European Genome-Phenome Archive

File Quality

File InformationEGAF00000864363

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.

331 984 362229 235 376187 561 531143 185 91999 568 75863 413 90337 254 91720 270 51010 320 0454 966 3762 315 0461 089 004539 235301 163192 425139 843112 36993 16279 96769 29560 20653 80946 74041 88738 22034 03730 98927 60224 86521 57019 31417 08615 23914 18212 87011 18410 2339 7789 0438 3037 5757 0106 6756 1395 7955 2975 0644 9934 5554 4214 1414 0333 8553 6183 3543 2233 0532 8892 9352 8692 6482 5452 4952 4452 3532 2802 1992 1202 0362 0881 9921 9121 8511 8351 7811 7871 7831 5341 5761 6281 6311 4291 5381 5251 5001 4051 3381 2551 3641 3691 3601 3361 4101 2861 2311 2501 2031 1751 2141 1941 1221 2141 2111 1601 1021 1331 0869981 10599998088986489887988891299087589880189985486288085986371374674976974478978273272167267165166667160763170165357762854753051259359155656155453852948056952056753653853053848049254249848245648149645550247146544344543645338846246543244241640646542343448845146748845543842841242540941742545539540042942643243340142641535136940137338931736736132534837331930935333829729929830931528326927429130229330428729930331831431632131631027731630929227627726626325226826126123021524528125625626622023622620522620121120817117319817918319918517518518318215817415617015016614015218418715616015914218918321616718718919320519516917915915716716715216716819317817315518117619417116814414817314516316414815514215714113217017312916313613416313714216414814415213914416716117518314114214314013115511613712312914511913114413413812712910915714412612211914011010810110498102102104106113991041099411098110113971018891939910392108104869973768374807481637566698674496672787074797072648078747874978180857272976374816768516458615750585357685156525160585062513443384340475242504556515078736967738062635850746061454761604542545447506677806845474754626767594848526847576652585465484961726264674366487274606463715560536249466560504667476948584758526351455465597748485865645461615442515867566278757958586065666471738980726684536956587366556670706975906579696758606869496349555164555343695255615148474751554848445139494647414143472840484333405044374643403648493849364032414338373942405148464050394430393332272934363640373118321828202326282820192120242422313421132026192016222418181018101628143414191921181518811172721252523202024182016193114151812232525231714241833222722252324202922221829212223222524191520151818171745222927191316161519161212161516131614251223209141616121024181381241413101514613912111812915611810878146138410135811107912713151461910101215115161410981163968138313512983576991069228461451413174149878104791513761111816747118114107895114567111181261571791163103675464104875597129873985681311151151163 491100200300400500600700800900>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.

00536 749 25700431 0891 827 7458 113 79314 712 7138 180 76314 392 2993 254 3092 338 2405 162 0392 394 7817 478 08311 599 14411 200 78415 642 3029 318 1418 707 4477 361 13917 722 45519 236 92922 292 53527 550 05543 558 72947 741 36347 416 80843 093 674100 916 315123 364 304103 145 513129 742 202187 384 181274 561 248154 663 433318 448 661254 755 058350 993 656418 091 100573 927 96300510152025303540Phred quality score0M50M100M150M200M250M300M350M400M450M500M550M# 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).

89 %46 624 98689 %11 %

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.

87.4 %45 753 84687.4 %12.6 %

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%).

1.9 %871 1401.9 %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 %26 183 13550 %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.

85.2 %44 629 37385.2 %14.8 %

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.

1.2 %653 2191.2 %98.8 %

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.

7 779 70622 68112 07310 3785 2354 3483 3007 6515 22147 32112 023382 29047 98695383 716469 6161 450324 54960 0658 8672541 18943 243393 03271 4904 628 0401 835206 7042 193 528162 94026 47018 81435 329 302051015202530354045505560Phred quality score5M10M15M20M25M30M35M# 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.

98.33%98.11%98.34%97.81%98.22%98.34%98.18%98.25%98.11%98.09%98.49%98.48%98.24%98.44%98.38%98.15%98.56%98.26%98.57%98.74%98.25%97.64%86.84%98.41%1.67%1.89%1.66%2.19%1.78%1.66%1.82%1.75%1.89%1.91%1.51%1.52%1.76%1.56%1.62%1.85%1.44%1.74%1.43%1.26%1.75%2.36%13.16%1.59%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped