European Genome-Phenome Archive

File Quality

File InformationEGAF00001404681

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.

510 000 340226 471 90184 086 70338 821 61917 103 5479 881 9486 032 7634 399 7243 437 7362 895 6952 529 9962 267 6542 078 1571 924 4911 805 4431 700 8091 615 5711 539 7011 473 3551 414 0551 359 8671 322 0211 278 9761 243 3721 210 4731 176 3811 141 5681 120 2721 094 7671 069 7951 046 4481 025 5501 004 714984 738967 111950 287931 961915 535900 412886 490870 826853 239838 687825 488812 905800 282786 934777 253765 659752 500742 044730 320717 533707 280695 561683 204676 185666 501658 201649 656641 452632 836625 016616 929606 974601 038591 513582 069574 130567 148560 339554 635549 378540 550534 604527 618519 357513 565506 910501 034495 352489 660482 061474 824470 996464 014455 604450 740445 535439 360434 479426 737420 842413 438408 257401 310396 335389 694383 165376 166370 980364 950359 426352 461346 678342 294336 734332 473326 383321 853316 273310 583304 264298 239292 027287 649282 342275 793271 868265 922260 164256 105250 725245 241239 629235 201230 689225 430221 000215 730210 316206 168201 674196 902192 635188 977184 647181 169176 946174 043169 175164 724160 780156 969153 096149 485145 945142 380137 800135 178131 921128 741125 467121 908118 394115 833112 756109 976106 765103 369101 18097 79495 51593 29690 89287 96385 87383 52481 04478 77775 92674 49971 61069 83667 95466 23364 23762 33760 63858 76157 48456 00853 58352 73550 43648 90947 56045 97144 87743 27441 84040 63339 04537 97136 78135 65734 66033 85032 36531 57830 50229 84528 58927 46026 57525 89024 77224 02323 21122 07621 74920 87420 31119 57718 92218 15617 33016 88216 32415 73115 24314 79514 14713 59912 92312 48712 05911 82211 41510 98710 90710 53510 0729 6579 2628 8748 6148 3448 0247 9877 5637 1317 2287 0246 8516 6416 2046 1726 1985 7265 6815 4435 1755 1304 9104 6444 5804 5184 3804 1224 1114 1633 8763 6753 6033 4063 4453 2423 0793 1452 9972 9332 8552 6862 6992 5072 4182 3262 2742 1852 2002 0652 1052 0581 9801 9521 9031 8991 8711 8251 7211 6421 6461 5271 5571 4851 5281 4121 2971 3521 3121 2601 2831 3051 2131 1541 1171 0781 0921 1051 0701 0391 0281 0421 036939952947907893917827889791797807786762771768715709689706651598692635640653599631605581579553534544572525491457488457446465485488450393462443446457370397380383389349349340355335341334319376349356329323336308310294288284283254254250261236243263241269263250232206239213235193206205192211184181167155170161162150144124150145134132122139147117134139133138931231331171261291271231101071131241379710410810110486106112798995988686789483757566818585767685831078271727975747091606480738363675676716361825859645358607157414643565258535640503952544163484146464536415054443750364038404246513557583747334542454552414742334238273326382730311536352440223324283035343026252818343426272823192530252424232323331431182124332213192434241517142220212224181616222320221715202225241925322620211923262125192516181824332615241414141691891219161316151719142021121720151515151316171921172328211317141613141491115141615155139619189671113710161214891017610698108799611759371451689710141810389116121213298810889589121114713810891277111012995965121397104813191016161310116587118681626691346666574755741563365647276665538844577744356263101397769811715741265176813681186147973581177648542695724455126324225223426323242344232632366722344554534184321248514341651522218142432426131215253241 064100200300400500600700800900>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.

2 163 9261 217 190910 1111 766 8312 955 29611 364 4454 350 4704 175 0475 829 3216 280 8364 983 5276 564 1537 401 0886 410 6025 633 5625 766 9367 210 1739 168 8948 680 1909 960 12311 922 57412 481 92214 484 81115 374 92920 251 50427 414 35846 927 40073 857 394126 429 365189 454 932358 196 166762 616 6161 445 191 648977 008 8731 019 824 8631 059 038 590769 712 317181 531 01615 673 3010000510152025303540Phred quality score0G0.2G0.4G0.6G0.8G1G1.2G1.4G# 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).

99.7 %96 291 76699.7 %0.3 %

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 %96 141 31899.6 %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 %150 4480.2 %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 %48 267 90250 %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.

99.4 %95 992 46299.4 %0.6 %

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.

18.2 %17 590 31518.2 %81.8 %

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.

2 498 2677 0954 64815 2325 2277 4157 84811 2869 74959 71723 46020 28551 39716 01212 514195 74817 29063 86239 69815 70794 3574 250123 210362 1733 76918 4243 4973 6882 9341 944 6704 7473 1513 4204 7563 6715 617246 232845 07510 77722 72121 52313 9125 75642 0969 53512 572183 48821 36421 19124 69841 31817 50049 99637 27952 03787 870154213 0861636788 813 4065914210112620945072 1100510152025303540455055606570Phred quality score10M20M30M40M50M60M70M80M# 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