European Genome-Phenome Archive

File Quality

File InformationEGAF00000642974

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.

227 731 08940 498 36510 748 3646 852 2605 415 3844 711 3594 218 4693 828 0993 517 5703 249 7963 000 1612 778 4522 575 8002 379 4772 202 8652 028 6351 875 4251 734 4481 601 1061 473 2001 360 5571 252 1981 149 1981 060 758976 082894 125825 835760 347701 817650 487597 314556 282518 435480 932443 195410 862383 425357 628334 332312 465290 873272 542254 718239 086223 993210 065197 641185 273174 292164 257155 125145 381136 819129 163122 831114 909110 440104 35498 45392 73087 10483 14378 48874 66271 61967 17764 44561 09558 03755 70353 06350 53847 90045 24543 48341 48739 58637 65335 66834 31832 95131 62130 12628 91127 78927 00325 86324 76623 77822 81622 01021 34820 35119 24218 66317 90917 43416 70816 23915 74115 24814 44114 14213 45013 15512 74012 39911 86311 71711 03711 02310 25710 1049 8569 4609 1629 1088 8088 5258 1677 7867 6797 6797 3377 1486 9696 9496 6866 5686 3916 2736 0465 9935 8605 6695 5355 4715 3045 2415 0704 9174 8914 8174 7134 5754 5524 3524 3144 2774 0804 0123 9083 9383 7363 6553 7123 5363 4403 3223 2633 1623 0953 0932 9772 8582 7792 6802 7342 7912 8392 6062 6292 6742 5452 5972 5162 3952 3012 4192 3462 3662 2312 1702 1382 2072 1381 9902 0221 9591 9441 8281 8411 8671 8071 7711 7051 7201 6201 7011 5981 5691 5831 5481 5581 5231 4771 4771 4601 4931 3861 3731 3291 2971 2921 3521 3251 2551 1941 2441 2121 2501 1661 1761 1001 1151 0621 1241 0931 0479851 0451 0549579639891 0129759508968589028498777568168107917438157007097787497808117997777737667127396736976646696816816286286476716937026906886416836776257036236025815795966055965666015646145985705815425525895415255355325575175164894894965185015005345154854884905084574304564984554534674534594284684704284524384644514514554464774594274754664254674264134283994164044183774144234034154033993814314324204153784214243933653623453303363343353232983483113043232783112992562692913132512622532832342442542512332762612642512632482322122032362232452232122232602432372492282132552202421942122002222022091651661921852061831791701671411671591471581341761481691361461391361381371481531361331611361261451361401251141201231161071211391181081131061119492929588100949999106938592888089928084887573849071715788647190856957726477684852455261505662405252495654506062505142485554555150404843465050495249455942454840574668485449503443454560424053374346454355473433534539553230323631293030362928313139222032263744433234343528493638333244353335274127402936383936283642343334393230373238293229343137334132322624252928342324232724261618182912281418201718221716211118151624192620292822222123181628131316182517201824181617181122212219142213122315191118161119151913181211191510119131315161015178141312129171192014131912101312101099201510121013129141041189751015881012109926575634383105851013889765793882106558396874954762621133313743488510651081541111714872877458673555435356415363435224456334111437313637273792553443853862423231465431742133124522221249113222322231213111363413236321522231311 938100200300400500600700800900>1000Coverage value1101001k10k100k1M10M100M# 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.

00260 866001 465 921907 3343 977 9032 873 617920 4291 642 075750 966653 3241 196 210485 6791 461 778963 8951 239 5332 246 2001 138 2012 177 1741 137 1312 082 5102 904 2052 932 4483 654 9736 329 3874 766 1545 282 4256 477 87312 028 41221 436 35113 455 94727 079 43685 123 36287 176 24646 200 928164 413 71284 831 681207 390 558225 655 881651 666 87500510152025303540Phred quality score0M50M100M150M200M250M300M350M400M450M500M550M600M650M# 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).

98.9 %22 240 59298.9 %1.1 %

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.

98.6 %22 172 03498.6 %1.4 %

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%).

0.3 %68 5580.3 %99.7 %

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 %11 242 58450 %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.

98.4 %22 131 14698.4 %1.6 %

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.

2.1 %473 8472.1 %97.9 %

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.

2 655 2682 6742 1644 5762 3656 0835 39911 1818 69926 30120 9736 34642 9808 9177 88997 17617 21748 24335 33312 60067 56584343 435153 7497788 5279579761 046584 9962 6872 1482 6763 3383 3524 66892 957282 6808 9502 40415 6968 4741 41222 6201 4142 27662 3862 7744 2464 2028 7924 79414 51213 80621 15037 93488 61017 878 954051015202530354045505560Phred quality score2M4M6M8M10M12M14M16M# 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.

99.72%99.72%99.78%99.38%99.8%99.83%99.66%99.73%99.38%99.44%99.79%99.86%99.84%99.82%99.6%99.62%99.72%99.58%99.82%99.84%99.62%99.68%93.36%99.6%0.28%0.28%0.22%0.62%0.2%0.17%0.34%0.27%0.62%0.56%0.21%0.14%0.16%0.18%0.4%0.38%0.28%0.42%0.18%0.16%0.38%0.32%6.64%0.4%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped