European Genome-Phenome Archive

File Quality

File InformationEGAF00000138909

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.

79 839 658185 081 632308 831 762403 467 424435 761 578404 208 997330 887 583243 916 461165 040 270103 964 87161 975 76735 571 79320 120 59411 518 0146 893 1614 407 4063 051 9022 273 3761 783 3941 443 1661 191 596988 433817 390679 094568 075475 274401 749342 525293 648252 683221 016190 960166 453145 389127 887113 56099 77786 87077 68767 82059 71953 13347 76143 63739 09134 45831 09928 58925 98023 68521 59519 97318 71117 96916 55915 90514 98613 81913 19412 57611 60810 85310 3089 7849 0638 5847 9927 7227 6727 1877 1756 9876 5836 1225 9665 7495 4605 3485 0104 9644 8844 5824 5084 3694 1274 1773 9473 8833 8433 7613 6823 3473 3343 3623 3293 2423 0392 8782 9122 8052 7582 8322 4692 5152 4902 5662 5052 4992 5802 3772 3292 4252 3622 3242 2892 2132 0622 0411 8461 8781 8071 8281 7951 7381 6441 6561 6361 5471 6381 6381 5131 5061 5081 4371 4681 4541 4011 4441 3981 3061 3581 3511 4011 2411 1851 2231 2031 1531 1061 1451 1291 0501 0991 0259381 0061 0741 0131 0251 0071 0189229661 0321 0341 05691290690898090682387790591590886385183480076976678074381180382487383282180975069372772971476364474666666562464664267468366468070568274468071265261363967058663560956360056157058153654257455755455259858758055451953749352952956050455946948050346947449246148152248044448943246050045542647239445243943142445639643544646741244139837938539340844843539037641236540640143945544942840041635838437138738335737639839237938438839740233335938437136835433435939138539838535633935337334137137838637141138938139038836440541038434734531832633133530531130733733635932127535731034736132034030730133432530934129634732634730635730032130629628027129032831829529630429829128726232228428524128427723730522025925824528222521922626521626424523726724322325527926121223224424325921425823223524022625620421823122024826425123219622719820122826221319022819024519619519622819022122921119818819418921618318120918621620119922020721920020619422021120720719621920518820319618622521221219319616718718518218117621417221719718920518319316616918319418418318821118817520622416420919019220219220018519622921021720621620018619418717220118518716116817114514315617214315817016616517115216519412515616514617213514816216716015414815215014115316415717915016716616814316215316016215614615214915816814215415816214314114216913613616217214417017515915416415513513914815416114913314412915013312713512912514213613914015614213913214216115714815013513114215513614614011813613715313114114213215714414014312815812113113612514414013413514511512615215915012815813014615214114211012515313114113310213512116516812915612315315415912116013113913615714713419714613514514412413811814013114411111313012811414112711914113710913310715211112613894138116121125117123107136106941181391261131151261481361441421231231451271401231161131241301301321311121471061331319611713411312011713812913411212711211014011711710310510310911113910411710111710799100101102929811010510912511211211410011010611085110102791099393108931041089710393921089793979611511588999181102811121069911398105969310397901039987891067910393109106971039692921137695978687928371968486857587103100811061007972881038681746773798491878674817178749978697761517963667378708666586864747794706787776993687558707171795167647477677677727267778169485663555277658085677590767467728781557277726076907286739075677772646160676672767476667272648068756264556182 390100200300400500600700800900>1000Coverage value1001k10k100k1M10M100M# 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.

1 671 1231 039 2342 812 47617 509 31734 744 92812 912 721113 222 834197 908 91463 582 75211 156 08114 846 66586 979 60296 939 188138 931 56881 455 38873 479 12621 753 91137 591 81715 804 72829 733 68717 941 05416 411 72168 837 93479 414 344166 044 87096 329 642127 415 065167 220 628181 592 290183 004 927146 378 758250 595 968236 026 080429 293 511570 770 993841 612 8091 370 475 4893 679 339 9915 913 495 5633 147 113 888537 614 65997 323 21329 615 6249 241 91900510152025303540Phred quality score0G0.5G1G1.5G2G2.5G3G3.5G4G4.5G5G5.5G# 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).

87 %168 918 07887 %13 %

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.

86 %167 045 95686 %14 %

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%).

1.1 %1 872 1221.1 %98.9 %

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 %97 085 93550 %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.

85.4 %165 766 44885.4 %14.6 %

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.

2.1 %4 152 0372.1 %97.9 %

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.

30 261 71446 44925 33282 08023 60541 78928 98643 35433 924291 929132 41091 039243 86061 61759 636531 68269 888497 239151 72744 663244 76115 417129 246619 8029 076138 7838 6238 4098 7788 302 70912 1528 7789 61412 2509 75213 922375 6503 386 44129 17817 10044 52638 56018 47473 28427 32234 652214 38247 53251 45057 49691 81639 460109 18681 530117 316181 590363 012146 456 918051015202530354045505560Phred quality score20M40M60M80M100M120M140M# 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.

100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped