European Genome-Phenome Archive

File Quality

File InformationEGAF00000904108

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.

22 869 94817 574 9489 943 1545 571 8362 600 8381 686 863850 074662 557383 284326 737220 994189 047140 284125 793100 50587 93275 88667 39259 13454 45049 25644 96840 31337 05935 35932 77030 38229 03927 42325 55924 31723 82721 68920 19819 86918 99618 22417 35816 54615 92515 84215 42614 94814 44714 37913 55012 98312 49212 27111 63511 54111 39811 16111 01310 78110 86910 1169 7979 9059 6379 2009 1969 0018 9058 6148 5578 6148 1898 1597 9587 6397 8147 6187 2727 1137 1237 1627 0506 9396 8676 7716 5646 3596 2276 3316 2576 1036 1826 1425 6605 7695 5015 5235 4495 4055 1775 3965 2665 0284 9224 9204 8654 7534 9534 5374 6524 6374 4944 5464 3654 3464 2824 1864 1414 2374 1934 2134 0104 0624 0053 9903 9073 9033 9043 7013 9983 8673 7043 7173 5143 4893 5213 5513 4143 3523 1803 2953 2513 2613 3083 1813 2743 1933 1383 1213 0712 9582 9822 9232 8202 8572 9142 7902 7802 7242 6782 7172 5472 6272 6602 5902 5812 5522 6222 5732 5812 5742 5272 4542 4192 3832 4622 3622 3742 2442 3242 2072 2092 1912 2712 0582 1632 3182 2622 1092 2112 0962 1702 1122 0921 9812 1082 0471 9662 0951 9851 9642 0051 9721 8951 9552 0111 9401 8441 8201 7791 7941 7661 8051 7701 7041 7471 6851 8151 7581 8381 6991 7861 7451 6581 6321 6711 6541 6701 7341 5951 6261 6381 6381 5741 6641 5001 5121 5421 5631 4641 5141 5551 4721 4541 4511 4721 3731 4801 4631 4871 4561 3541 4101 3801 3791 3641 3781 4731 4411 3941 3161 3261 3011 2781 3401 2521 3201 2931 2751 2031 3381 2761 1961 2071 1691 1471 1501 1441 0841 1491 1261 1141 1341 0831 0871 1211 0601 0259711 0331 032983995975973954921949979988916982934894918972972884896940913912823922878869908944848874859822814841801837793865808799796742801801785718791748752678740722714740677698671686674684681676692736695672693661658676696644707668695670685678607605655644658676625650650634609630609610589643630594596615616584615614582621571639611572595602584535551524537549550527493551503518490519523498510524518488449530511510496437504473532480512473493503479477445426444404433426470424428454446434416423404481432470409395450412386399388398381355416370371375373392391366362374323377382366288314330291349321337328344339342334303344326293323326322296290320319330302322302317306288296298289274280298279295301294306267273271272216289281283289257254237235252241242281240265271281234245238237238275233257240242245223244244236246226263272260276279258253269234239255255242256218271242279272252273240249265249256230245238227218211218234256240226201215200232204225203191223213181187198182209215213202205211172188207184190168175195184192197192175184203194178168173182171152167193177168167163167161156150188152161148165166162146163165181153155157142167140140159142168154155133139148150140112138120131139148150144141154146135132142140121154129138115126125124132131129121131138110124124971381231321481331121091171361061141121291271091041021141151171001021011251181051139010810610210496979193909810498827984848396781129780879791108917781879481998888836486100929585768896767880639884827893718181707984638184876582857975817070797577758991748181788675707872778277628190707084887779707368766380716972657360785968547470757077677274887077797266767370757965656865627859676480547567636764778477719680917466787380965984828581808872767955888680776162887974858173868579656672789873766177587366776468614754586357566362485964615160615645706956565360616272586456615857655565724153365455593853496342595660596251474751552659574856494715 564100200300400500600700800900>1000Coverage value1001k10k100k1M10M# 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.

25 2760000420 725259 9191 365 6021 031 835352 572615 140247 975253 674504 063192 273563 259460 796523 957898 893483 831799 865512 253953 9871 331 5581 413 7401 634 9792 677 6852 541 0842 556 1852 610 1936 010 4399 717 8225 972 11710 335 91321 632 99129 510 09615 746 13343 640 26628 635 37253 083 27358 343 184130 777 52500510152025303540Phred quality score0M10M20M30M40M50M60M70M80M90M100M110M120M130M# 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).

91.8 %5 370 72491.8 %8.2 %

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.

91 %5 322 26291 %9 %

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 %48 4620.9 %99.1 %

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 %2 924 24350 %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.

88.3 %5 162 87488.3 %11.7 %

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.

45.5 %2 660 03245.5 %54.5 %

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.

659 6826653868514175565028378855 4504 9221 8719 2951 6081 13226 8892 3437 3487 9741 98113 88937410 87642 7853055 804262171313397 65940861446477648483823 198230 4092 7208142 9662 6386286 0401 1381 65619 4302 5982 7723 6285 7882 8068 3066 5569 01615 92831 1344 256 701051015202530354045505560Phred quality score0.5M1M1.5M2M2.5M3M3.5M4M# 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.

100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped