European Genome-Phenome Archive

File Quality

File InformationEGAF00000827159

File Data

Base Coverage Distribution

This chart represents the base coverage distribution along the reference file. Y-axis represents the number of times a position in the reference file is covered. The x-axis represents the range of the values for the coverage.

Data is represented in a log scale to minimise the variability. A high peak in the beginning (low coverage) and a curve descending is expected.

56 064 28048 454 87031 112 86621 386 7939 981 4187 443 4853 163 3143 057 8701 386 0911 497 441773 127802 834499 530482 504345 554320 410251 435228 283192 785173 514151 245134 753120 417112 14499 57391 38184 38177 20872 21565 27561 86558 08954 13349 71047 36043 55440 63338 11635 83835 31732 59731 74129 31128 78626 52525 23623 97523 59522 24721 32920 57619 77619 42018 22917 74617 04016 61016 15915 34015 02014 75114 23713 49512 83112 80812 29412 37211 90011 33010 98810 72010 61010 2849 9899 5549 3779 2468 9138 7958 5028 5108 1848 0187 9057 7047 5937 3617 0507 1266 8956 7826 6546 6776 2456 2526 1556 0995 9265 6585 5115 4135 2735 2175 4085 1845 1065 1804 8924 8474 9224 9144 9484 7704 4974 5294 5734 6054 4174 3714 2734 1294 1844 1224 0403 8873 9963 9093 8443 8733 8593 6483 7223 7753 7173 7133 5603 6113 5663 5993 5453 5213 5063 4523 3613 3643 2843 2923 3073 1983 2283 2233 1623 0513 0233 1073 0893 0773 0643 0522 9562 8262 9232 9243 0242 9982 8842 7582 9652 7932 7952 6422 8292 6602 7752 6452 7822 6792 7032 6772 5612 6132 5382 5632 4512 4872 5472 5652 4322 5742 4842 5312 3922 4902 4742 3962 5382 4562 2742 3432 4182 3512 3572 3342 2552 1882 2672 1952 2512 2112 2742 1832 2232 2452 2522 1472 1922 2162 0882 1332 1472 1302 1522 0212 1402 0852 1072 0962 0842 1772 1342 0652 0282 0792 1552 0452 0702 0701 9301 9452 0941 8922 0852 0161 9881 9711 9841 9681 9511 9221 9521 9311 8571 8881 8491 8871 8351 9181 7891 8311 8371 7951 7941 8341 7531 7691 8221 7641 8621 8871 8421 8381 7671 7691 7611 8331 7401 7481 7191 7741 7491 7781 7061 7161 6911 8061 7021 7221 6761 6971 7351 7161 6931 7441 6391 6091 6801 6591 7161 7171 6971 5351 6361 5771 6131 6241 5851 6901 6261 6141 5951 6321 5801 5931 5301 6441 5911 6231 6301 5731 5381 6031 5091 5541 5491 6091 4941 5411 5601 5061 5361 5891 5701 5671 5031 4811 5061 4821 4621 4271 4491 4611 5021 4421 4171 5111 3891 5221 4481 4811 4381 4921 4301 4881 4041 3961 4391 4241 4391 3901 4261 3911 4291 3891 3921 4531 4241 3761 4081 3851 4161 4031 4511 3301 3661 4141 3961 4411 3391 3351 3621 3351 3401 3601 3571 4261 3161 2541 2821 3511 3001 3081 3221 3191 3311 3441 4171 3911 3181 3911 3971 3411 2971 2751 2991 2761 3411 2061 2321 2771 2811 2641 3391 3071 3231 2721 2431 3051 1711 2311 3331 2921 2391 3621 2561 2841 2841 2881 3231 3291 3181 3181 2991 3101 2861 2671 2401 2581 3121 2431 2851 2721 2821 2511 2841 2031 2011 2161 2851 2011 3021 2421 1611 1581 1701 2951 2091 1661 1641 1841 2461 1901 2141 0791 1841 1991 2091 1991 1691 1051 2371 1411 1991 1901 1561 1201 1771 1311 0861 1821 1671 2061 1621 1701 1341 1141 1571 1261 1721 0781 1291 1461 1651 0731 1001 0751 1521 0981 0501 1031 1001 1261 0641 0751 0711 0489911 0071 0521 0791 0841 1051 1051 0139601 0511 0679979961 0381 0381 0071 0201 0381 0269681 0131 0291 0091 0599841 0311 0751 0209451 0551 0521 0499909489979381 0309811 0111 0241 0081 0119429819949789739619719799779961 0039939691 0379829881 0059489859639849851 0289659569129549911 0481 006931957924946981915969976921967949917938914898993967953912949963942951879925962961964912871910961915896887877907927936901925849913897902875872891894963865912900939853881889922851941924842896877942859882906873885876949890914937877935846889858867878955886892838856899888864888968851860879848913838856877891826861840866834827840840870876853898866836908806878854802786880811866894819892872871843867886858867843841878839840858855837829796891849815783789850777860814827787813819812784792807796771761842857776764791857775773762753807834817818771814789801760776819765782806796767778795797795709772754739735725741742787772776781757834740761789751761764784766710718747777757738701748711669728713732798745694737718731756755677705766716750772706715696722718736738704695677721723685713739667744717722681664729655722719707689715687675694680701682724695663677687692677663683650667672682688646658701688661615692658671651675677645677650679630635699650660696599690604667727680651629660587650639657661647672656654650672632611630632667636608676647628635637635625647691623620639615634653615630649652620628595622660619647650630640636616671623649632606595638634662599633613611623625581618568591660656652634613644622604590578626639627591590622572600628614604641623581582580587625596624594590590623 715100200300400500600700800900>1000Coverage value1k2k10k20k100k200k1M2M10M20M# Bases

Base Quality

The base quality distribution shows the Phred quality scores describing the probability that a nucleotide has been incorrectly assigned; e.g. an error in the sequencing. Specifically, Q=-log10(P), where Q is the Phred score and P is the probability the nucleotide is wrong. The larger the score, the more confident we are in the base call. Depending on the sequencing technology, we can expect to see different distributions, but we expect to see a distribution skewed towards larger (more confident) scores; typically around 40.

801 413000000000000078 925 14300000004 080 373000069 999 97000000255 434 8150002 059 573 18600000510152025303540Phred quality score0G0.2G0.4G0.6G0.8G1G1.2G1.4G1.6G1.8G2G# Bases

Mapped Reads

Number of reads successfully mapped (singletons & both mates) to the reference genome in the sample. Genetic variation, in particular structural variants, ensure that every sequenced sample is genetically different from the reference genome it was aligned to. Small differences against the reference are accepted, but, for more significant variation, the read can fail to be placed. Therefore, it is not expected that the mapped reads rate will hit 100%, but it is supposed to be high (usually >90%). Calculations are made taking into account the proportion of mapped reads against the total number of reads (mapped/mapped+unmapped).

100 %32 907 479100 %0 %

Both Mates Mapped

When working with paired-end sequencing, each DNA fragment is sequenced from both ends, creating two mates for each pair. This chart shows the fraction of reads in pairs where both of the mates successfully map to the reference genome. .

Notice that reads not mapped to the expected distance are also included as occurs with the proper pairs chart.

99.9 %32 898 07699.9 %0.1 %

Singletons

When working with paired-end sequencing, each DNA fragment is sequenced from both ends, creating two mates for each pair. If one mate in the pair successfully maps to the reference genome, but the other is unmapped, the mapped mate is a singleton. One way in which a singleton could occur would be if the sample has a large insertion compared with the reference genome; one mate can fall in sequence flanking the insertion and will be mapped, but the other falls in the inserted sequence and so cannot map to the reference genome. There are unlikely to many such structural variants in the sample, or sequencing errors that would cause a read not to be able to map. Consequently, the singleton rate is expected to be very low (<1%).

0 %9 4030 %100 %

Forward Strand

Fraction of reads mapped to the forward DNA strand. The general expectation is that the DNA library preparation step will generate DNA from the forward and reverse strands in equal amounts so after mapping the reads to the reference genome, approximately 50% of them will consequently map to the forward strand. Deviations from the 50%, may be due to problems with the library preparation step.

50 %16 458 76650 %50 %

Proper Pairs

A fragment consisting of two mates is called a proper pair if both mates map to the reference genome at the expected distance according to the reference genome. In particular, if the DNA library consists of fragments ~500 base pairs in length, and 100 base pair reads are sequenced from either end, the expectation would be that the two reads map to the reference genome separated by ~300 base pairs. If the sequenced sample contains large structural variants, e.g. a large insertion, where we expect the reads mapping with a large separation would be a signal for this variant, and the reads would not be considered as proper pairs. Based on the sequencing technology, there is also an expectation of the orientation of each read in the fragment.

The rate of proper pairs is expected to be well over 90%; even if the mapping rate itself is low as a result of bacterial contamination, for example.

98.6 %32 448 22498.6 %1.4 %

Duplicates

PCR duplicates are two (or more) reads that originate from the same DNA fragment. When sequencing data is analyzed, it is assumed that each observation (i.e. each read) is independent; an assumption that fails in the presence of duplicate reads. Typically, algorithms look for reads that map to the same genomic coordinate, and whose mates also map to identical genomic coordinates. It is important to note that as the sequencing depth increases, more reads are sampled from the DNA library, and consequently it is increasingly likely that duplicate reads will be sampled. As a result, the true duplicate rate is not independent of the depth, and they should both be considered when looking at the duplicate rate. Additionally, as the sequencing depth in increases, it is also increasingly likely that reads will map to the same location and be marked as duplicates, even when they are not. As such, as the sequencing depth approaches and surpasses the read length, the duplicate rate starts to become less indicative of problems.

58.6 %19 304 04058.6 %41.4 %

Mapping Quality Distribution

The mapping quality distribution shows the Phred quality scores describing the probability that a read does not map to the location that it has been assigned to (specifically, Q=-log10(P), where Q is the Phred score and P is the probability the read is in the wrong location). So the larger the score, the higher the quality of the mapping. Some scores have a specific meaning, e.g. a score of 0 means that the read could map equally to multiple places in the reference genome. The majority of reads should be well mapped, and so we expect to see this distribution heavily skewed to a significant value (typically around 60). It is not unusual to see some scores around zero. Reads originating from repetitive elements in the genome will plausibly map to multiple locations.

1 572 25419 7498 25227 4489 1149 68521 92917 1167 17627 05211 77713 33227 62114 5306 91120 9026 9748 99912 69114 00215 50425 06215 83337 55155 932106 4314 776252 1295 36712 8159 2099 9354 21619 0353 4046 0728 84212 2013 97525 357371 72713 84012 08422 84917 71628 48721 32026 19129 71761 23774 05046 267223 1227 17642 91023 5668 04062 4456 7853 83229 613 417051015202530354045505560Phred quality score2M4M6M8M10M12M14M16M18M20M22M24M26M28M# Reads

Mapped vs Unmapped

Stacked column chart for both mapped and unmapped reads along all chromosomes in the reference file. It is a similar representation as shown in the Mapped reads chart but for each chromosome. Although sequenced sample may be a female, it is possible to get reads in the Y chromosome as there are common regions in both chromosomes called pseudoautosomal regions (PAR1, PAR2).

Unmapped reads belonging to each chromosome are determined when the one mate/pair is aligned and the other is not. The unmapped read should have chromosome and POS identical to its mate. It could also be due when aligning is performed with bwa as it concatenates all the reference sequences together, so if a read hangs off of one reference onto another, it will be given the right chromosome and position, but it also be classified as unmapped.

99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.98%99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.97%99.98%99.98%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.02%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.03%0.02%0.02%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped