European Genome-Phenome Archive

File Quality

File InformationEGAF00003611389

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.

399 792 765148 134 85749 346 62925 500 54113 220 6879 848 3477 485 5376 492 1595 722 2085 214 1264 826 8314 487 3634 239 1393 973 4233 755 4133 567 9723 385 7773 219 5683 062 6022 931 2342 779 6742 662 2932 542 0992 422 3292 323 1142 227 7212 131 6552 036 7661 957 9131 867 9991 798 5211 723 8831 664 6521 588 3601 523 5501 462 3121 402 3991 347 8731 293 1601 243 2851 201 4241 150 3361 104 5771 058 9621 019 042975 825934 004891 967854 420818 815788 909757 239723 926694 583666 642639 312608 245586 326564 381538 175515 106492 997471 721452 504434 918418 344399 861382 780365 034348 940333 830321 218307 316292 372281 311268 670258 751247 581238 365228 297217 683207 092197 368189 425178 795172 807166 567159 074152 740144 762137 313132 454126 665121 890115 376111 034105 117100 95295 06290 60986 59582 92278 77375 74871 43168 76365 07961 75357 97355 33752 57650 14247 22545 53842 19840 39238 42636 66934 65833 32732 75330 84428 54927 99725 88424 69823 47522 28821 27020 23719 28118 49117 10716 65015 86415 08814 45613 44812 82712 22511 57111 21010 69110 1849 6949 3048 8318 3507 9557 6787 4717 1846 8086 5296 0175 6865 7245 3765 2915 0794 7674 6624 4414 2284 0753 9183 7193 7123 6433 2703 3063 0292 9322 8672 6892 6142 4502 3502 3582 3002 1902 0972 1311 9311 9211 8461 7611 7801 8841 7421 6551 6161 5691 4241 4011 3381 3751 4481 3491 2591 1681 3711 1391 1411 1531 1041 0569881 00496491091593388687388493486082384081578482874277379970470267172981980380777178177674863368471268865970657461359557855158455758166553650951558353844251549444748345547141460445445244845748149549446345345445243740144644946039336437841640044537936831731132131830628133831631533433540630333935531528031030129037129927628627226429026331428225626527028828127026831328925628322825625824228629322623624325522423321818921620522323823318317519021929919817117518920619019019818418820117316919316914817815115015113216115315614016715814513814415314913915215115815112614314412312211711312314299116122112124111891041021031041231069491788074828669746757748364664460596058454539454645313042485348365242454753524455487350435036534437463135554639403927344036353027182728253127232725252924183140202635323236212433263127294028252935292925223120252730211921262728261930223217292920302934241821182720212023243129202235192019212924291215211618262917221635222419213327222423232226221521131213232724293129201013191698125256641138714947813410119761110128109146127131114141481112109108711983684611111013109134634133316372321344469734343431433255334352595484611743234223233333121221142212313435939164426335224522584535256472521233356648124423243735875755113485152386625232295462534662322361352242635411345518211433121122242426113653113343145423726413144112232441214324554342674652723351333213122111561100200300400500600700800900>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.

606 167000000037 035 692000301 796 550000000000188 646 6100000224 098 7650000394 517 4910000762 406 1430002 853 012 18200510152025303540Phred quality score0G0.2G0.4G0.6G0.8G1G1.2G1.4G1.6G1.8G2G2.2G2.4G2.6G2.8G# 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).

99.6 %31 632 07199.6 %0.4 %

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.

99.3 %31 519 08899.3 %0.7 %

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%).

0.4 %112 9830.4 %99.6 %

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 %15 873 73250 %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.

98.8 %31 355 66098.8 %1.2 %

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.

25.5 %8 093 99825.5 %74.5 %

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.

696 4807 8264 53012 2995 5835 95910 9629 0548 44711 9303 5643 3007 6965 4152 60510 0613 5453 9988 4717 6236 90312 0989 6778 19916 25930 7711 624150 0862 1992 1156 9934 1502 8729 9262 0742 3596 1185 4051 40014 023209 9099 2008 61613 8859 76122 38727 87328 462132 4557 77811 95410 06013 2857 23212 04510 5449 32342 21710 43718 91030 087 470051015202530354045505560Phred quality score2M4M6M8M10M12M14M16M18M20M22M24M26M28M30M# 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.

99.64%99.63%99.64%99.64%99.65%99.64%99.65%99.65%99.64%99.64%99.64%99.64%99.62%99.65%99.63%99.66%99.65%99.63%99.67%99.65%99.65%99.64%99.31%99.53%0.36%0.37%0.36%0.36%0.35%0.36%0.35%0.35%0.36%0.36%0.36%0.36%0.38%0.35%0.37%0.34%0.35%0.37%0.33%0.35%0.35%0.36%0.69%0.47%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped