ATAqC

Sample Information

Sample ATAC4-trimmed-pair1.PE2SE
Genome hg19
Paired/Single-ended Paired-ended
Read length 76

Summary

Read count from sequencer 66,716,160
Read count successfully aligned 63,482,035
Read count after filtering for mapping quality 51,529,472
Read count after removing duplicate reads 44,238,724
Read count after removing mitochondrial reads (final read count) 36,710,784
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.

Alignment statistics

Bowtie alignment log

33358080 reads; of these:
  33358080 (100.00%) were paired; of these:
    2047012 (6.14%) aligned concordantly 0 times
    22069338 (66.16%) aligned concordantly exactly 1 time
    9241730 (27.70%) aligned concordantly >1 times
    ----
    2047012 pairs aligned concordantly 0 times; of these:
      109783 (5.36%) aligned discordantly 1 time
    ----
    1937229 pairs aligned 0 times concordantly or discordantly; of these:
      3874458 mates make up the pairs; of these:
        3234125 (83.47%) aligned 0 times
        377833 (9.75%) aligned exactly 1 time
        262500 (6.78%) aligned >1 times
95.15% overall alignment rate

  

Samtools flagstat

66716160 + 0 in total (QC-passed reads + QC-failed reads)
0 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
63482035 + 0 mapped (95.15%:-nan%)
66716160 + 0 paired in sequencing
33358080 + 0 read1
33358080 + 0 read2
62622136 + 0 properly paired (93.86%:-nan%)
62973108 + 0 with itself and mate mapped
508927 + 0 singletons (0.76%:-nan%)
96778 + 0 with mate mapped to a different chr
36470 + 0 with mate mapped to a different chr (mapQ>=5)

  

Filtering statistics

Mapping quality > q30 (out of total) 51,529,472 0.772
Duplicates (after filtering) 7,290,748.0 0.284
Mitochondrial reads (out of total) 9,304,541 0.147
Duplicates that are mitochondrial (out of all dups) 7,803,383 0.395
Final reads (after all filters) 36,710,784 0.550
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 0.788187 out of range [0.8, inf]
PBC1 0.778657 out of range [0.8, inf]
PBC2 4.278458 out of range [1.0, inf]
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

56,912,841

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 0.647351135753 - OK
NFR / mono-nuc reads 4.05039339087 - OK
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
Raw peaks 243565 - OK
Naive overlap peaks 0 out of range [10000, inf]
IDR peaks 59125 - OK

Raw peak file statistics

Min size 150.0
25 percentile 156.0
50 percentile (median) 208.0
75 percentile 314.0
Max size 2163.0
Mean 291.20975099

Naive overlap peak file statistics

Min size 0
25 percentile 0
50 percentile (median) 0
75 percentile 0
Max size 0
Mean 0
Metric failed.

IDR peak file statistics

Min size 150.0
25 percentile 628.0
50 percentile (median) 910.0
75 percentile 1230.0
Max size 2794.0
Mean 955.25146723
For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks 
for a specific cell type.

Sequence quality metrics

GC bias

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

Annotation-based quality metrics

Enrichment plots (TSS)

Open chromatin assays should show enrichment in open chromatin sites, such as
TSS's. An average TSS enrichment is above 6-7. A strong TSS enrichment is
above 10.
  

Annotated genomic region enrichments

Fraction of reads in universal DHS regions 7,885,350 0.225
Fraction of reads in blacklist regions 129,240 0.004
Fraction of reads in promoter regions 2,329,280 0.067
Fraction of reads in enhancer regions 10,127,389 0.289
Fraction of reads in called peak regions 6,313,436 0.180
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.