European Genome-Phenome Archive

File Quality

File InformationEGAF00001553350

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.

4 689 287879 501493 836367 325301 247254 408223 617204 653179 940168 640160 013150 510139 722134 892126 618120 937118 689111 096109 47699 65699 66595 90991 50089 20886 17684 27180 31179 12778 18179 19075 68671 82771 11871 35170 31869 89867 50866 40664 37363 74761 93662 24660 64958 81857 26556 84257 41954 01652 59151 23849 45948 52647 76047 20145 24343 45241 91541 60340 55338 35738 04137 81636 67335 96334 01334 13633 08731 61630 49130 00029 11627 87027 19126 32325 70525 94423 92923 20922 77621 94321 26320 80920 10119 92419 43418 86818 35217 43016 87716 03015 43915 46714 98214 13213 50113 22112 65712 29012 05611 90311 32910 52810 13910 0739 5089 2829 1378 7378 3818 0517 9147 3007 1697 1176 7666 9396 4286 0455 8325 7595 3625 2915 1894 8494 8204 8304 6134 3964 0503 8604 3763 8923 7193 6083 5983 6023 7483 5903 2663 3292 9432 9622 7373 0392 8632 6802 7862 5522 3512 4172 2342 2342 1092 0932 0301 9601 8041 9651 9442 0091 9081 7181 8921 6461 5481 5181 6311 8491 3851 4641 5441 3631 3821 3391 4651 3601 2841 2501 1181 2311 2951 2581 1301 2041 2491 0179981 0861 0431 0201 1289109801 0289389179098978938631 001848806880889750796817805825797785753759667759687573639620736687665672569595604637530535586557517522488622515455430561453404447435400420357412409396418364333360471396363348343362344381387425310320313365317330309357309324356281280408340376298354268314239287225245214230200253231237222235280272267304232244247222199218261304183256186163172144159182151158146198183159187207158112179159148122145144130144116151164170100145127113147114140128115110135125137147125134124140151136115114119112125134103114128112116981131329912186779512312510810014686154901559275811109977759386617998745986827267667283567991729478659491837964618882101596663839394648779113651737511262160746068161697286909854545759495950515281564911651633847615359494655413957736053584354794945515869555749515646446153524860555043444841414544394235757546384280574647312839294765394940453349263034384034301094146293937463310433285338262432413235312629383224192533423130283024323716233727353024202726265233172229222226201724261525201716183124122423302623222118163118262423202711147237174122263020192620242315201220181918152014202412561115191710171316101722151715182412191125217232627243418122020252822292323242989202225131812915222515251446263621231725151916122719161915202223916182116142611111511111213181416202319191412171636132621142315271622251620182020121111181633261715131316101072112121819291719422516272115171720161712271216142312181819916922161511910101181310111910201110191323111813202324211424151613131218141910131024971416141318610111910101314141191291516131371191191311171113918211347171812121413813102024171724861315121310251012116614616125751198813106101716124159689691257171941271261312106106121177810991185787797213721381189139874119614151011691421 313100200300400500600700800900>1000Coverage value101001k10k100k1M# 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 194000000000000018 660 85500000003 144 720000013 927 1890000031 767 865000257 379 17700000510152025303540Phred quality score0M20M40M60M80M100M120M140M160M180M200M220M240M# 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).

96 %2 499 35096 %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.

94.1 %2 451 01894.1 %5.9 %

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%).

1.9 %48 3321.9 %98.1 %

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 %1 301 94450 %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.

73.3 %1 908 54273.3 %26.7 %

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.

13.4 %347 70513.4 %86.6 %

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.

705 9626 7513 31613 7332 4383 35535 8525 3683 52910 8563 4703 23616 3484 0751 7814 9351 5101 5429 9762 1351 4434 7802 3634 4189 6555 4391 84617 2381 5821 7418 5702 3652 1414 9922 4143 7677 8342 7301 6906 02832 3432 4848 6762 1793 1223 1945 6633 51313 06613 5592 0073 3021 8553 7559 1361 7432 1334 9363 6622 8302 113 691051015202530354045505560Phred quality score0.2M0.4M0.6M0.8M1M1.2M1.4M1.6M1.8M2M# 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.

98.32%98.18%98.51%97.6%98.56%98.77%98.64%97.64%97.77%97.33%98.32%98.82%98.04%98.73%98.8%97.95%98.51%97.5%98.35%97.64%99.21%98.46%91.67%99.75%1.68%1.82%1.49%2.4%1.44%1.23%1.36%2.36%2.23%2.67%1.68%1.18%1.96%1.27%1.2%2.05%1.49%2.5%1.65%2.36%0.79%1.54%8.33%0.25%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped