European Genome-Phenome Archive

File Quality

File InformationEGAF00001553464

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.

5 067 998895 604477 511346 956271 019226 267195 510170 182153 363140 870129 736119 078111 617105 606104 18197 99594 34993 95485 61784 05682 98679 03977 33075 72972 06272 89570 70968 44468 65166 09565 63560 62661 46358 61158 64658 07455 93255 22054 29553 29752 81553 10152 15949 45049 79847 66847 92946 60445 06844 00142 68742 02041 14439 71638 29238 72538 18237 50136 52736 05234 02134 46034 37333 50832 68431 54231 15330 90929 96629 61527 49027 14926 38226 49825 27724 32324 16023 33323 56722 76622 33421 82521 21420 57119 99519 51319 02818 48817 93517 65916 52916 73015 76115 61915 61515 10614 53814 08713 60713 43612 79212 74812 42611 96311 01510 99810 8239 8269 9329 7639 8729 2438 9859 0198 3958 2487 7077 6897 4137 5726 7486 7816 8476 5486 4036 0645 9085 5885 5625 2684 9945 0794 8594 7904 4904 1623 9884 1333 9233 9773 8463 7733 7123 4473 4643 4143 2353 1443 1252 7582 7722 8422 6822 7072 6492 8302 4892 3402 2642 2812 4542 1122 1732 1532 0081 8911 8841 9971 9011 7571 7471 5721 8111 6391 6021 4061 5751 5751 3591 3291 3941 3801 3011 2791 1911 1371 1521 1651 0441 1041 1751 2301 0991 1199709818651 04683593686880282575684483080786073678478771868671768968364264861162759659854869255069961466358854161850755146549064055546149950141439442144139851842237840137741034240637344837749734732038333834839334632435333929431932444929129627525927929026830328233025522226325524125121825035829724037136027826828322225226537622120119124929822823420225823119919617319316515516620722319429120330621618319525619118720518915915618319225519416123815716117914616429716615015218417812814614513617116520612913413815413011913916112117414416220912414312713912315811312212912110010110212613611090118109114102103101148971161301369312711513010710995912008219910491879686106867096959692949685828611297918774849410982726867979310878847675937077667367887973756563779079877882658364581557089826274565651687362555840514684605751717473925492496662526255756949323929303140403653383328904339544355545349104535052463343393036581063236301264742584642674257394634415643434035514437464462443235355711439524138243738493440605835445448604533525133434037245241284339433251484756453948483836523733314024403638353742414354515726342923342834301493044423848393634343127354232322725253029293014025282238212416292514211819153321181818211024271616241321182012715145731171813151526221181612144196713101826121613241518181219613128132012131171112151110991491416412127648155201016912961099733274647713881312121554363010712101371210121310151415444317151094627912877967985631478106815779811116911121010213179121412898576612117101011515148888897859111571371314899956510911101259747813818915771215181371081411101721151511151591399115811912914191510108121014861211122014141513162213191214915141822112215111712161396131419131914151912151351521151591312191220 400100200300400500600700800900>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.

542 971000000000000019 403 81800000003 188 436000014 614 2290000030 124 116000269 315 93000000510152025303540Phred quality score0M20M40M60M80M100M120M140M160M180M200M220M240M260M# 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).

96.1 %2 591 18896.1 %3.9 %

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.

94.4 %2 547 12694.4 %5.6 %

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%).

1.7 %44 0621.7 %98.3 %

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 %1 348 75850 %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.

76.7 %2 068 33076.7 %23.3 %

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.

17.1 %462 06817.1 %82.9 %

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.

914 7356 5833 05913 4772 2833 69332 7995 4553 1169 8852 9522 63613 8344 0411 5514 8501 4991 6969 0832 7121 6315 2292 6254 6769 9207 0831 78017 1391 7731 6637 7052 6871 8855 2332 3793 4417 0473 0371 6086 28535 3942 6787 7792 3733 1533 6986 3763 79912 13514 3942 2183 5252 1463 2267 8501 7362 0583 9713 6163 0801 969 803051015202530354045505560Phred quality score0.2M0.4M0.6M0.8M1M1.2M1.4M1.6M1.8M# 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.

98.48%98.4%98.65%97.87%98.76%98.78%98.42%97.74%97.77%97.59%98.71%98.86%98.3%98.49%98.79%97.63%98.56%97.77%98.7%98.08%99.45%98.3%93.28%99.78%1.52%1.6%1.35%2.13%1.24%1.22%1.58%2.26%2.23%2.41%1.29%1.14%1.7%1.51%1.21%2.37%1.44%2.23%1.3%1.92%0.55%1.7%6.72%0.22%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped