European Genome-Phenome Archive

File Quality

File InformationEGAF00001752882

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.

8 840 2601 114 057177 410181 74660 62087 59231 08752 42224 04533 85417 31423 15713 52119 10212 23913 3029 44811 7205 2298 1775 0498 5697 5286 2185 0836 3277 6984 5703 1514 9853 8473 2733 1263 4193 0885 1823 8224 0543 6203 0992 5092 4562 2891 4841 4412 7852 0392 3851 5613 0381 8142 0462 1081 2821 3411 2591 9291 3271 3181 1551 3971 2246967879051 7009187478666395491 0105415871 0779985428038511 1131 0256281 0106145691 057417610610322605359661572596388451563622694403553505466206558191209298401435670130221427495530484487186224429127646510482292786198527383169177556434279427200286179238586141173337332583219664249296189137205352138280411253161101198212275306165288152206853549226311010713692323807017611910411432914219127214211653601263592817129687134254577914066484246329136199100776424131120126018563407163221507260352672495624332271953779406557917332518627593765523724917222957933260549546533812947412611653401887567615126266125104566185773687079911962374266124392471387273227146399172152535041242175245342315131236463320236445868245278465033464834553139212379533615562075222261920301381314332835262530184430246311354024912012529202890218323234227545371235332121272149131733421231719182140181816339451732812915812481912612188335916251646283124117131152581215715911913111381211641615531716161627162628292252101314141778161810111413131510311414111954071122873719221091238363740144116652019391259151433323365667663134478328534561311524121250397724037102618352631581417610913613512537713215361195373691081286738202835141210121411214181914203413781213139191252826715510331151378263619302217420161012763223605328562357272296255247344753563081253466657442819548217139637156655642793936862362980292421155216346260727336171328126571178323420954471081139106551014148771014914152525191812845989953543125746533538285763156412415459183363445854457323694934116312401015553961361291141089625102012111239171368831046231137152351416201171091517183202852893884104542781612246574764783779612193961281241721176857981213921545446114131818121319231623161613171091615226182170209516137112322350371222515112546153153829253171045928722 416100200300400500600700800900>1000Coverage value1101001k10k100k1M# 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.

000000015 2711 065 58711 897 2908 697 1045 082 97368 56582 1001 536 5472 293 1011 208 0042 828 4962 081 427875 2291 925 9611 421 9872 947 5642 629 1562 773 5973 646 9941 524 7813 639 4061 590 6031 908 8541 872 7012 792 2611 483 9941 289 21214 912 2154 875 6217 408 13620 592 643104 904 8200000510152025303540Phred quality score0M10M20M30M40M50M60M70M80M90M100M# 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).

99.9 %738 71899.9 %0.1 %

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.

99.8 %738 40899.8 %0.2 %

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 %3100 %100 %

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 %369 78750 %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.

72.7 %537 46872.7 %27.3 %

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.

76.2 %563 61076.2 %23.8 %

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.

974 62823 44517 56646 68520 94221 87373 95914 7448 88914 6267 6029 34427 27314 1749 90015 98811 43911 14817 41213 04610 65615 78611 41610 59517 27311 65010 51620 38710 0969 71116 7029 2769 48512 7828 5249 44837 6758 2327 33112 3157 4226 77111 9176 5137 7077 4386 4246 33018 9567 0066 7705 4345 4825 65815 7806 6744 9815 4634 9575 534348 570051015202530354045505560Phred quality score100k200k300k400k500k600k700k800k900k# 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.

99.99%99.98%99.98%99.98%99.97%99.99%99.99%99.97%99.99%99.99%99.99%99.98%99.99%99.99%99.99%99.99%99.98%99.99%99.99%99.97%100%99.98%99.97%100%0.01%0.02%0.02%0.02%0.03%0.01%0.01%0.03%0.01%0.01%0.01%0.02%0.01%0.01%0.01%0.01%0.02%0.01%0.01%0.03%0%0.02%0.03%0%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped