European Genome-Phenome Archive

File Quality

File InformationEGAF00001226672

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.

784 085 809650 782 499410 736 475211 536 03192 742 83535 748 24912 570 3394 240 0681 470 083601 513310 108194 915140 566110 14585 06468 99256 48846 31839 64733 13328 52424 12020 62617 78515 38214 34312 99911 2219 8568 6077 6806 9126 5505 2795 0094 8564 7324 1683 9243 8363 3263 3783 2963 2143 0252 7972 6842 7332 5182 4442 3122 1012 0282 0762 1762 1011 9631 8221 8081 8661 7361 6951 6861 7061 5231 3751 4321 3961 3041 3181 2281 1441 1701 2211 2251 1711 1581 1111 0301 0901 0639721 0149929601 024951886906910851860919889856861892878830909860884819787784787770628748777764663734724736707596573581641707575585606610638587610585577545553642522521546550539490494471508475470416409445431408456449390414424399391408399342367380415390420362358377381376389352358372352371351405373327356375300345337341387356324330350318321307337351381319325333327328293318331288288291310317285285282262319258296249229267288281250242220229227211258219213234239228263230244204235247225283273253245238230221254226226239230229230220235200213209197198206228202211207185212185180196189185181214190179177176178200175204194167162148175158164162174150159142185187151174183188181159188211145153145145173161154143174172172163152183164186174155185183198124163137136152145147148152155134157137143163181181158197146162145134174181185184211158160168163186189138158155138130127148123151133146138158131132146158169176146184160167131122141129124138142144124137123138116142145107116137123134117125134127143134145153163123134150163168150122127140129118140129139142128122135128126135116132123132162155122135107921109811612397115113122104991051051041161201071149711199101107841251341071371291581261151121231051271071139210497969210110576981001111271181229089919975102941011019310297948291851141271061139910893857685153837492968777638398818579801007883737264826756725661846669706867658580737665727465798482697160756481868890736971826678100697681716955745369395957646271666276516658695652553742495655636444535645444346404637474650593446486064596043455748484011654585333454541465054514648404753463737414029323241423228302837293536433554373940343137395238353542314135355031264647304638403739315034323933353740323938322831513351633856383830313536283626293939364526412832363441343536404036343328403230392336253533333336533534363833394826402634302628262626282434342926311928352136262428252823302926252932283620372628202130342851254222333123262123273029242529242227322927193526292618132433332321353929251727313726223022342322162018212421132821142717212421241617161517202328172319183226293521293232283123272742332422242325182021302620241323181920252722172028212113162519112810222121142013211916201222212422161723191421131418161616122023161222192022132027212126212623202721261723161414141313 414100200300400500600700800900>1000Coverage value101001k10k100k1M10M100M# 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.

001 770 286 10586 095485 4761 156 0002 457 5933 453 0064 761 9266 161 7309 410 8018 630 0625 581 1865 669 5916 995 79011 133 71611 100 71921 196 09224 304 88114 487 27014 952 61217 144 98618 480 84463 181 91723 798 94133 942 57540 818 20473 226 26858 139 940101 232 733107 939 661141 265 873119 596 999276 644 589114 799 258322 529 362282 834 865156 959 082546 957 378904 386 6121 093 141 99000510152025303540Phred quality score0G0.2G0.4G0.6G0.8G1G1.2G1.4G1.6G# 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).

79.2 %47 088 90479.2 %20.8 %

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.

77.4 %45 999 63277.4 %22.6 %

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%).

2.3 %1 089 2722.3 %97.7 %

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 %29 719 13350 %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.

77.1 %45 826 92877.1 %22.9 %

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.

0.9 %556 3500.9 %99.1 %

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.

13 460 4586 7534 54710 5864 2217 0856 0089 4536 93562 78553 96814 907100 74614 2219 736289 76915 7011 231 22819 1214 99931 6061 50118 41284 1201 06680 1571 1921 1981 10718 741 9391 3651 1241 2721 5581 4541 91446 419723 1973 8661 9405 8064 6182 8169 9102 3365 57428 2164 41417 2585 15258 8283 5329 6647 48010 86416 86835 71224 129 584051015202530354045505560Phred quality score2M4M6M8M10M12M14M16M18M20M22M24M# 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.

97.5%97.59%98.38%98.2%98.04%98.4%97.84%97.68%96.56%96.98%98.09%98.43%98.54%98.21%97.47%95.38%97.52%98.32%97.22%98.4%97.68%97.18%78.92%96.06%2.5%2.41%1.62%1.8%1.96%1.6%2.16%2.32%3.44%3.02%1.91%1.57%1.46%1.79%2.53%4.62%2.48%1.68%2.78%1.6%2.32%2.82%21.08%3.94%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped