European Genome-Phenome Archive

File Quality

File InformationEGAF00002485953

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.

370 087200 388146 465121 347103 95592 27084 97877 86972 77666 88663 82657 98755 10249 62446 52642 72739 43035 78132 26929 19926 50124 55921 92319 90917 85516 51614 65112 80811 50210 1669 1028 0237 3376 7835 8775 5025 0424 6794 2233 8323 4933 1632 9002 7682 4072 3062 1562 1071 8641 7711 7021 6421 6611 5481 4211 3331 3311 1651 1491 1011 045987931855821789693654623581545527564455447515411397365336353314335318311285291300300260274281238253216207185227165188191196166145130139161125130159140119121152142112105104116131981138883767985879776645569675358546746706063694934544468425742727545535663578163695865565469667761524057575665516444493451354229324338353828262957263134383129193232274135272529372326293421292723222236322021141827241919211319171626282032222928542626251915141917132333231321182723141020151820141216122099131516108121376131072794117681012151211711487975134119139358414685106119313141089610813108475669913121012125161311916279410475799289933757834584519247676469634246610497789838677574525785585111061213751081110848711111271254111378811513158386766514645867811141158634468117976365329234441186310947446775671057827665454634623133361114243123422212242146123311164212251211221112376545431411225512232121411221211153131112114123221112211312122111131131111212111121111114212121111212121121112131221111182311121112212242221112211131111111213122142225226413253322223122112211212231131232214121231112221314141211122121366100200300400500600700800900>1000Coverage value1210201002001k2k10k20k100k200k# 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.

8 6170000000000000188 277178 377954 8080000000000855 42142 8890365 925529 718135 282182 6281 220 2143 166 9371 390 3781 035 8992 461 60611 514 60627 010 96800510152025303540Phred quality score0M2M4M6M8M10M12M14M16M18M20M22M24M26M# 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).

48.2 %329 11548.2 %51.8 %

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.

45.3 %309 47445.3 %54.7 %

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%).

6 %19 6416 %94 %

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 %341 61750 %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.

40.3 %275 59440.3 %59.7 %

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.

2.6 %18 0532.6 %97.4 %

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.

383 7601 0303027597605058661 7213202 013684752322 9692601 4541 0461691 592199335 815101 359428235 393108242222122 18449 728644152126242218141 948749854140341301021944001 148184 576051015202530354045505560Phred quality score50k100k150k200k250k300k350k# 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.

93.03%94.85%95.7%94.48%92.29%93.63%95.77%95.43%93.63%93.15%94.81%94.28%95.9%94.55%92.15%92.41%93.73%95.98%93.91%93.88%93.53%94.45%94.89%98.48%6.97%5.15%4.3%5.52%7.71%6.37%4.23%4.57%6.37%6.85%5.19%5.72%4.1%5.45%7.85%7.59%6.27%4.02%6.09%6.12%6.47%5.55%5.11%1.52%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped