads wthin Blacklist regions +

    +
  • +
+
+
+
+
+QC Results +
+
+
+
+Mapping, Filtering and Duplication rate +
+
+

+This section presents the mapping quality, duplication rate and distribution of reads + in known genomic features. +

+
+
+

+Table 2.  +Number and percantage of mapped,duplicated and MapQ filter passing reads +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ID + +Tissue + +Factor + +Condition + +Replicate + +Unmapped + +Mapped + +Pass MapQ Filter and Dup + +Total Dup% + +Pass MapQ Filter% + +Pass MapQ Filter and Dup% +
+KO_1_chip + + + +KO + + + +1 + +0 + +2560660 + +0 + +0 + +100 + +0 +
+KO_1_input + +NA + +NA + +NA + +NA + +0 + +2562828 + +0 + +0 + +100 + +0 +
+KO_2_chip + + + +KO + + + +2 + +0 + +2254600 + +0 + +0 + +100 + +0 +
+KO_2_input + +NA + +NA + +NA + +NA + +0 + +2391888 + +0 + +0 + +100 + +0 +
+WT_1_chip + + + +WT + + + +1 + +0 + +664649 + +0 + +0 + +100 + +0 +
+WT_1_input + +NA + +NA + +NA + +NA + +0 + +2690313 + +0 + +0 + +100 + +0 +
+WT_2_chip + + + +WT + + + +2 + +0 + +1347881 + +0 + +0 + +100 + +0 +
+WT_2_input + +NA + +NA + +NA + +NA + +0 + +2780778 + +0 + +0 + +100 + +0 +
+
+

+Table 2 shows the absolute number of total, mapped, passing MapQ filter and duplicated reads. + The percent of mapped reads passing quality filter and marked as duplicates (Non-Redundant Fraction?) are also included. +

+

+Description of read filtering and flag metrics: +

+
    +
  • +

    +Total Dup%-Percentage of all mapped reads which are marked as duplicates. +

    +
  • +
  • +

    +Pass MapQ Filter%-Percentage of all mapped reads whichpass MapQ quality filter +

    +
  • +
  • +

    +Pass MapQ Filter and Dup%-Percentage of all reads which pass MapQ filter and are marked asduplicates. +

    +
  • +
+

+Duplication rates (Dup %) are dependent on the ChIP library complexity and the number of reads sequenced + Higher duplication rates maybe due to low ChIP efficiency when read counts are lower or conversely + saturation of ChIP signal when sequencing large number of reads. Since this metric is dependent on both read depth + and the properties of the ChIP itself, comparison between biological or technical replicates of similat total read counts can best identify problematic + libraries . + +

+

+Highly mappable (multimappable) positions within the genome can attract large levels of duplication + and so assessment of duplication before and after MapQ quality filtering can identify contribution of + these positions to the duplication rate. + +

+
+
+

+Figure 1.  +Heatmap of log2 enrichment of reads in genomic features +

+
+
+ +
+
+

+The distribution of reads across known genomic features such as genes and their subcomponents + may allow further evaluation of ChIP-seq success and quality. A transcription factor know to + preferentially bind at a genomic feature should show relative enrichment against other transcription factors + showing no such preference. In addition,a replicate showing a differing enrichment patterns across genomic features + compared to those within its sample group would highlight a potential outlier sample worthy of further investigation +

+

+Figure 2 shows the log2 enrichment of specified genomic features within samples with regions + of greater enrichment showing bright yellow and lower enrichment seen in black +

+
+
+
+
+ChIP signal Distribution and Structure +
+
+

+ In this section, metrics relating to genome wide depths of coverage and, + the relationship between Watson and Crick reads are presented. The metrics are the SSD metric and cross-coverage metrics, + Relative_CC and fragmentLength_CC. +

+
+
+

+Figure 2.  +Plot of the log2 base pairs of genome at differing read depths +

+
+
+ +
+
+

+SSD is the standard deviation of coverage normalised to + the total number of reads. Evaluation of the number of bases at differing read depths,(figure 3)alongside + the use of the SSD metric allow for an assessment of the distribution of ChIP-seq or input signal. +

+

+Successfull Histone + and transcription factor ChIP-seq samples will show a higher proportion of genomic positions at greater depths and + equivalence of sample and input SSD scores highlights either an unsuccessful ChIP or high levels of anomalous input signal + +

+
+
+

+Figure 3.  +Plot of CrossCoverage score after successive strand shifts +

+
+
+ +
+
+

+An important measure of ChIP successive is + the degree to which Watson and Crick reads cluster around the centres + of transcription factor bindind sites or epigentic marks. +

+

+ Transcription factor binding sites identified + by ChIP-seq will show two distinct peaks of Watson and Crick strands separated by the fragment length. + Here the method of cross-coverage (ChIPseq package) analysis is used to investigate this + spatial clustering of Watson and Crick reads. +

+

+ To investigate this spatial clustering, reads on the positive strand are shifted in 1bp steps + and the total proportion genome now covered by both strands combined is assessed. + Figure 4 shows the CCov_Score (described below) after successive shifts. The points of highest + outside of the read-length exclusion region, 2* the read length, (marked in grey) is considered the fragment length + + + +

+

+Following the methodology first presented for cross-correlation + by Encode to calculate + the Relative Strand Cross Correlation (NSC) and Normalised Strand Cross Correlation, the Relative + Cross Coverage score and Fragment Length Cross Coverage score are calculated. + +

+

+The calculation of cross-coverage (CCov),Relative CCov and Fragment Length CCov scores are explained below: +

+
    +
  • +

    +CCov_Score- 1-(Total covered genome size at strand shift)/(covered genome size with no shift) +

    +
  • +
  • +

    +Fragment Length CCov- (CCov of fragment length strand shift)/(Minimum CCov) +

    +
  • +
  • +

    +Relative CCov- (CCov of fragment length strand shift)/(CCov of read length strand shift) +

    +
  • +
+
+
+
+
+Peak Profile and ChIP Enrichment +
+
+

+Following the identification of genome wide enrichment (peak calling), + the percentage of ChIP signal within enriched regions, as well + the average profile across these regions can be used to further evaluate ChIP quality +

+
+
+

+Figure 4.  +Plot of the average signal profile across peaks +

+
+
+ +
+
+

+Figure5 represents the mean read depth across and around peaks. + By identying the average pattern of enrichment across peaks, differences in both mean + peak height and shape may be found. This not only assits in a better characterisation of + ChIP enrichment but can aid in the identification of outliers. + +

+
+
+

+Figure 5.  +Barplot of the percentage number of reads in peaks +

+
+
+ +
+
+

+Figure6 shows the total percentage of reads contained within enriched regions or peaks. + The higher efficiency ChIP-seq will show a higher percentage of reads in enriched regions/peaks and longer epigenetic + marks will often have a higher ranges of efficiencies than punctate marks or transcription factors. + +

+
+
+

+Figure 6.  +Density plot of the number of reads in peaks +

+
+
+ +
+
+

+Figure7 shows the distribution of reads in all peaks. Evaluation of the distibution can allow for greater characteriation of + the variability and range of signal in peaks within a sample and so better characterise the signal across peaks than the RIP score may allow. + +

+
+
+

+Figure 7.  +Plot of correlation between peaksets +

+
+
+ +
+
+
+
+

+Figure 8.  +PCA of peaksets +

+
+
+ +
+
+

+Figure8 and 9 shows the correlation between samples as a heatmap and by principal component analysis. + Replicate samples of high quality can be expected to cluster together in the heatmap and be spatially grouped within the PCA plot. + +

+
+
+
+
+
+
+Files and Versions +
+
+

+R Version Information +

+
    +
  • +

    +Version: 4.0.3 +

    +
  • +
  • +

    +Version_String :R version 4.0.3 (2020-10-10) +

    +
  • +
+

+ChIPQC Version Information +

+
    +
  • +

    +Version: ChIPQC:1.26.0 +

    +
  • +
  • +

    +Author: Tom Carroll, Wei Liu, Ines de Santiago, Rory Stark +

    +
  • +
  • +

    +Maintainer: Tom Carroll , Rory Stark +

    +
  • +
+
+
+ +
+
+
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