European Genome-Phenome Archive

File Quality

File InformationEGAF00002337266

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.

113 652 707210 713 848303 874 264367 424 052387 048 411364 983 757313 608 909249 168 016184 987 948129 553 46386 348 97055 209 46134 078 26120 505 97312 148 5667 156 5664 258 9952 593 6431 644 6271 107 184792 995606 769493 907414 146360 146309 749275 003242 710220 092197 236178 095162 849148 372133 490121 418111 414103 41293 27185 78780 80474 34268 26562 91858 54753 16649 47446 38743 41039 72837 04834 95232 78031 86030 23728 75627 39825 96023 88723 17622 43221 06620 58219 44419 01718 01817 15916 86216 36915 72615 77015 11614 73814 31513 79813 70512 85512 83713 14012 32012 02111 63410 95010 97310 59010 1199 6759 5679 4559 3509 6129 4449 3298 5978 4508 2337 9687 8017 8597 7477 4897 1017 0337 0817 1487 0646 8916 7346 5796 6136 3006 0265 8285 8995 6505 4945 5175 2325 1895 2375 5595 3704 9364 9914 8805 0625 0504 7884 9734 8794 8534 9144 6034 4834 9294 4734 4604 2284 3454 0213 9823 9883 9303 8083 8673 9723 8403 8513 9333 7723 8933 8083 9603 5473 5703 4323 5053 6273 4283 4313 3083 4113 4363 5923 3543 3463 1653 1433 2553 0992 9213 0343 0423 0392 9993 0252 8732 9102 6802 7942 6062 6232 5212 5432 5802 5282 3962 4652 3582 4162 3802 3412 3082 2902 3372 2302 3032 2332 1992 2642 0452 1062 0882 1642 1812 1192 2442 3022 1002 0862 1082 1632 0482 0921 9772 0421 9932 0612 0601 9952 0282 0122 0361 9432 0492 1631 9531 9781 8952 0002 0232 0021 8961 9501 9491 9011 9151 9901 9681 9931 9441 8411 8791 8111 7041 7301 7051 7431 7541 6671 7841 7001 6871 5561 5721 5531 5551 5861 6401 5521 5451 5671 5681 6311 5911 5341 5831 5881 5171 5201 4401 4381 4341 4611 4431 3971 3871 3831 4181 5241 4211 4101 3901 2881 3731 3351 3161 3831 3761 2991 2531 2661 2411 2801 2891 1701 1281 1201 1621 1331 2391 1821 1761 2491 1651 1741 1771 1351 0941 1351 1631 2171 1681 1241 2101 2101 1761 0921 0971 0411 0951 0561 1261 0851 0491 0671 1411 0591 1141 1301 0621 0941 1121 1641 0569991 0751 1491 0911 0761 0429951 0411 0101 0271 0621 0641 0791 0931 0861 0651 0711 1001 0911 0431 0561 0491 1211 0521 0919989411 1021 0241 0381 0139589481 0261 0389931 0341 0121 0241 0021 0169931 0221 0821 0459419669621 0071 0041 0269419921 0401 0451 0359471 0271 0421 0041 0431 0381 0499559501 0109399869179189099008999058549187858578228388208488768741 014840877870947869907895818843835780849785845804820785844801814749761850741754762746742752733766759783710751761730659727695695701658743677687665648667688620657622654653603589616632589606606602644657620640627618587614671637624628615559636629585603621618637614604622572601562579548544571593584553536577520532534496531522518489529454473551531549527516576592503510501484492495508510560481540509513510493485494528455511572444455439461485462440461473453481443484460484450427485456447474464477449463425445429453445518459465458404412444466436453430400450437418448447455452466438462429435365408392427451410417398411380415385392385417438429375400415391339414448376399367414409417401456390414395389381362345358340384385353345350398348386416358417417404386339324358354349385365338323358335344345372333346358324359357356332335343317323357340347311353340343330318337344360314323317314299285324338296270321294311326279303331287281276304314289301306305347327276308298316287310265266294296263326328292299357318324330345323323354318328322332341352318358369333321337385302299323325309293290262302302297283282312282273302286271278318282300280295295285265283337319312300290280279295303300312254309299266291270292273276288318278296309260307266283293276284326287326268265304292274258283299278277259262248281292276274284267256251219244260240246263277252262243239249246270228225288258247246259231242238209247235247266216250249244228239241235231238254259252256241245297230219210220212220213193183195179217184194206208196208170200166189176161196192210196201212184198221214213201186203174213199190206204173194166183186190184167197195172172185186180154204158169193180203171151177181169143210188161174182181169158199152171166195167170208182183169207162180147166182180189171184224 802100200300400500600700800900>1000Coverage value1k10k100k1M10M100M# 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.

2 263 195000000084 579 7680001 066 665 773000000000583 421 6080000663 276 41100001 253 259 74500002 450 352 72700010 863 102 49300510152025303540Phred quality score0G1G2G3G4G5G6G7G8G9G10G# 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).

99.1 %111 323 04599.1 %0.9 %

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.

98.7 %110 860 02098.7 %1.3 %

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%).

0.4 %463 0250.4 %99.6 %

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 %56 181 86050 %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.

94.6 %106 290 46094.6 %5.4 %

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.

6.6 %7 366 4686.6 %93.4 %

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.

7 393 497137 257103 398171 533141 356155 049172 133220 050156 331181 987107 47884 42297 88095 06057 193106 87975 27486 642108 667144 576152 472166 740215 198145 701220 388318 32357 780532 24066 36156 38089 10296 77583 387112 78961 46663 93179 16296 16846 899147 3241 289 44195 370100 355148 116114 401186 719161 305236 374370 00278 81084 89084 25394 31262 351160 96088 50477 772169 37982 761128 161104 814 973051015202530354045505560Phred quality score10M20M30M40M50M60M70M80M90M100M# 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.

99.6%99.58%99.6%99.61%99.6%99.6%99.61%99.6%99.6%99.6%99.6%99.61%99.6%99.61%99.6%99.63%99.62%99.59%99.65%99.59%99.61%99.61%99.67%99.55%0.4%0.42%0.4%0.39%0.4%0.4%0.39%0.4%0.4%0.4%0.4%0.39%0.4%0.39%0.4%0.37%0.38%0.41%0.35%0.41%0.39%0.39%0.33%0.45%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped