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
Flagstat (filtered/deduped BAM)
Filtered and duplicates removed
rep1 (PE)
Total
158522472
Total(QC-failed)
0
Dupes
0
Dupes(QC-failed)
0
Mapped
158522472
Mapped(QC-failed)
0
% Mapped
100.0000
Paired
158522472
Paired(QC-failed)
0
Read1
79261236
Read1(QC-failed)
0
Read2
79261236
Read2(QC-failed)
0
Properly Paired
158522472
Properly Paired(QC-failed)
0
% Properly Paired
100.0000
With itself
158522472
With itself(QC-failed)
0
Singletons
0
Singletons(QC-failed)
0
% Singleton
0.0000
Diff. Chroms
0
Diff. Chroms (QC-failed)
0
Peak calling
IDR (Irreproducible Discovery Rate) plots
Reproducibility QC and peak detection statistics
The number of peaks is capped at 300K for peak-caller MACS2
overlap
IDR
Nt
0
0
N1
213158
135186
Np
0
0
N optimal
213158
135186
N conservative
213158
135186
Optimal Set
rep1-pr
rep1-pr
Conservative Set
rep1-pr
rep1-pr
Rescue Ratio
0.0000
0.0000
Self Consistency Ratio
1.0000
1.0000
Reproducibility
pass
pass
Overlapping peaks
N1: Replicate 1 self-consistent overlapping peaks (comparing two pseudoreplicates generated by subsampling Rep1 reads)
N2: Replicate 2 self-consistent overlapping peaks (comparing two pseudoreplicates generated by subsampling Rep2 reads)
Nt: True Replicate consisten overlapping peaks (comparing true replicates Rep1 vs Rep2 )
Np: Pooled-pseudoreplicate consistent overlapping 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'
IDR (Irreproducible Discovery Rate) peaks
N1: Replicate 1 self-consistent IDR 0.05 peaks (comparing two pseudoreplicates generated by subsampling Rep1 reads)
N2: Replicate 2 self-consistent IDR 0.05 peaks (comparing two pseudoreplicates generated by subsampling Rep2 reads)
Nt: True Replicate consistent IDR 0.05 peaks (comparing true replicates Rep1 vs Rep2 )
Np: Pooled-pseudoreplicate consistent IDR 0.05 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'
Enrichment
Strand cross-correlation measures
Performed on subsampled reads (25M)
rep1
Reads
25000000
Est. Fragment Len.
0
Corr. Est. Fragment Len.
0.3619
Phantom Peak
150
Corr. Phantom Peak
0.2854
Argmin. Corr.
1500
Min. Corr.
0.2271
NSC
1.5933
RSC
2.3134
NOTE1: For SE datasets, reads from replicates are randomly subsampled.
NOTE2: For PE datasets, the first end of each read-pair is selected and the reads are then randomly subsampled.
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
Fraction of reads in overlapping peaks
rep1-pr
Fraction of Reads in Peak
0.2501
ppr: Overlapping peaks comparing pooled pseudo replicates
rep1-pr: Overlapping peaks comparing pseudoreplicates from replicate 1
rep2-pr: Overlapping peaks comparing pseudoreplicates from replicate 2
repi-repj: Overlapping peaks comparing true replicates (rep i vs. rep j)
Fraction of reads in IDR peaks
rep1-pr
Fraction of Reads in Peak
0.2151
ppr: IDR peaks comparing pooled pseudo replicates
rep1-pr: IDR peaks comparing pseudoreplicates from replicate 1
rep2-pr: IDR peaks comparing pseudoreplicates from replicate 2
repi-repj: IDR peaks comparing true replicates (rep i vs. rep j)
ATAQC
Summary table
rep1
Genome
male.hg19.fa.gz
Paired/single-ended
Paired-ended
Read length
N/A
Read count from sequencer
275072572
Read count successfully aligned
273905197
Read count after filtering for mapping quality
226836091
Read count after removing duplicate reads
193623143
Read count after removing mitochondrial reads (final read count)
158522472
Mapping quality > q30 (out of total)
226836091, 0.824640891495
Duplicates (after filtering)
33212948, 0.295294
Mitochondrial reads (out of total)
31660220, 0.115588241285
Duplicates that are mitochondrial (out of all dups)
14732128, 0.221782902258
Final reads (after all filters)
158522472, 0.576293269981
NRF = Distinct/Total
0.759084, out of range [0.8, inf]
PBC1 = OnePair/Distinct
0.762263, out of range [0.8, inf]
PBC2 = OnePair/TwoPair
4.250521, OK
Picard est library size
185978300
Fraction of reads in nfr
0.223780123322, out of range [0.4, inf]
Nfr / mono-nuc reads
0.528581053485, out of range [2.5, inf]
Presence of nfr peak
OK
Presence of mono-nuc peak
OK
Presence of di-nuc peak
OK
Naive overlap peaks
213158, OK
Idr peaks
135186, OK
Naive peak stats: min size
150.0000
Naive peak stats: 25 percentile
511.0000
Naive peak stats: 50 percentile (median)
791.0000
Naive peak stats: 75 percentile
1183.0000
Naive peak stats: max size
3671.0000
Naive peak stats: mean
894.0926
Idr peak stats: min size
150.0000
Idr peak stats: 25 percentile
656.0000
Idr peak stats: 50 percentile (median)
977.0000
Idr peak stats: 75 percentile
1373.0000
Idr peak stats: max size
3671.0000
Idr peak stats: mean
1052.3530
Fraction of reads in universal dhs regions
51731104, 0.330361522487
Fraction of reads in blacklist regions
252868, 0.001614847761
Fraction of reads in promoter regions
25173240, 0.160759567249
Fraction of reads in enhancer regions
43556488, 0.278157367179
Fraction of reads in called peak regions
33684563, 0.215113977019
Replicate 1
Sample Information
Sample
Genome
male.hg19.fa.gz
Paired/Single-ended
Paired-ended
Read length
N/A
Summary
Read count from sequencer
275,072,572
Read count successfully aligned
273,905,197
Read count after filtering for mapping quality
226,836,091
Read count after removing duplicate reads
193,623,143
Read count after removing mitochondrial reads (final read count)
158,522,472
Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.
This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.
Filtering statistics
Mapping quality > q30 (out of total)
226,836,091
0.825
Duplicates (after filtering)
33,212,948
0.295
Mitochondrial reads (out of total)
31,660,220
0.116
Duplicates that are mitochondrial (out of all dups)
14,732,128
0.222
Final reads (after all filters)
158,522,472
0.576
Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
Library complexity statistics
ENCODE library complexity metrics
Metric
Result
NRF
0.759084 out of range [0.8, inf]
PBC1
0.762263 out of range [0.8, inf]
PBC2
4.250521 - OK
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.
Picard EstimateLibraryComplexity
185,978,300
Yield prediction
Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.
Fragment length statistics
Metric
Result
Fraction of reads in NFR
0.223780123322 out of range [0.4, inf]
NFR / mono-nuc reads
0.528581053485 out of range [2.5, inf]
Presence of NFR peak
OK
Presence of Mono-Nuc peak
OK
Presence of Di-Nuc peak
OK
Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.
Peak statistics
Metric
Result
Naive overlap peaks
213158 - OK
IDR peaks
135186 - OK
Naive overlap peak file statistics
Min size
150.0
25 percentile
511.0
50 percentile (median)
791.0
75 percentile
1183.0
Max size
3671.0
Mean
894.092560448
IDR peak file statistics
Min size
150.0
25 percentile
656.0
50 percentile (median)
977.0
75 percentile
1373.0
Max size
3671.0
Mean
1052.35303952
For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.
Annotation-based quality metrics
Annotated genomic region enrichments
Fraction of reads in universal DHS regions
51,731,104
0.330
Fraction of reads in blacklist regions
252,868
0.002
Fraction of reads in promoter regions
25,173,240
0.161
Fraction of reads in enhancer regions
43,556,488
0.278
Fraction of reads in called peak regions
33,684,563
0.215
Signal to noise can be assessed by considering whether reads are falling into
known open regions (such as DHS regions) or not. A high fraction of reads
should fall into the universal (across cell type) DHS set. A small fraction
should fall into the blacklist regions. A high set (though not all) should
fall into the promoter regions. A high set (though not all) should fall into
the enhancer regions. The promoter regions should not take up all reads, as
it is known that there is a bias for promoters in open chromatin assays.
Comparison to Roadmap DNase
This bar chart shows the correlation between the Roadmap DNase samples to
your sample, when the signal in the universal DNase peak region sets are
compared. The closer the sample is in signal distribution in the regions
to your sample, the higher the correlation.