Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.
Library complexity quality metrics
Library complexity (filtered non-mito BAM)
rep1
rep2
ctl1
Total Fragments
5848407
5605469
5822383
Distinct Fragments
5413830
5218556
5598875
Positions with Two Read
356247
322967
176596
NRF = Distinct/Total
0.925693
0.930976
0.961612
PBC1 = OneRead/Distinct
0.928474
0.933208
0.966256
PBC2 = OneRead/TwoRead
14.10987
15.078934
30.634578
Mitochondrial reads are filtered out by default.
The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1. See more details at
the ENCODE portal standard for ChIP-Seq pipeline
NRF (non redundant fraction)
PBC1 (PCR Bottleneck coefficient 1)
PBC2 (PCR Bottleneck coefficient 2)
PBC1 is the primary measure. Provisionally
0-0.5 is severe bottlenecking
0.5-0.8 is moderate bottlenecking
0.8-0.9 is mild bottlenecking
0.9-1.0 is no bottlenecking
Replication quality metrics
IDR (Irreproducible Discovery Rate) plots
Reproducibility QC and peak detection statistics
overlap
idr
Nt
50952
119
N1
12022
5
N2
12641
16
Np
45682
145
N optimal
50952
145
N conservative
50952
119
Optimal Set
rep1_vs_rep2
pooled-pr1_vs_pooled-pr2
Conservative Set
rep1_vs_rep2
rep1_vs_rep2
Rescue Ratio
1.115362724924478
1.218487394957983
Self Consistency Ratio
1.0514889369489269
3.2
Reproducibility Test
pass
borderline
Reproducibility QC
N1: Replicate 1 self-consistent peaks (comparing two pseudoreplicates generated by subsampling Rep1 reads)
N2: Replicate 2 self-consistent peaks (comparing two pseudoreplicates generated by subsampling Rep2 reads)
Ni: Replicate i self-consistent peaks (comparing two pseudoreplicates generated by subsampling RepX reads)
Nt: True Replicate consistent peaks (comparing true replicates Rep1 vs Rep2)
Np: Pooled-pseudoreplicate consistent peaks (comparing two pseudoreplicates generated by subsampling pooled reads from Rep1 and Rep2)
Self-consistency Ratio: max(N1,N2) / min (N1,N2)
Rescue Ratio: max(Np,Nt) / min (Np,Nt)
Reproducibility Test: If Self-consistency Ratio >2 AND Rescue Ratio > 2, then 'Fail' else 'Pass'
Number of raw peaks
rep1
rep2
Number of peaks
97586
86929
Top 300000 raw peaks from spp with FDR 0.01
Peak calling statistics
Peak region size
rep1
rep2
idr_opt
overlap_opt
Min size
390.0
404.0
410.0
410.0
25 percentile
390.0
404.0
410.0
410.0
50 percentile (median)
390.0
404.0
410.0
410.0
75 percentile
390.0
404.0
410.0
410.0
Max size
390.0
404.0
410.0
410.0
Mean
390.0
404.0
410.0
410.0
Enrichment / Signal-to-noise ratio
Strand cross-correlation measures (trimmed/filtered SE BAM)
rep1
rep2
Number of Subsampled Reads
5848407
5605469
Estimated Fragment Length
120
120
Cross-correlation at Estimated Fragment Length
0.678645999369163
0.670740405789749
Phantom Peak
35
30
Cross-correlation at Phantom Peak
0.6749437
0.6680087
Argmin of Cross-correlation
1500
1500
Minimum of Cross-correlation
0.6687553
0.6619522
NSC (Normalized Strand Cross-correlation coeff.)
1.01479
1.013276
RSC (Relative Strand Cross-correlation coeff.)
1.59826
1.451025
Performed on subsampled (15000000) reads mapped from FASTQs that are trimmed to 50.
Such FASTQ trimming and subsampling reads are for cross-corrleation analysis only.
Untrimmed FASTQs are used for all the other analyses.
NOTE1: For SE datasets, reads from replicates are randomly subsampled to 15000000.
NOTE2: For PE datasets, the first end (R1) of each read-pair is selected and trimmed to 50 the reads are then randomly subsampled to 15000000.
Normalized strand cross-correlation coefficient (NSC) = col9 in outFile
Relative strand cross-correlation coefficient (RSC) = col10 in outFile
Estimated fragment length = col3 in outFile, take the top value
Jensen-Shannon distance (filtered/deduped BAM)
rep1
rep2
AUC
0.3705675131833317
0.37137017215650164
Synthetic AUC
0.4951994198138206
0.4951107691966223
X-intercept
0.036349162646491975
0.036353152894326266
Synthetic X-intercept
0.0
0.0
Elbow Point
0.5129762859571207
0.5144287361688035
Synthetic Elbow Point
0.5077715077628184
0.4955956051932492
JS Distance
0.003633158461006217
0.005533412654900454
Synthetic JS Distance
0.18025005801144617
0.17847779303000483
% Genome Enriched
43.44701549413234
42.269293845840764
Diff. Enrichment
4.106327607553434
4.215678215030266
CHANCE Divergence
0.03541796027198635
0.03619589833056551
Peak enrichment
Fraction of reads in peaks (FRiP)
FRiP for spp raw peaks
rep1
rep2
rep1-pr1
rep2-pr1
rep1-pr2
rep2-pr2
pooled
pooled-pr1
pooled-pr2
Fraction of Reads in Peaks
0.4321469156284523
0.4036032966534031
0.22376395458028028
0.2352518789863718
0.23279031018159213
0.24747373196319974
0.483697794151591
0.4006659934692862
0.40505489924416976
FRiP for overlap peaks
rep1_vs_rep2
rep1-pr1_vs_rep1-pr2
rep2-pr1_vs_rep2-pr2
pooled-pr1_vs_pooled-pr2
Fraction of Reads in Peaks
0.2445239579852132
0.06928012908966151
0.07499405752317566
0.2190041316057304
FRiP for IDR peaks
rep1_vs_rep2
rep1-pr1_vs_rep1-pr2
rep2-pr1_vs_rep2-pr2
pooled-pr1_vs_pooled-pr2
Fraction of Reads in Peaks
0.0016785613925448689
0.00024441554615288274
0.0006314477781241308
0.0029202061579774786
For spp raw peaks:
repX: Peak from true replicate X
repX-prY: Peak from Yth pseudoreplicates from replicate X
pooled: Peak from pooled true replicates (pool of rep1, rep2, ...)
pooled-pr1: Peak from 1st pooled pseudo replicate (pool of rep1-pr1, rep2-pr1, ...)
pooled-pr2: Peak from 2nd pooled pseudo replicate (pool of rep1-pr2, rep2-pr2, ...)
For overlap/IDR peaks:
repX_vs_repY: Comparing two peaks from true replicates X and Y
repX-pr1_vs_repX-pr2: Comparing two peaks from both pseudoreplicates from replicate X
pooled-pr1_vs_pooled-pr2: Comparing two peaks from 1st and 2nd pooled pseudo replicates