European Genome-Phenome Archive

File Quality

File InformationEGAF00003448830

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.

29 012 33119 934 419534 3081 903 68383 585196 15637 51540 53522 58421 54016 34314 98013 71411 83610 2689 3108 8067 8737 1126 2386 4885 6375 2304 9144 6354 4814 0954 0073 9903 7263 7423 3153 2242 9792 9202 7242 4712 5742 3452 5302 0402 1472 0042 0492 0042 1591 9541 7381 7701 7411 8761 6641 7191 5081 5431 4071 4481 4231 4061 5701 4861 3251 1871 3601 3041 3021 2281 2931 3551 3891 2141 2331 2261 1231 1641 1181 1301 0071 0851 0831 0811 2131 0419871 1921 0101 0019859709601 00492195182185382294692788686089682879283285088783486481880571073574373673573375181667867870471171268381863969366359860560559459059159258174163459256152754061354968157553855652860155656256252251052256248863157258655053152151752752949952952151651145046546850848347948045946843247046044143541242841842842840941941644442642642543243843345741539340041141442737643138737639938643138841438539740140737636237538537940441840637736238139237738139735238934938936438535934735137536634935832535534534335337736835135937934530533932932133431529131430933732132829532532229729929632631134631231528732128132231430431231230032927829228531331129630126632427126527929428528829526930528427827930328430030029126928228126628024426329825726424830327628629731225128427527726825422927228629324726128527625526926426425525725326425123324926524824623222623722319826324723922823724823226326523824524526823527624925125724826427322524124223124325422325623324826021323622823920423723625122022822722124222924122124121723320321322220820722322921320921621920219922622321122922222421220021522618621819022621919820418218419819520920022319018319418519420218618919520318821521520020719821321019920022120020722220220321822718220321318417520020719019115520119421117118118019718720818720920820319918318918617119334319018917318520817319619718919017017616918420218918120116419516715717219718217718917215815018716115615817018118115115315714016814316115816615717314317117014714616916915115915115116116813616916315116315413815114614514114914114915114714312113213115415016916017115615212914715116513413313013314412514415016013515013312413713112313513413115811013515313613015113614514813512412813514113212314013910814213413113311614314313713613113414112613112612311812313613210610611413414512814813010813913211913811811614913111210812110810911713912011511511597122110135971321201141131361301061241331001211151251051251201041191191041131151261059711310910611111810912111299106109123105111106112108127121100133111961051351219710612210711710311110511911010711010410410212099103109111117109126138111121104106961041179010911711910710811310796109111124120941081051181211141101241091021069612310910210411295120115981301131029912696102111115941011121118810210810011311410112011610310311597109100102102104113119108118961099887103721011188811211310990103106868610210810599959611310384116110928572116979598103999410011494979210993102103888410480818980979010777979011492106971059189971161119778839575889895798410486921068594969697979295829188879687931039176881031067670891049985851088283891018890839182100779095878587908991878386938583102819392868586829381818770266 399100200300400500600700800900>1000Coverage value1002001k2k10k20k100k200k1M2M10M20M# 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.

00134 0510107 457297 6091 820 0111 086 7743 078 6454 738 4126 721 7886 205 34012 546 47813 448 21527 847 28716 521 3445 562 3565 937 8353 993 1353 456 1364 119 8085 957 1478 143 0827 149 2556 770 0105 952 47010 554 22021 349 54918 586 31727 517 11336 781 84046 295 89339 038 44886 518 45165 919 382210 228 943220 283 46091 312 23811 296 7870000510152025303540Phred quality score0M20M40M60M80M100M120M140M160M180M200M220M# 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 %6 842 63999.6 %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 %6 820 24899.3 %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%).

0.3 %22 3910.3 %99.7 %

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 %3 434 69350 %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.

98.2 %6 747 25298.2 %1.8 %

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.

21 %1 440 38421 %79 %

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.

184 6984 1451 5669 1952 0822 8304 46913 4363 05214 1281 3561 6073 0023 50784112 1771 1711 2172 8473 7841 1509 0162 0171 4709 28619 42546065 7917606772 6024 2058639 7145646672 3594 09234312 20480 9203 9733 3729 1349 26033 74125 80555 80987 98517 49212 2408 4449 3132 0823 0914 7245 54720 4155 89511 0546 060 29434135413211 193301020304050607080Phred quality score0.5M1M1.5M2M2.5M3M3.5M4M4.5M5M5.5M6M# 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.

99.66%99.65%99.69%99.71%99.66%99.66%99.68%99.66%99.67%99.69%99.45%99.63%99.72%99.72%99.7%99.64%99.69%99.65%99.62%99.75%99.7%99.65%99.57%99.81%0.34%0.35%0.31%0.29%0.34%0.34%0.32%0.34%0.33%0.31%0.55%0.37%0.28%0.28%0.3%0.36%0.31%0.35%0.38%0.25%0.3%0.35%0.43%0.19%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped