ATAqC
Sample Information
Sample |
RTB31_S31_R1.trim.PE2SE |
Genome |
hg19 |
Paired/Single-ended |
Paired-ended |
Read length |
75 |
Summary
Read count from sequencer |
1,804,440 |
Read count successfully aligned |
1,782,169 |
Read count after filtering for mapping quality |
1,586,310 |
Read count after removing duplicate reads |
1,582,685 |
Read count after removing mitochondrial reads (final read count) |
1,570,760 |
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
902220 reads; of these:
902220 (100.00%) were paired; of these:
18081 (2.00%) aligned concordantly 0 times
662307 (73.41%) aligned concordantly exactly 1 time
221832 (24.59%) aligned concordantly >1 times
----
18081 pairs aligned concordantly 0 times; of these:
2866 (15.85%) aligned discordantly 1 time
----
15215 pairs aligned 0 times concordantly or discordantly; of these:
30430 mates make up the pairs; of these:
22271 (73.19%) aligned 0 times
3171 (10.42%) aligned exactly 1 time
4988 (16.39%) aligned >1 times
98.77% overall alignment rate
Samtools flagstat
1804440 + 0 in total (QC-passed reads + QC-failed reads)
0 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
1782169 + 0 mapped (98.77%:-nan%)
1804440 + 0 paired in sequencing
902220 + 0 read1
902220 + 0 read2
1768278 + 0 properly paired (98.00%:-nan%)
1778440 + 0 with itself and mate mapped
3729 + 0 singletons (0.21%:-nan%)
4078 + 0 with mate mapped to a different chr
2889 + 0 with mate mapped to a different chr (mapQ>=5)
Filtering statistics
Mapping quality > q30 (out of total) |
1,586,310 |
0.879 |
Duplicates (after filtering) |
3,625.0 |
0.005 |
Mitochondrial reads (out of total) |
65,148 |
0.037 |
Duplicates that are mitochondrial (out of all dups) |
6,276 |
0.549 |
Final reads (after all filters) |
1,570,760 |
0.870 |
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 |
0.997668 - OK
|
PBC1 |
0.997696 - OK
|
PBC2 |
438.294118 - 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
214,933,096
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 |
0.245776040491 out of range [0.4, inf]
|
NFR / mono-nuc reads |
1.15497927368 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 |
Raw peaks |
58116 - OK
|
Naive overlap peaks |
58116 - OK
|
IDR peaks |
0 out of range [10000, inf]
|
Raw peak file statistics
Min size |
150.0 |
25 percentile |
247.0 |
50 percentile (median) |
352.0 |
75 percentile |
486.0 |
Max size |
1361.0 |
Mean |
387.980229197 |
Naive overlap peak file statistics
Min size |
150.0 |
25 percentile |
247.0 |
50 percentile (median) |
352.0 |
75 percentile |
486.0 |
Max size |
1361.0 |
Mean |
387.980229197 |
IDR peak file statistics
Min size |
0 |
25 percentile |
0 |
50 percentile (median) |
0 |
75 percentile |
0 |
Max size |
0 |
Mean |
0 |
Metric failed.
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 |
868,176 |
0.564 |
Fraction of reads in blacklist regions |
6,547 |
0.004 |
Fraction of reads in promoter regions |
342,006 |
0.222 |
Fraction of reads in enhancer regions |
639,047 |
0.415 |
Fraction of reads in called peak regions |
538,556 |
0.350 |
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.