European Genome-Phenome Archive

File Quality

File InformationEGAF00001404695

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.

439 909 638200 850 79075 653 36735 507 83215 797 5909 490 1935 815 3434 360 9463 418 1772 911 7962 548 6572 303 7462 111 7121 967 9461 848 4111 742 4491 660 2481 585 7811 522 6951 464 2751 415 5431 369 8241 329 2211 287 3261 250 7141 219 6871 188 4651 162 1641 135 9421 110 6291 089 3541 064 6811 042 6091 022 2321 002 476982 144959 506942 150922 852912 981894 477877 359863 718848 059835 474821 878804 410790 744775 681761 406746 226734 294722 348710 556700 970689 889681 976671 654662 121653 552644 731633 145623 953614 413607 760600 560593 506584 693577 759569 881560 824553 235547 418540 108529 920522 705516 756509 186502 247495 673487 347481 788474 452466 710460 839453 197446 941440 104432 755425 665418 980412 566405 564399 456393 578386 762380 165373 195366 986359 647352 539346 258339 540334 302327 920322 074314 674309 180302 597297 074290 661285 462279 517273 862268 330263 457258 628252 920247 641242 101237 659232 168227 500222 019217 484212 910207 082202 622198 458195 388190 250186 617181 638177 478172 762168 272164 332160 017156 170152 248148 093143 797140 079136 333133 407130 052126 644123 098119 830116 341114 661111 623108 411105 112102 35899 13596 77794 37591 58289 07586 53983 89781 36379 09776 56874 29872 45370 01868 06365 60763 64561 58560 29658 49257 07754 74553 11751 80149 92948 60646 92945 20944 25242 45640 96939 74138 58837 43135 67634 64633 79332 45131 87130 44429 46528 72127 89427 08725 86124 68724 11323 01222 54321 48420 98520 21919 49019 08218 21617 76517 18616 51016 21515 29815 04214 15813 66413 21612 75512 34611 80611 53411 28910 84010 29810 1059 6729 1989 0928 4088 5228 3248 0847 6537 4377 1287 1186 6616 6176 2846 1135 8075 4525 4965 3055 0154 8364 6614 6734 4214 3974 1074 0103 8743 6193 5543 3183 2333 3653 1773 0062 8842 9182 8362 5832 6082 5602 3012 3482 2152 2332 1682 1262 0452 0321 9521 8241 7691 7021 6971 6131 5991 5871 4961 4131 4341 4141 3641 3411 2351 2361 1731 1861 1031 1311 0661 1111 0201 0521 0319961 0479388928779338348338778397818107797507577107306486246266536406235485645445245264955175425225144834834965154824844464454354284334114223973693353833683483803793373613433833533913173483382963162713042932852942832742803033082492742502722252352312342462242252232191882122052051611661601631691851621681801721721401681481531521401191201411151081161149610484100102108101941031041071001018710611293108102928910478991017910791879210210187798984566682736268616773476864536074557057616558626465846061737066495348564447525556633650525858545250474832545251484452444348375055594352375952394550232942454440474457454639404238443326513130213640283224223829233228292221232334283331282529343030312837424125343242342723362933262927302833273834202118232626231820202514162527232435313528131519191323221681791817251923221013141013131510771819820151916202527172514182013131798231781212161571122131321149141114981681217981259510149115581085711991087778119499631211131158979107961068119591258871413101210127814698111151395977819463475957649969151276767966679105101111512814310984778164105567956891041132534777423337556524475363341742447723463336646663247136763185581071024761010987345397263276536677753882578437874886369721051239109359549811656535227464693337944341334114221511 120100200300400500600700800900>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.

1 479 23764 5011 058 7421 225 8611 443 46711 524 6683 666 1413 821 8865 598 3185 610 0185 923 2406 528 4296 810 7398 117 7697 921 5898 011 3325 757 9767 662 0828 148 0539 286 8769 800 39812 233 91116 444 70518 912 61419 253 00421 007 87031 368 63660 336 357109 085 995214 375 843355 208 518718 792 8581 378 516 816909 816 661867 003 607951 068 512718 050 341274 882 6142 720 1160000510152025303540Phred quality score0G0.1G0.2G0.3G0.4G0.5G0.6G0.7G0.8G0.9G1G1.1G1.2G1.3G# 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).

99.8 %90 426 86499.8 %0.2 %

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.

99.6 %90 281 17099.6 %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 %145 6940.2 %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 %45 323 60250 %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 %90 080 23899.4 %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.

21.5 %19 479 27221.5 %78.5 %

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.

2 314 6726 2484 10412 9564 1716 6716 8119 8248 91453 53221 15318 86346 74614 08711 486182 47015 37955 15235 16314 41886 2884 039115 598339 8163 47216 9882 9823 2032 6031 794 5584 2002 4873 0984 1473 1964 717229 976851 4679 59120 87319 08612 2024 83939 3198 69211 207168 61019 13018 88022 51236 68615 68244 66833 89447 98479 412140196 9111345783 452 96643132859416538067 1750510152025303540455055606570Phred 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