European Genome-Phenome Archive

File Quality

File InformationEGAF00002340303

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.

744 869 518689 541 335477 143 924271 824 613134 452 40759 768 05824 642 2389 705 0143 850 1941 646 639825 399492 765337 712261 062209 694169 733143 640120 016101 85991 74382 54874 85068 80861 22256 35352 73748 99146 46742 52139 73537 83735 98034 17431 91630 32328 97028 04725 83223 84523 43722 35721 19121 06720 74619 84519 13017 57416 81216 70315 62515 76815 40014 99914 11613 53313 18512 85912 10911 80511 78711 13610 72010 1089 7029 6659 3478 8108 7468 2278 3308 2748 0648 0147 5027 3757 1766 9517 0426 8226 5706 5176 2216 0326 1155 8885 6915 5565 7425 5745 2095 6125 1014 8964 8474 9024 9804 8364 8194 6264 8134 5444 4204 3604 2714 2074 1123 9694 0984 2363 8273 7283 8793 6733 8143 9263 5813 6813 5243 5083 5463 3493 5173 3493 1413 1923 1693 1723 0923 0303 0703 0452 8972 8812 8392 7132 6802 9242 6852 7332 5452 6012 5692 4972 6602 5742 4522 3472 1622 3802 3702 3822 3922 2472 1902 2792 3062 2302 1432 1602 2002 0671 9482 1352 0471 9632 0111 9141 8981 9091 9261 9791 8961 8491 8971 8452 0271 8481 8081 8941 9111 8082 0151 9121 9901 9361 8831 8841 9461 9141 9551 8441 8141 8661 8261 7761 8321 7971 8281 8691 7461 8051 8231 7831 6631 7321 6281 6521 7031 6831 6931 6361 6241 6421 5461 5681 5351 5491 4401 3871 4871 3591 3651 2591 3321 1691 1591 1281 0761 0821 1251 0651 0661 0541 0701 0179881 0131 0241 04088595791691592993197588187488690492189484883781879183280479486184577682580381579577572580380969479679075477876069273775369269366968766274567864462059061370266663863565360557757157756062661657156661357057655356154258457254456656355155655354853750252255551047951454351148851348950951351947650649247648449848549253352551351051750351153553755854150546849051247944547745649150547051151854454150147147951954249348948350951750348355150147748947849149247950547749946245348647046749249947151349850754553048451550053951353751750749351556251153550052457759248353852950952052645848852851651449951144647147850451744247251244950551246653247442943648144345145039646745846945344741641144742243435742341042440345349344539938740436237937541937240041435237134938434531929230931529730430130627133328328830430732933831029130829630131025828527728324428629227830226828326528026723123324326924926525224921426322424027026326324724225224423723624822524628424728724825325224324423523424222022124324122524022222919120222020120922423421120520621124322523220320921623223024226222022224025223921921223921121220921420221018220719119915917315717418215816917217716419614817617617314216916217316815015814615116313414913013513816316215214316213715614815614715814716815515116117014416814513915614016716115714913915212516114314914115813614914315614716216616013616012712313115814615211612414013214814613314613912313914214914313812816314715415417914714815013415515813513912212713812211912711912310211211610710913097103144111137114107135112102951201171111351221191271131261101141001431461331131351301171041281111251141151041031021121081211041441081251411101131191201251081161191081171081161341061191141091141181131081399311312110195108104110114979411996991161001041079510911111290105911081078798104939499102941189887891191268511487119113721079210073848575867710699928674969079719984909071746495738476799175689490858797858210092106916977758486767980909110287847492888483818072688994808087769281887986888792829777729274707762719080736767747681898190809380817385818687756279887675887384796887737471697573897674726667736693706663767376837677687168726275976742 070100200300400500600700800900>1000Coverage value1001k10k100k1M10M100M# 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.

334 946000000057 186 915000451 513 121000000000253 629 7760000273 927 4780000493 691 2810000919 538 2920003 841 934 45100510152025303540Phred quality score0G0.5G1G1.5G2G2.5G3G3.5G# 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 %41 534 54199.7 %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.

99.5 %41 438 52899.5 %0.5 %

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 %96 0130.2 %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 %20 833 63050 %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 %40 985 42698.4 %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.

8.9 %3 687 8478.9 %91.1 %

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.

1 619 56938 21123 28645 51832 89234 50540 05252 67722 08241 17717 96815 83323 05325 70012 44230 90720 57423 93731 68841 20241 38242 41248 04538 08363 207108 2116 430192 1179 8879 63321 13720 4848 36625 14810 0579 64417 61522 4565 75933 534569 01224 03824 19037 53533 06759 73851 60180 523114 41616 52919 36718 73222 22612 60019 88822 89317 99855 19319 65634 36237 624 315051015202530354045505560Phred 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.

99.75%99.76%99.77%99.78%99.77%99.77%99.77%99.77%99.76%99.75%99.75%99.77%99.77%99.77%99.76%99.76%99.75%99.77%99.74%99.74%99.76%99.78%99.83%99.69%0.25%0.24%0.23%0.22%0.23%0.23%0.23%0.23%0.24%0.25%0.25%0.23%0.23%0.23%0.24%0.24%0.25%0.23%0.26%0.26%0.24%0.22%0.17%0.31%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped