European Genome-Phenome Archive

File Quality

File InformationEGAF00000659682

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.

60 747 84931 039 53712 150 7905 719 1482 419 1931 560 332841 164619 955410 570320 880239 448191 124152 534126 615105 47590 07179 13068 21660 38653 54548 87144 31039 70036 53533 20231 29429 01427 23424 93723 72322 37421 00920 60319 55418 82717 62417 42316 87516 14615 56915 30414 70114 33214 19913 71913 74613 17312 60612 54412 42711 98311 72811 74411 21411 12211 09010 99710 50610 38810 04710 11710 0809 6879 8029 3589 2529 1999 0708 9339 0868 7068 7658 3288 4338 7148 4338 3808 2618 1318 0217 9197 8857 6467 7247 6467 7427 6327 5097 3377 4107 2287 2077 2037 0287 0716 9306 8776 6406 7966 7516 7476 6756 4956 3786 5046 5486 4506 2606 2996 3626 2916 2726 2646 2456 1296 1745 9615 8655 9645 8205 9595 8615 8515 6815 8115 6345 5535 4345 5705 6405 6875 5795 3935 5695 4625 3825 4475 4295 3705 2325 2355 2105 1805 1755 2545 1515 0485 1234 9725 0665 0124 9914 9135 0294 9674 8474 9805 0044 9464 8014 7874 8184 9834 8214 7724 7664 8744 9364 6584 8874 7024 8094 7094 7074 7124 6054 6744 6824 5654 6214 6334 5564 5624 3304 4904 5824 4974 5514 2914 4454 4294 4114 2774 3694 3434 3174 3784 2674 4004 2884 3304 2844 2464 3044 1084 1094 1264 1974 0394 0384 0483 8904 0174 0073 8763 9514 0393 9074 0073 8883 8183 8463 9223 6423 6723 6953 7123 7493 6593 6463 6373 6573 5193 6423 5063 5183 5363 5253 3823 3133 3513 3023 2063 2453 1683 1513 2293 1152 9793 2003 0923 1283 0843 0832 9152 9562 9832 9122 8982 8762 8642 8602 8112 8532 7842 7882 7882 7292 6552 6802 6682 6752 6602 6332 5642 5292 5322 5132 4262 4032 3272 3012 2292 2442 2892 2522 2972 1592 1212 0662 0222 0902 1101 9892 0952 0571 9212 0291 9591 9291 9971 9401 8841 8451 8081 8511 7991 7581 8431 7931 8131 7741 7491 8321 7421 6841 7391 6851 6601 6411 6421 7111 7071 6561 7311 6181 6391 6381 6861 6801 5821 5941 6361 5271 4861 5311 4881 4991 3781 4001 3751 3841 4471 3821 3301 3401 4211 3541 3741 3131 3401 2431 2281 2531 2311 2171 2351 2691 2631 2591 2131 1381 1331 1541 1091 1381 0441 0731 0871 0691 0731 0681 0131 0491 0071 0491 0731 0021 0451 0621 0421 0401 0141 0579629709669429439409479219498878708308618648217818357747267107627167296987026576736347486816586796606686206105946446045605786125616095665935485555555395605125285084844914765125094894964505165054634914444644233914124053903664173573623443583213503543313393153113433123142972912922972913012812882952762862712952272572632402562252122322392072042002121681861921871941801901491781381701741661401591491429212811012612611612811398107116101931061179988112100819190869483957272907810378767688548270726979717092675048587679556173507963616257686644596254555466395464615255574558474955425134494052374343313824443637373337333227243525202922202620282622332222303024102518201927132819162220251832141719252120201821192118112311172212121623191218121710161314211613192018182317171217161818211612242617142016151219252119131918121614141414101414192314219131713151721121718192020121014191517141521151322131113911151414151412121120148149161515222021122417151920121418117222012211722151815211417221899141214191081172313201316201417132116181823161616221212131414141417131216101816131010661010891310115659681181510109101614367151095815159117781171048811769966666810111166117895108466865141016648711141010989510951077785131089981021371512968108610589673106957367511781342913669951111679537541 957100200300400500600700800900>1000Coverage value101001k10k100k1M10M# 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.

300 3570000560 098280 6381 617 1751 139 434379 609705 721277 686304 281515 821203 977670 542484 899574 0241 011 343538 149934 247557 4361 036 0061 454 1531 541 0311 762 2802 855 4402 803 6552 620 0012 902 8136 455 58011 067 1146 381 87011 996 63425 125 26335 328 25717 645 94351 511 15033 315 48162 499 15972 819 942163 705 09100510152025303540Phred quality score0M20M40M60M80M100M120M140M160M# 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 %6 950 53499.1 %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.

98.9 %6 932 96298.9 %1.1 %

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 %17 5720.3 %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 %3 505 88250 %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.

98.6 %6 913 75098.6 %1.4 %

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.

33.1 %2 323 75433.1 %66.9 %

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.

293 9481 0275651 8908741 0878331 4451 3677 8305 4702 8089 7212 6901 74928 1173 06111 6539 0072 72316 01060514 72753 8144473 077357393497234 0328967607301 0107581 26232 379114 2253 3741 1384 1923 4021 0687 5081 8222 43626 9124 1624 2945 4289 2664 36812 0849 60612 97223 16042 4225 968 306051015202530354045505560Phred quality score0.5M1M1.5M2M2.5M3M3.5M4M4.5M5M5.5M# 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