European Genome-Phenome Archive

File Quality

File InformationEGAF00001404634

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.

479 265 108222 651 23185 907 45640 559 09018 140 35710 551 4486 317 9974 563 2603 487 1532 913 0762 518 3302 245 1042 038 0141 888 0071 763 6941 656 6471 575 5231 501 2311 437 8971 383 8751 331 8821 288 8341 249 1811 210 4631 180 3181 149 0921 122 3541 092 7541 067 3481 048 5741 026 3271 006 416986 346969 791951 330929 875914 798898 229881 079866 832851 974839 326827 641813 222798 828786 609776 596763 274751 347740 387729 761719 499708 290695 989686 045677 356666 148657 165650 542642 968633 331628 105616 569611 307603 218594 590587 979579 026572 222566 549557 153550 388545 029537 980532 438524 965518 938511 869506 887500 855495 975488 667482 906476 598468 651464 201458 798452 636446 923440 527433 063428 048420 869415 735410 364405 324400 033396 815390 375383 839377 758372 352368 144362 230356 484351 166345 646339 769334 036328 626323 326318 384313 918307 488301 628294 652291 332285 858279 475276 026270 232265 784261 520257 014253 055247 476243 489237 951233 408229 580224 863220 136217 116211 454207 747203 184198 989194 903189 804186 142180 771177 357173 920169 322166 495162 346159 047155 120151 320147 890143 484140 604136 540133 917130 137127 560124 263121 449118 265115 133112 638109 846107 537105 123102 659100 33896 99594 82692 99889 93788 23985 43183 90081 03578 59776 55874 42572 55669 94568 10266 19964 84462 95861 03860 09558 30056 13155 01553 09351 58149 97448 42547 78246 44545 08743 21942 58541 83539 97138 77337 38336 30235 33733 96433 37432 19530 88929 81929 46928 64027 27326 46125 68024 98524 31123 57922 78822 25121 35320 75319 62319 40618 55118 25417 30016 76616 33115 97914 97714 73614 42913 87113 02512 73412 14112 11211 56811 15510 92710 65010 1399 7169 6199 0828 8498 7348 4758 1467 8577 9367 3077 3057 1346 7496 5636 2986 0035 8875 6935 4125 2445 1144 9644 6814 6224 4214 3204 1744 0013 9253 7693 6723 6743 4463 4133 2503 2003 1433 0702 9012 7612 7652 6642 6492 4242 5172 4572 3772 3592 2712 1672 1142 0582 0361 8281 8571 8671 6881 6391 7611 5491 4621 4621 4951 4311 3901 3891 3211 3051 2891 2511 2381 1321 1901 1361 0511 0511 0941 0259911 0011 0429961 00396695392692696293682187479977672867566866869469969668167167467662962462459057757960655659654158351549854454251847449747852645445145545044042243941039637435338138037235134134233733233232929831227528827031929827925924726026429528426226426227725024625724622122624522722222922824623122723519924019320419318919419019017018217516116616314315014415615315413815415814815613713915613412212611211410610996113125909311810710710898909891105117919093909691809999989694901021038785729475788584888393848377716570695660566552596756766439536166684460535344615349556242494142493550495542393041323834373735394832523238304841362232353440353131362337303628253037252531293636334047293027283126262727251624273332313030353034302836291728323330303433223123302018392521143420261827192117132120142225193216192214231719151927202320261914172114212515151315161811121515131731191321221820152414201820131918168142011968139911101413107467751291281097106101110131698151915887121491279751293651010877115976691396651187324539454527636452548386554666211353445556566861210366579443941910610114886997610133912666136910485737966663106854114101481061388582757117846294811673456871284610868436613451013410989711128774549511211672553925565473345234542274111123212113242322121436132225728100200300400500600700800900>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.

2 751 8861 523 117553 5661 261 7102 554 93611 782 9202 228 3794 137 0914 887 8294 454 6015 583 1345 299 0386 529 8287 099 1947 291 9126 458 7126 580 3077 720 0236 348 7957 600 44211 267 01513 357 26516 649 18817 519 03219 731 08025 760 82958 299 802109 466 387187 995 033319 117 913725 302 3021 344 653 867774 840 3051 014 113 7941 138 302 7701 002 949 839400 678 421134 988 2732 504 1150000510152025303540Phred 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).

99.7 %98 673 45999.7 %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 %98 506 91099.6 %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 %166 5490.2 %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 %49 467 63150 %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 %98 346 86499.4 %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.

20.8 %20 604 50220.8 %79.2 %

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.

2 557 2586 5564 07313 6634 6487 1367 54510 3559 59955 78422 76420 92750 71215 47112 794200 60216 85355 86537 83215 85194 1234 568128 650375 2673 77320 8563 1913 5532 8971 949 4564 4792 8243 4154 5143 7335 440250 569879 50210 54823 83821 21613 4075 12142 6959 38112 129188 18020 13820 46823 81939 07617 56247 54236 52750 86385 932143214 5271828591 110 254481349212121851773 4010510152025303540455055606570Phred quality score10M20M30M40M50M60M70M80M90M# 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