European Genome-Phenome Archive

File Quality

File InformationEGAF00003948116

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.

370 985 110190 076 84999 296 61462 449 38437 549 83224 795 14716 398 05611 707 5788 704 2276 843 2855 624 8604 845 6134 282 4813 885 9583 575 8203 331 8353 139 1622 961 2682 809 3022 672 8422 545 1372 437 3472 323 8072 226 3472 133 2912 052 3721 965 1141 892 2111 824 2471 753 9681 693 0231 627 4391 566 5451 514 3651 458 3531 409 3521 363 4871 320 2151 272 3011 228 4971 193 2681 152 4391 114 6011 078 2211 038 8721 008 640973 115936 312911 812883 707857 310827 164798 941772 889745 155720 382696 864674 495649 416628 852611 126590 385571 531552 375537 017518 914501 847482 441465 666450 981437 066419 217404 468389 579376 033363 571349 810338 694329 484317 774306 281294 661284 610275 904266 208255 227247 223236 911227 196220 468211 352203 749196 245190 478185 126176 717171 693164 235158 034152 342147 081142 099136 332131 473127 146121 781117 845112 366108 431104 244100 38696 94693 02189 18685 95782 98580 15277 43873 94670 41468 29465 82063 15860 32358 47055 96853 46451 59849 58148 01045 83043 88941 72039 63938 36737 31135 58134 51432 81431 25429 99228 92227 86526 11525 45324 62423 52822 86621 43720 63019 77118 92018 33317 15916 73416 17315 24514 80214 28314 12213 42612 87712 50911 98211 44610 99910 92810 3679 6329 1208 8558 5597 9907 9907 4677 1186 9926 6576 3886 1116 0735 6785 6055 4425 2385 0174 7614 6754 4664 5244 3444 0724 0083 7593 4733 4183 3043 2913 1483 0062 8272 7762 6152 5992 4252 3642 3142 3302 2222 2342 1632 1851 9761 9601 9181 9771 8711 9601 8361 7231 7701 8741 6131 5341 5421 4431 4211 3651 3391 3981 4001 3371 3381 2541 1351 1251 2841 0941 0071 1829889049289079019388659058869169539428888758238837057217467517297266876776676416136465705665325664974905094964994954704775134864584854334374474384154284344563943993633124493443213333322952883293212993313082812932703273043023432672632512572702922642582762432322342462461772032142182322192072111982122511971682051741762102262142142151961871901871881551851671601761661751872132281992242152042142242362481991991801861921991752142041931891931892242072271741851982412402031631861991801952031871831781841691691902001821791841591791521551691521551741601491551631551611531241271291281151161111271141381431071061051171441201141051291281081181201401231411051329410612211211594100120961051231258485808481806675791401698591668288776981879014012882698054604961565962757778709961586156545254555351544951495350384240415345494837524137474353524848465157454456575862574849515634465138545351475252445547584853444040504741404840384244403447404741364229324133324240403425313323242232434532201728212425393230322837314336374236313633313528312925171631232615262020243026222129312220252127182725232422192717192735262422192514161722201017202217191713181191313111114101797151014171516151013161316147211314142023101821121312151117142217151416716111114201915131013109139810955716121018141511132415191371491213171492015181418192118222816151117161810111717221422914172011613111616810139121212101315159101215152120191011101618131277101414101012981181087887767795913910109715141313161671111468105124599391257694978957129614911178493131061457775984459367810416103118691410815791391185129996117101114131411910111315101010912941055838911109756107478899108910494 362100200300400500600700800900>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.

38 5750000000000348 912 2210000000000000475 389 607000000000005 157 239 81100000510152025303540Phred quality score0G0.5G1G1.5G2G2.5G3G3.5G4G4.5G5G# 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).

99.8 %39 534 11899.8 %0.2 %

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.

99.6 %39 471 11899.6 %0.4 %

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%).

0.2 %63 0000.2 %99.8 %

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 %19 806 55750 %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.

98.8 %39 126 69098.8 %1.2 %

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.

17.7 %7 027 64917.7 %82.3 %

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.

819 8227 3724 29013 1285 1285 8999 27113 6177 21213 5703 7053 4106 8515 9052 63511 5163 5174 0746 7286 5516 01613 02110 2669 22918 96238 4261 841184 3212 3552 2777 3115 3632 67811 4162 3642 5645 5326 2701 84416 669235 74710 7899 28717 44112 44532 19728 67884 997114 1229 25013 44613 04217 6469 08214 85214 30011 82049 55312 44023 78637 723 690051015202530354045505560Phred quality score5M10M15M20M25M30M35M# 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.

99.84%99.85%99.85%99.87%99.85%99.85%99.85%99.85%99.83%99.84%99.83%99.85%99.86%99.85%99.84%99.83%99.83%99.86%99.82%99.82%99.84%99.84%99.86%99.5%0.16%0.15%0.15%0.13%0.15%0.15%0.15%0.15%0.17%0.16%0.17%0.15%0.14%0.15%0.16%0.17%0.17%0.14%0.18%0.18%0.16%0.16%0.14%0.5%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped