QC Report

	general
Report generated at	2019-07-15 19:03:08
Title	ENCSR356KRQ
Description	ATAC-seq on primary keratinocytes in day 0.0 of differentiation
Pipeline version	v1.4.2
Genome	hg38_google.tsv
Paired-end per replicate	[True, True]
Aligner	bowtie2
Peak caller	macs2
Control paired-end per replicate	[True, True]

Alignment quality metrics

SAMstat (raw BAM)

	rep1	rep2
Total	276305638	338971378
Total(QC-failed)	0	0
Dupes	0	0
Dupes(QC-failed)	0	0
Mapped	272041416	334808681
Mapped(QC-failed)	0	0
% Mapped	0.0	0.0
Paired	276305638	338971378
Paired(QC-failed)	0	0
Read1	138152819	169485689
Read1(QC-failed)	0	0
Read2	138152819	169485689
Read2(QC-failed)	0	0
Properly Paired	222420584	272644706
Properly Paired(QC-failed)	0	0
% Properly Paired	0.0	0.0
With itself	270395242	332530340
With itself(QC-failed)	0	0
Singletons	1646174	2278341
Singletons(QC-failed)	0	0
% Singleton	0.0	0.0
Diff. Chroms	6029032	8172582
Diff. Chroms (QC-failed)	0	0

Marking duplicates (filtered BAMs)

	rep1	rep2
Unpaired Reads	0	0
Paired Reads	98099280	118329560
Unmapped Reads	0	0
Unpaired Dupes	0	0
Paired Dupes	25925767	23745187
Paired Opt. Dupes	720889	1031664
% Dupes/100	0.264281	0.20067

Filtered out (samtools view -F 1804):

read unmapped (0x4)
mate unmapped (0x8, for paired-end)
not primary alignment (0x100)
read fails platform/vendor quality checks (0x200)
read is PCR or optical duplicate (0x400)

Fraction of mitochondrial reads

	rep1	rep2
Total reads	424777493	543920290
Mito. reads	21564100	30950790
Frac. of mito. reads	0.0507656369637	0.056903172338
Total deduped reads	144347026	189168746
Mito. deduped reads	2743046	3308438
Frac. of deduped mito. reads	0.0190031348481	0.017489347844
Total dup reads	51851534	47490374
Mito. dup reads	10459536	15613116
Frac. of mito. dup reads	0.201720859406	0.328763803797

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.

SAMstat (filtered/deduped BAM)

	rep1	rep2
Total	144347026	189168746
Total(QC-failed)	0	0
Dupes	0	0
Dupes(QC-failed)	0	0
Mapped	144347026	189168746
Mapped(QC-failed)	0	0
% Mapped	100.0	100.0
Paired	144347026	189168746
Paired(QC-failed)	0	0
Read1	72173513	94584373
Read1(QC-failed)	0	0
Read2	72173513	94584373
Read2(QC-failed)	0	0
Properly Paired	144347026	189168746
Properly Paired(QC-failed)	0	0
% Properly Paired	100.0	100.0
With itself	144347026	189168746
With itself(QC-failed)	0	0
Singletons	0	0
Singletons(QC-failed)	0	0
% Singleton	0.0	0.0
Diff. Chroms	0	0
Diff. Chroms (QC-failed)	0	0

Filtered and duplicates removed

Fragment length statistics

	rep1	rep2
Fraction of reads in NFR	0.501361391702	0.559164537468
Fraction of reads in NFR (QC pass)	True	True
Fraction of reads in NFR (QC reason)	OK	OK
NFR / mono-nuc reads	1.59708295351	1.96472615597
NFR / mono-nuc reads (QC pass)	False	False
NFR / mono-nuc reads (QC reason)	out of range [2.5, inf]	out of range [2.5, inf]
Presence of NFR peak	True	True
Presence of Mono-Nuc peak	True	True
Presence of Di-Nuc peak	True	True

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.

Library complexity quality metrics

Library complexity (filtered non-mito BAM)

	rep1	rep2
Total Reads (Pairs)	91497989	108868783
Distinct Reads (Pairs)	71030625	93255779
One Read (Pair)	55129598	80368374
Two Reads (Pairs)	12476229	10988872
NRF = Distinct/Total	0.776308	0.856589
PBC1 = OnePair/Distinct	0.776138	0.861806
PBC2 = OnePair/TwoPair	4.418771	7.313615

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.

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

	rep1	rep2
Estimated library size by Picard tools	218636838.0	367922688.0

Replication quality metrics

IDR (Irreproducible Discovery Rate) plots

Reproducibility QC and peak detection statistics

	overlap	idr
Nt	273569	198938
N1	265938	181312
N2	267029	181177
Np	278971	204660
N optimal	278971	204660
N conservative	273569	198938
Optimal Set	pooled-pr1_vs_pooled-pr2	pooled-pr1_vs_pooled-pr2
Conservative Set	rep1_vs_rep2	rep1_vs_rep2
Rescue Ratio	1.01974638939	1.0287627301
Self Consistency Ratio	1.00410245997	1.00074512769
Reproducibility Test	pass	pass

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 peaks called

	rep1	rep2	idr_opt	overlap_opt
Number of peaks	299541	299460	204660	278971

Peak calling statistics

Peak region size

	rep1	rep2	idr_opt	overlap_opt
Min size	73.0	73.0	74.0	73.0
25 percentile	231.0	228.0	426.0	307.0
50 percentile (median)	413.0	409.0	638.0	531.0
75 percentile	670.0	669.0	900.0	807.0
Max size	2249.0	3228.0	2430.0	2581.0
Mean	491.037056697	489.644864089	692.616666667	597.587111205

Alignment enrichment

Strand cross-correlation measures

	rep1	rep2
Reads	25000000	25000000
Est. Fragment Len.	0	0
Corr. Est. Fragment Len.	0.38420349321	0.367035620183
Phantom Peak	75	75
Corr. Phantom Peak	0.3296718	0.3220599
Argmin. Corr.	1500	1500
Min. Corr.	0.1972714	0.2069599
NSC	1.947589	1.773462
RSC	1.411869	1.390754

Performed on subsampled reads

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

TSS enrichment

	rep1	rep2
TSS enrichment	17.459884614	16.6453688953

Open chromatin assays should show enrichment in open chromatin sites, such as TSS's. An average TSS enrichment in human (hg19) is above 6. A strong TSS enrichment is above 10. For other references please see https://www.encodeproject.org/atac-seq/

Peak enrichment

Fraction of reads in peaks (FRiP)

FRiP for macs2 raw peaks

	rep1	rep2	rep1-pr1	rep2-pr1	rep1-pr2	rep2-pr2	pooled	pooled-pr1	pooled-pr2
Fraction of Reads in Peaks	0.36138889599	0.323622238913	0.357758291822	0.319941350791	0.357206697156	0.320312866371	0.345327149078	0.342095593642	0.341496432124

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	0.334878855553	0.348362538963	0.311893629273	0.337325809402

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	0.29616248719	0.301782421652	0.269407328218	0.300262821331

For raw peaks (e.g. spp and macs2):

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

Annotated genomic region enrichment

	rep1	rep2
Fraction of Reads in universal DHS regions	0.454773714694	0.420893093538
Fraction of Reads in blacklist regions	0.000318733979087	0.000309834846502
Fraction of Reads in promoter regions	0.147301827251	0.133853345385
Fraction of Reads in enhancer regions	0.390787737746	0.374695715021

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.

Other quality metrics

Sequence quality metrics (GC bias)

Open chromatin assays are known to have significant GC bias. Please take this into consideration as necessary.

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.