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| | == Mapping Qualities == | | == Mapping Qualities == |
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| − | We should evaluate mapping qualities by counting how many reads are assigned each mapping quality (or greater) and among those how many map correctly or incorrectly. This gives a Heng Li graph, where one plots number of correctly mapped reads vs. number of mismapped reads. | + | We should evaluate mapping qualities by counting how many reads are assigned each mapping quality (or greater) and among those how many map correctly or incorrectly. This gives a Heng Li graph, where one plots number of correctly mapped reads vs. number of mismapped reads. |
| − | | |
| − | == Available Test Datasets ==
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| − | | |
| − | *Location: wonderland:~zhanxw/BigSimulation
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| − | *Scenarios:
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| − | | |
| − | no polymorphism ; 1, 2, 3 SNP ; Deletion 5, 30, 200; Insertion 5, 30
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| − | | |
| − | *Quality String
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| − | | |
| − | Picked the 75 percentile of Sanger Iluumina 108 mer test data set
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| − | BCCCCBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBAAAAAAAAAA@@@@@@@@@@@@@@@???????????>>>>>>>>>>>>=========<<<<<<<<<<;;";
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| − | | |
| − | | |
| − | *Format
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| − | | |
| − | Both base space and color space
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| − | | |
| − | Both single end and paired end, and paired end reads are given insert size 1500.
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| − | | |
| − | Forward strand and reverse strand are randomly assign with probability 1/2
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| − | | |
| − | * Tag
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| − | | |
| − | @2:12345:F:SE:Exact
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| − | | |
| − | @2:12345:F:SE:SNP:2,12345,A,G;2,12346,T,C
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| − | | |
| − | @2:12345:F:PE+offset:SNP:2,12345,A,G (ref is A, read is G)
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| − | | |
| − | @2:12345:F:PE+offset:Indel:25M30D5M
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| − | | |
| − | * File Naming
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| − | | |
| − | BS_SE_EXACT_1M_50
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| − | | |
| − | BS_SE_SNP1_1M_50
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| − | | |
| − | CS_SE_INDEL1_1M
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| − | | |
| − | CS_SE_INDEL30_1M
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| − | | |
| − | CS_SE_INDEL200_1M
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| − | | |
| − | CS_SE_DEL1_1M
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| − | | |
| − | For PE, appending "_1" and "_2", e.g.:
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| − | | |
| − | PE_EXACT_1M_1
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| − | | |
| − | PE_EXACT_1M_2
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| − | | |
| − | *Program (generator)
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| − | | |
| − | Usage:
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| − | | |
| − | generator [bs|cs] [se|pe] [exact|snpXX|indelXX|delXX] -n numbers -l readLength -i insertSize
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| − | exact: Accurate sample from reference genome
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| − | snpXX: Bring total XXX SNP for a single read or a pair of reads
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| − | indelXX: Insert a random XX-length piece for a single read, or at the same position for a paired reads
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| − | delXX: Delete a random XX-length piece for a single read, or at the same position for a paired reads
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| − | e.g. ./generator bs se exact -n 100 -l 35
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| − | | |
| − | *Output
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| − | | |
| − | Simulation file are named like: BS_SE_EXACT_1000000_35, meaning base space, single end, exact (no polymorphism), 1M reads, 35 bp per read. For each read, the tag was named in a similar way to Sanger's.
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| − | | |
| − | * Example
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| − | | |
| − | For illumina (from Sanger, 108mer hap1 test file):
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| − | | |
| − | Example:
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| − | <pre>
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| − | _1 file:
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| − | @20:14812275:F:217;None;None/1
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| − | AGTTGTTTACTTTCCTTTCCTACCTGGCTGCATCTGTCACATGCATATAGTGTCCCCTGACATGAAGCTCTGATATTGATCTGGAGCCCTATTGGTCTGCAAGTGACT
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| − | +
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| − | %27::2:::<70<<::95<<6/8<.)3;::9-,3:6/67731/.+)66;;53'31;9<815.%%%+%4-%%%90-)./26<831))(.%%%%%%%)%0%2%%%%%+%%
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| − | | |
| − | @15:59364621:R:-118;None;None/1
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| − | TGTTCAACCCACTATTAAGCCAGTATTAAATTGTTAATATCAGTTATTATACTTTTATTTCTAAAATTTCTATTTGATCCCTTTTTTTATAAACTCCAATGCATTCTC
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| − | +
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| − | %%2=;28>>>>=><>>>>>=>>=>>>;>=>9<1%+,//0+)<<91<4=;;<.%)2::8;;/9<;;;;8647<<;8;;066:<:4628;;;;5:9<<0/25752:3482
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| − | | |
| − | _2 file:
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| − | @20:14812275:F:217;None;None/2
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| − | CACTGGAGGGAATCCAATCCCAAATTAATATAACAAAACCAGAAGCTTGCTTAAAAAATATTTTATCAGATTCCAAAGTTGAGCTTGTGTTAGGGTGTACTGGAACTC
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| − | +
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| − | %%0;+250::-863486::599<9679/2%%))%+80%--7<;9/1%33,-%%)28/),3,67-8;56<1%)0/%%8;<;59/%%,())%%1%%+%).%099'4;+%-
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| − | | |
| − | @15:59364621:R:-118;None;None/2
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| − | AGAAATAAGACCACATGACAATGTTAAAAATAAAACAGGCAATAGCAATAGTCCCAGAGGTGGTTACAATATGATTTCATGCTCCAGAAAGTATAGGAGAAGACAAAG
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| − | +
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| − | %3===;==;7<<;7<5;==<<4<;9=8==<====:<<<<<;<==:=<58;===;:8'8:<===:.9:38908:=;;7;57)%.+%)967%%-%%'6:-%)7);<;0+%
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| − | </pre>
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| − | | |
| − | Conclusion:
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| − | | |
| − | If the first read is forward, then itself is the same as reference sequence and the second read is reverse complement to the reference sequence.
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| − | | |
| − | If the first read is backward, then itself is reverse complement to the reference genome and the second read is the same as the reference sequence.
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| − | | |
| − | The first strand always position can always obtain from tag, first two fields (seperated by colon).
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| − | | |
| − | The second strand position is first strand position plus the offset.
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| − | | |
| − | For SOLiD (from Sanger, 50 mer hap1 test file)
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| − | e.g.
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| − | | |
| − | <pre>
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| − | _1 file:
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| − | >2:67043752:F:1445;2,67043761,A,G;None
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| − | T12221203021201200302123102221322000012301300211213
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| − | 22212031230012003021211022213220000123013022112123 (ref)
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| − | >4:125830377:R:-1541;None;None
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| − | T30002222300330113020203010322111010300030003230320
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| − | | |
| − | _2 file:
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| − | >2:67043752:F:1445;2,67043761,A,G;None
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| − | G13031223023023012201210020003310110111111203310211
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| − | 30312230230230122012100200033121201111113033112112 (ref)
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| − |
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| − | >4:125830377:R:-1541;None;None
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| − | G13311131230200010201210032223330120312000301230032
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| − | | |
| − | </pre>
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| − | | |
| − | Conclusion:
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| − | The first strand and second strand have the same direction (both either same as the reference genome, or reverse complement to reference genome),
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| − | where their positions are the same as Illumina reads.
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| − | | |
| − | <br>
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| − | | |
| − | = Bulk statistics result =
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| − | Running time (all submitted to the MOSIX client nodes)
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| − | <br>
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| − | Calculated by "./parseRunbatch.py batch2.log |cutrange 0,-1|charrange :-1".
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| − | | |
| − | Log file is from runbatch.pl and negative time means unfinished (at the moment of editing).
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| − | | |
| − | TODO: Add file size comparison; add link to memory page summarized by Dharknes.
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| − | <pre>
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| − | BWA(second) Karma(second) Scenarios
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| − | 7561 4638 BS_PE_DEL200_1000000_50_?.fastq
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| − | 7548 4677 BS_PE_DEL30_1000000_50_?.fastq
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| − | 7225 4730 BS_PE_DEL5_1000000_50_?.fastq
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| − | 975 6531 BS_PE_EXACT_1000000_50_?.fastq
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| − | 1726 793 BS_PE_INDEL30_1000000_50_?.fastq
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| − | 6199 4140 BS_PE_INDEL5_1000000_50_?.fastq
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| − | 1193 4949 BS_PE_SNP1_1000000_50_?.fastq
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| − | 1646 4513 BS_PE_SNP2_1000000_50_?.fastq
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| − | 2064 4089 BS_PE_SNP3_1000000_50_?.fastq
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| − | 2594 3707 BS_SE_DEL200_1000000_50.fastq
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| − | 2641 3942 BS_SE_DEL30_1000000_50.fastq
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| − | 2355 4263 BS_SE_DEL5_1000000_50.fastq
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| − | 441 4228 BS_SE_EXACT_1000000_50.fastq
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| − | 809 764 BS_SE_INDEL30_1000000_50.fastq
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| − | 2217 3932 BS_SE_INDEL5_1000000_50.fastq
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| − | 645 3808 BS_SE_SNP1_1000000_50.fastq
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| − | 1102 3473 BS_SE_SNP2_1000000_50.fastq
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| − | 1142 3267 BS_SE_SNP3_1000000_50.fastq
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| − | 6193 6909 CS_PE_DEL200_1000000_50_?.fastq
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| − | 6173 6636 CS_PE_DEL30_1000000_50_?.fastq
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| − | 6096 6702 CS_PE_DEL5_1000000_50_?.fastq
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| − | 858 8496 CS_PE_EXACT_1000000_50_?.fastq
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| − | 1743 948 CS_PE_INDEL30_1000000_50_?.fastq
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| − | 5517 5412 CS_PE_INDEL5_1000000_50_?.fastq
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| − | 1253 8454 CS_PE_SNP1_1000000_50_?.fastq
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| − | 2113 7420 CS_PE_SNP2_1000000_50_?.fastq
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| − | 2622 6076 CS_PE_SNP3_1000000_50_?.fastq
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| − | 3878 1493 CS_SE_DEL200_1000000_50.fastq
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| − | 3859 1513 CS_SE_DEL30_1000000_50.fastq
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| − | 3775 1542 CS_SE_DEL5_1000000_50.fastq
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| − | 621 1666 CS_SE_EXACT_1000000_50.fastq
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| − | 1392 289 CS_SE_INDEL30_1000000_50.fastq
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| − | 3525 1390 CS_SE_INDEL5_1000000_50.fastq
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| − | 874 1661 CS_SE_SNP1_1000000_50.fastq
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| − | 1965 1449 CS_SE_SNP2_1000000_50.fastq
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| − | 3314 1237 CS_SE_SNP3_1000000_50.fastq
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| − | </pre>
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When evaluating read mappers, we should always focus on well defined sets of reads:
SNPs and errors are different because SNPs can lead to mismatches in high-quality bases. In addition to integrating according to the metrics above, we could separate results by the number of errors in each read.
We should evaluate mapping qualities by counting how many reads are assigned each mapping quality (or greater) and among those how many map correctly or incorrectly. This gives a Heng Li graph, where one plots number of correctly mapped reads vs. number of mismapped reads.
