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Cancer Analysis Service User Guide - Support

1. iScan iSelect ForenSeq MiSeq MiSeqDx MiSeq FGx NeoPrep Nextera NextBio NextSeq Powered by Illumina SeqMonitor SureMDA TruGenome TruSeq TruSight Understand Your Genome UYG VeraCode verifi VeriSeq the pumpkin orange color and the streaming bases design are trademarks of Illumina Inc and or its affiliate s in the U S and or other countries All other names logos and other trademarks are the property of their respective owners Read Before Using this Product This Product and its use and disposition is subject to the following terms and conditions If Purchaser does not agree to these terms and conditions then Purchaser is not authorized by Ilumina to use this Product and Purchaser must not use this Product 1 Definitions Application Specific IP means Ilumina owned or controlled intellectual property rights that pertain to this Product and use thereof only with regard to specific field s or specific application s Application Specific IP excludes all Ilumina owned or controlled intellectual property that cover aspects or features of this Product or use thereof that are common to this Product in all possible applications and all possible fields of use the Core IP Application Specific IP and Core IP are separate non overlapping subsets of all Ilumina owned or controlled intellectual property By way of non limiting example Ilumina intellectual property rights for specific diagnostic methods for specific forensic m
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3. El Sample Barcode SummaryReport csv Summary report in csv format El Sample Barcode SummaryReport pdf Summary report in pdf format Genotyping 3 Sample_Barcode _idats Folder containing genotyping intensity data files for the sample idat files and genotyping sample sheet El Sample Barcode Genotyping vcf gz Genotyping SNPs mapped to reference in vcf format El Sample Barcode GenotypingReport txt Genotyping SNPs tab delimited report Variations El Sample Barcode CNV vcf gz Copy number calls 10 kb in vcf format El Sample Barcode Indels vcf gz Small Insertion Deletion calls in vcf format El Sample Barcode SNPs vcf gz Single nucleotide polymorphism SNVs calls in vcf format E Sample Barcode SV vcf gz Large Structural Variation calls 51 bp 10 kb in vcf format El Sample Barcode genome vcf gz Genome vcf file containing SNVs indels and reference covered regions El Sample Barcode vcf gz vcf file containing basic annotations and SNV and indel calls md5sum txt checksum file for confirming file consistency Cancer Analysis Services User Guide 6 eJnjonuJ1g JOp 04 US Analysis Deliverables NormalSample Barcode Assembly Sample Barcode bam Archival z bam file for sample El Sample Barcode bam bai Index for bam file Sample Barcode SummaryReport csv Summary report in csv format El Sample Barcode SummaryR
4. GATAACAGTAACAGACTTCYGL AAC AGA TACT I GATCOAG GAT GAACGIAGOG TRAO GANGO IAI CAAT I GAGAG AAATAT AAC IACCALAAGAGGTACGGTCLICTGHIAAGG TANGATTACT TGATCUACT GAT IGAAC ACCA MSS TAC PV AACCTTAAGATTACTTGATCCACT el AACGAACGTATCAAT TGAGACTAAATAT TAACGTACCAT TAAGAGCTACCGTGCAACGACGAACT TCTGT T CET AAGAT TACTTGA GCTACCGTGCAACGAAAATAACC lTAAGATTACT TGATCCACTGAT TCAACGTACTTCTGTTAACCTTAAGATTACTTGATCCACTGAT TCAACGTACCG TAACGAACGTATCAATTGAGAC TAAGCTACCGTGCAACGACGAAAAGAATGA EE TAACCLIAAGAT IAG LIGATCCACT GATT CAACTACCGTAMAGATIAG LIGATCCAGTGATICAASGTACCGIAACGAACGTALCAAITCAGAG TAAATAT TAACGTACCAT TAAGAGCTAC Dee E EE EE TEC Ce A ATT ACTA AC NAME GATA TAM ANA Ca ACCAT IAAGAGC TACCGTGCAACAGTAACACACT TCTGT TAACCTTAAGAT TACT TGATCCACTGAT TCAACGTACCG TAACGAACGTAT CAAT TGAGAC TAAATAT TAACGTACCAT TAAGAGCTACCGT GCAACGACGAAAAGAAT GAT GATAACAGTAACACACT TCTGTTAACCTTAAGAT TACTTGATCCACTGATTCAACGTACCG TAACGAACGTAT CAATTGAGACT AAATATIAACGTACCATIAAGAGCIACCOTCHOTOTT AACCTTAAGA TAC TT RAT CO ACT CAT CARC ARR ER lee AT A NG CRT GET RP CP RAR AT OPERA CAT AA TIC ARE CT Ee CGTTAAGA Ee CGTAACGAACGTATCAATTGAGCTICTGTTAACCT TAAGAT TACT TGATCCACT GAT TCAACGTACCGTAACGAACGTATCAAT TGAGAC TAGCAACGACC GAAAAGAATGATAACAG TAACACAC TL TCTGT TAACCT TAAGAT TACTT GA TOGA CT GATT CAACGTACCGTAAAGATTACT TGATCCACTGAT TCAACGTACCGTAACGAACGTATCAAT TGAGAC TAAATAT TAACG TACCAT TAAGAGCTAC M og CA RPA LAE SR aT eA AS ATTER E E IN gt GTACCGT CARRE e GATTCAACGTACCGTAACGAACGTA TAL A CTAAATAT TAACGTACCAT TAAGAGC TA eT E D
5. Inc and its affiliates Illumina and are intended solely for the contractual use of its customer in connection with the use of the product s described herein and for no other purpose This document and its contents shall not be used or distributed for any other purpose and or otherwise communicated disclosed or reproduced in any way whatsoever without the prior written consent of Illumina Illumina does not convey any license under its patent trademark copyright or common law rights nor similar rights of any third parties by this document The instructions in this document must be strictly and explicitly followed by qualified and properly trained personnel in order to ensure the proper and safe use of the product s described herein All of the contents of this document must be fully read and understood prior to using such product s FAILURE TO COMPLETELY READ AND EXPLICITLY FOLLOW ALL OF THE INSTRUCTIONS CONTAINED HEREIN MAY RESULT IN DAMAGE TO THE PRODUCT S INJURY TO PERSONS INCLUDING TO USERS OR OTHERS AND DAMAGE TO OTHER PROPERTY ILLUMINA DOES NOT ASSUME ANY LIABILITY ARISING OUT OF THE IMPROPER USE OF THE PRODUCT S DESCRIBED HEREIN INCLUDING PARTS THEREOF OR SOFTWARE 2015 Illumina Inc All rights reserved Illumina 24sure BaseSpace BeadArray BlueFish BlueFuse BlueGnome cBot CSPro CytoChip DesignStudio Epicentre GAIIx Genetic Energy Genome Analyzer GenomeStudio GoldenGate HiScan HiSeq HiSeq X Infinium
6. 14x in the reference sequence Average fraction of filtered base calls within 50 bases of the indel is gt 0 3 Normal sample is not homozygous with the reference or the indel quality score somatic indel is lt 30 ie calls with NT ref or OSI NT lt 30 Cancer CancerSampleBarcode _Normal NormalSampleBarcode somaticSVs vcf gz The somatic SV file contains structural variants from 50 bp to 10 kb from the large indel and Isaac Structural Variant Caller called within the sample in VCF 4 1 format The VCF file contains the following fields 11 Table 7 INFO Fields ID BND DEPTH BND PAIR COUNT CIEND CIGAR CIPOS Description Read depth at local translocation break end Confidently mapped reads supporting this variant at this break end it is possible that mapping is not confident at remote break end CIGAR alignment for each alternate indel allele Number of samples with data Confidence interval around POS Part 15040893 Rev C ID DOWNSTREAM_AIR_ COUNT END HOMLEN HOMSEQ IMPRECISE MATE_BND_EPTH MATEID PAIR_COUNT SOMATIC SOMATICSCORE SVINSLEN SVINSSEQ SVLEN SVTYPE UPSTREAM_PAIR_ COUNT Table 8 FORMAT Fields ID PR SR Table 9 ALT Fields Description Confidently mapped reads supporting this variant at this downstream break end it is possible that mapping is not confident at upstream break end End position of the variant described in this record Length of base
7. AAR RANT GT VEA DACIA TRE RT ARE AAAAGAATGAT AACACACTTCTGTTAACCT TAAGAT TACTTGATCCACTGATTCAACGTACCGTAAAGAT TACT TGATCCACTGAT TCAACGTACCG TAACGAACGTATCAATTGAG TTAACGTACCAT TAAGAGCTAC ACA TANGAGCYACGOTACAACAGTAACACACTICTGTTAACUTTARQA TTIACTIGATCCACTGATTCAACGTAGCOTAACCAACG TAT CAATIGAGAGTABATATTAACGTACCAMAAGAGGTACCCTACAACCACGAAAR SANT GATA GATAACAG TAACACA ele EE ee CTAAATAT TAACGTACCAT TAAGAGC TACCGTCTTCTGTTAACCTTAAGAT TACTTGATCCACT GATTCAAC CTTGATCCACTGAT TCAACGTTAAGATTACTTGATCCACTGATTCAACG TACCGTAACGAACGTATCAAT TGAGCT TCT GT TAACCT TAAGATTACTTGATCCACTGATTCAACGTACCGT Fe oo oye eer cope goes CAATTGAGACT KE UE CTGTTAACCTTAAGA TANG HGATCCAGTOATICHACGIACCETAACGAACCIATCAATIGAGA CTAAATATTAACGTACCATTAAGAGCTACCGTGCAACGAAAAGAATGATAACAGT MAU aR ETRE Co TA CATA ALTA ee ERAT AT RAN TELE RM e ESTA GA TT NT VAS AAT ABA e DAC SCT OP CI NARA VACA E CTTGATCCACTGATTCAACGTIAAGA DAMM UE SUE CCGIAACGAACGTATCAATTGAGCTTCTGTTAACCT TAAGATTACT TGATCCACTGATTCAACGTACCGTAACGAACGTATCAAT T GAGAC TAGCAACGACC GAAAAGAATGATAACAGTAACACAC T TCTGT TAACCT TAAGATTACTTGATOCCACTGATTCAACGTACCGTAAAGATTACT TGATCCACTGAT TCAACGTACCGTAACGAACGTAT CAAT TGAGAC TAAATAT TAACGTACCAT TAAGAGCTAC GATAACAGTAACACACTTCTGTTAACCTTAAGATTACTTGT TGATCCACTGAT TCAACGTACCG TATCAAT TGAGAC TAAATAT TAACGTACCAT TAAGAGC TACCGTCTTCTGTTAACC T TAAGAT TACTIGATCCACTGATTCAACGTACCGI CACTGATTCAACGT YQ US ME Er CGTATCAATTGAGAC TAAATAT TAACGTACCAT TAAGAGCTACCGTCT TC TGT TAACCT TAAGAT TACT T GATCCAC TGAT TCAACGTACCGTAACG GAAAAGAATGATA
8. Service pipeline Renamed Strelka and Manta to Isaac Somatic Variant Caller and Isaac Structural Variant Caller respectively Revised documentation to reflect changes in version 3 of the Illumina FastTrack WGS pipeline Initial release Table of Contents Revision History 1 00 2 e V Table of Contents 2222 vi Chapter 1 Getting Started ooo ooooceccceeeeeeeeeeeec cece cc ccccccccceeeeeeees 1 Cancer Analysis Service 22 2 Data Delivery 3 Chapter 2 Analysis Deliverables 4 Analysis Folder Structure Overview 5 Result Folder Structure 6 SomaticVariations 9 Summary Report 2 2 0 00 eee 14 Data Integrity isi tili momie une gere nie eee 17 Chapter 3 Analysis Cverview 18 Analysis Overview Introduction 22 eee 19 Isaac Somatic Variant Caller 20 Isaac Structural Variant Caller 24 Copy Number Aberrations GENECA e cece eee cece 2 26 Appendix A Appendix odada aain n inor n nonn a nrnna 28 Illumina FastTrack Services Annotation Pipeline 29 Technical Assistance cio ese we ee ete tees 30 Cancer Analysis Services User Guide Getting Started Cancer Analysis Service EE 2 Data Delivery Eege do Sed REENEN AE SNE 3 3 a uM aa a Mio ART Cancer Analysis Services User Guide LJe1deuo Getting Started Cancer Analysis Service The Cancer Analysis Service Informatics Pipeline leverages a suite
9. as used to classify somatic variants One of ref het hom or conflict Somatic indel possibly overlaps a second indel Quality score reflecting the joint probability of a somatic variant and NT Data tier used to compute QSI_NT Most likely somatic genotype excluding normal noise states Somatic Mutation flag The type of structural variant Smallest repeating sequence unit in inserted or deleted sequence Number of times RU repeats in the reference allele Number of times RU repeats in the indel allele Largest reference interrupted homopolymer length intersecting with the indel Description 10 SUOI ELIEADITEWOS Analysis Deliverables ID DP2 TAR TIR TOR DP50 FDP50 SUBDP50 Table 6 FILTER Fields ID DP Repeat iHpol BCNoise OSI ref Description Read depth for tier 2 Reads strongly supporting alternate allele for tiers 1 and 2 Reads strongly supporting indel allele for tiers 1 and 2 Other reads for tiers 1 and 2 weak support or insufficient indel breakpoint overlap Average tier 1 read depth within 50 bases Average tier 1 number of base calls filtered from original read depth within 50 bases Average number of reads below tier 1 mapping quality threshold aligned across sites within 50 bases Description Greater than 3x chromosomal mean depth in the normal sample Sequence repeats more than 8x in the reference sequence Indel overlaps an interrupted homopolymer longer than
10. gain LOH to identify loss of heterozygosity events Ploidy and purity associated with the model having highest log likelihood are then used to assign a copy number state to each segment When both segments and copy numbers are estimated a quality score for copy number assignment is computed using a likelihood ratio test This test compares the likelihood of a current copy number assignment to a likelihood of assigning 1 more or 1 less copy Results of the likelihood ratio test are then reported as a Q score field in the VCF file using the following transformation 2 log s1 s2 where s1 is a sum of squares for selected model and s2 is a sum of squares for the next nearest model Q score threshold of 1 5 provides a good trade off between sensitivity and specificity CNA Output SENECA produces a genome wide plot a per chromosome plot and a VCF file Cancer Analysis Services User Guide 2 6 VO3N3S suoneueqy sequny Adoo The genome wide plot shows distribution of copy number and B allele ratios copy number ratios are classified as either gains red or losses green Estimated purity and ploidy values are listed at the top of the plot Per chromosome plots list the distribution of either B allele or copy number ratios Plots also report identified segments as black lines using a second Y axis of copy number states which range from 0 to a maximum of 9 copies Capped segments are indicated in red Segments exhibiting LOH are indicated in gr
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12. pair identical microhomology at event breakpoints Sequence of base pair identical microhomology at event breakpoints Imprecise structural variation Read depth at remote translocation mate break end String ID of mate break end Read pairs supporting this variant where both reads are confidently mapped Somatic mutation Somatic variant quality score Integer length of microinsertion at event breakpoints Sequence of microinsertion at event breakpoints Difference in length between REF and ALT alleles Type of structural variant Confidently mapped reads supporting this variant at the upstream break end it is possible that mapping is not confident at downstream break end Description Spanning paired read support for the ref and alt alleles in the order listed Split reads for the ref and alt alleles in the order listed for reads where P allele read gt 0 999 ID Description BND Translocation break end COMPLEX Unknown Candidate Type DEL Deletion DUP TANDEM Tandem Duplication INS Insertion INV Inversion Cancer Analysis Services User Guide 12 SUOI LELIEADITEWOS Analysis Deliverables Table 10 FILTER Fields ID Description MaxDepth Indicates that the normal sample site depth is greater than 3 0x of the mean chromosome depth MaxMQOFrac For a small variant lt 1000 bases in the normal sample the fraction of reads with MAPQO around either break end exceeds 0 4 MinSomaticScore Soma
13. positions where the normal sample is heterozygous Cancer Analysis Services User Guide 16 Analysis Deliverables Data Integrity 17 The md5sum txt file is provided as a means of checking the integrity of the sample files and folders Immediately after sample quality check the md5sums or compact digital fingerprint for every file in the directory tree are generated If media failures compromise data integrity you can use the md5sum tool to find the inconsistencies Use the tool to compare the hash from the provided md5sum file to one generated from the downloaded file On a Unix system you can use the following commands to perform an md5sum check assuming the utility is installed cd Sample Barcode md5sum c md5sum txt The check verifies every file and require approximately 30 45 minutes to complete Any errors are listed in the output In Windows there are various command line and GUI tools available to perform an md5sum check The Cygwin tools provide a utility identical to Linux Part 15040893 Rev C Analysis Overview Analysis Overview Introduction 222222222222 19 Isaac Somatic Variant Caller 20 Isaac Structural Variant Caller 24 Copy Number Aberrations GENECA ee I ses ell llle pei 26 mi d Ce d AP e ging TES V PS A N Pda A E AN d s SM XS amp 3 NN q y Ts Le c saga if Erna a SE o es SEH ay LIT SE n SR SRE y REA TGCGG CA sprengen peser 4 a idea e Cancer
14. ACAG TAACACACTTCTGTTAACCTTAAGAT TACTT GATCCACTGATTCAACGTACCGTAAAGAT TACT TGATCCACTGAT TCAACGTACCGTAACGAACGTATCAAT T GAGAC TAAATAT TAACGTACCAT TAAGAGCTAC TRAE TAL Lee Ra ee RAT TACTA AS ET TAC TA TEA Ke UM GUEST TET TA etel GATA T VEA CRETE ALT RACE TTGAGACTAAATATTAACGTTGTTAACCTTAAGATTACTTGATCCACTGATTCAACGTACCG TAACGAACG TATCAATTGAGACTAAATATTAACGTACCAT TAAGAGCT TCTGT TAACCT TAAGAT TACTT GATCCACTGAT TCAACGTACCG T7 TATCAAT TGAGACTAAATAT TAACGTAC T TAACCT TAAGAT TACT TGATCCACTGATTCAACGTACCGTAACGAACGTCTTCTGT TAACCTTAAGAT TACT TGATCCACTGATT CAACGTACCGTAACGAACGTAT CAAT T GAGAC TAACGACG ARR A ACTA ST TA GR AEST TASA TT RM Te PORT EAT STA lana cece Gea TENTA TR TATE TRE TAC CAT AGIR ES CT RAA CG ACCRA RARES TR USA UNA GATAACAGTAACACACTTCTGTTAACC TTAAGATTACT TGATCCACTGAT TCAACG TACCG TAACGAACG TATCAAT TGAGACTAAATAT TAACG TACCAT TAAGAGCTACCGTCT TCTGT TAACCT TAA EE beret aa ACCATTAAGAGCTACCGTGCAACTTAACCTTAAGAT TACTTGATCCACTGATTCAACGTACCGTAACGAACGTATCAAT TGAGACTAAATATTAACGTACCAT TAAGAGCTACCGTGCAACGACGAACT T CTGT TAACCT TAAGAT TACTTGA GCTACCGTGCAACGAAAATAACC T TAAGATTACT TGATCCACTGAT TCAACGTACTTCTGTTAACCTTAAGATTACTTGATCCACTGAT TCAACGTACCGTAACGAACGTATCAATTGAGACTAAGCTACCGTGCAACGACGAAAAGAATGA GAAAAGAATGATAACAG TAACACAC T TCTGT TAACC T TAAGAT TA va D eM TA CCGTAAAGATTACTTGATCCACTGATTCAACGTACCGTAACGAACGTA UE GATAACAGTAACACACT TCTGTTAACCT TAAGAT TACTTGATCCACTGAT TCAACGTACCGTAACGAACGTATCAATT GAGACTAAATAT TAACGTACCAT TAAGAGCTACCGTGCAACGACGAAAAGAAT GATAACAGTAACACACT T CTGT ACCA TA
15. ACGTATCAATTGAGACTAAGCTACCGTGCAACGACGAAAAGAA GARAAGAATGATARCAGTAACACACTICIGT ARCO LTAAGAT TACT TGAT CAG GAT CAACGTADCG AAAGATIACT TGAICCAGTGAT CAAGGTACGG TAA COMAG IATGAAT GAGAG TAAATAT TAAGGIACGAI TAAGAGCTAG AAG ARRON CTTCTGTTAACCTTAAGA CR le RANGER ACCGTAACGAACGTATCAATTGAGACTAAATATTAACGTACCA ME ce CCGTGCAACGACGAAAAGAAT GATAACAGTAACA REH IACCAT IAAGAGC TACCGTGCAACAGTAACACACT T AAGATTACTTGATCCACTGAT TCAACGTA GE RA e CTAAATATTAACGTACCAT TAAGAGCTACCGT GCAACGACGAAAAGAAT GAT TGATAACAGTAACACACT TCTGTTAACCTTAAG ATIACTTGATCCAG LGAPTCANCGTA CCGTAACGAACGTAT CAAT TGAGACT RAATATIAACGTACCATAAGAGCIACCOTCTTOT GTIAACCTTAAGA FRAC I GATCCACTGATIGAAG POI C eg eI Ge AM a GAT TAC GM eMe LGBLTQA eel taal veneer yaa a E EE GE e AACGTTAAGATTACTTGATCCACTGATTCAACG TACCGTAACGAACG TATCAAT TGAGCTTCTGTTAACCT TAAGAT T P TCAATTGAGACTAGCAACGAC GAAAAGAATGATAACAGTAACACACTTCTGTTAACCT TAAGAT TACTTGAT SGA CTGATTCAACGTACCGTAAAGATTACTTGATCCACTGATTCAACGTACCGTAACGAACGTATCAATTGAGACTAAATATTAACGTACCATTAAGAGCTAC NE e CI RU UA AN PENCHE SIG Rae SORA AI PE D AE USE CARE EE RSR AE UE ei BANE A Sy Ns EE EEN ACCGTAACGAACGTA UE ee CTAAATAT TAACGTACCAT TAAGAGC TACCGT GCAACGACGAAAAGAA NS ya e CTT CTGTTAACCTI GAAAAGAATGAT AACACACTTCTGTTAACCT TAAGATTACTTGATCCACTGATTCAACGTA AAAGAT TACTTGATCCACTGATTCAACGTACCGTAACGAACGTATCAAT TGAG TTAACGTACCAT TAAGAGCTAC AGUA TAAGAGCIACOGT SCAACAGTAACACACT ICT AGG TAAGATTACT GATOGAG GA GAADG TACUGTARCGAACG AT CAAT TGAGAG AAATAT TAACG ACAI IAAGAGCTAGC I GCAACGAGGAAAA
16. Analysis Services User Guide 1 8 Jejdeuyo Analysis Overview Analysis Overview Introduction The somatic variant calling pipeline uses 2 aligned sequence files bam files as inputs a normal bam and a tumor bam In the tumor analysis pipeline these bam files are the result of the whole genome sequencing pipeline described in the Whole Genome Sequencing Services User Guide part 15040892 These bam files are then processed through 3 interconnected callers Isaac Somatic Variant Caller Isaac Structural Variant Caller Copy Number Aberration Caller SENECA Isaac Somatic Variant Caller and SENECA are described in the following sections For information on the Isaac Structural Variant Caller see Isaac Structural Variant Caller on page 24 During the first stage of the pipeline the tumor and normal bam files run through a combined indel realignment operation This realignment operation is used as the input for further processing During calling putative calls and de novo reassembled sections of sequence are passed between the callers to produce internally consistent variant calls All 3 callers use statistical models that operate on the combined tumor and normal reads as input instead of the variants The statistical models use combined calling instead of subtraction of variant calls Using combined calling produces superior results However subtraction of the calls from the normal and tumor whole genome results often do n
17. CCGTAACGAACG TCTTCTGT TAACCT TAAGAT TACTT GATCCACTGAT TCAACGTACCG TAACGAACG TATCAAT T GAGACTAACGACG AGACTAAATAT TAACGTACCAT TAAGAGCTACAACCT TAAGAT TACT TGATCCACTGATTCAACGTACCGTAACGAACGTAT CAAT TGAGACTAAATAT TAACG TACCAT TAAGAGC TACCGTGCAACGACGAAAAGAAT GATAACAGTAACAC Ies Ed AACA RO REC p UCM cM CGTACCGTAACGAACG TATCAAT TGAGACTAAATAT TAACG TACCAT TAAGAGC TACCGTCT TCTGT TAACCT TAAGAT TACT TGATCCACT GAT TCAAC IACCAT TAAGAGC TACCGTGCAACT TAACCT TAAGAT TACT TGATCCACTGAT TCAACGTACCGTAACGAACGTATCAAT I GAGACTAAATATTAACGTACCATTAAGAGCTACCGTGCAACGACGAACTICTGTIAACCTIAAGATIACTIGA TO E RA E TRATTATI CRETA ES ANR TAGS ect Ee GAAAAG GGAAAAGAATGATAACAGTAACACAC T TCTGT TAACCTTAAGAT TACTTGATCCACTGATTCAACGTACCG TAAAGATTACTTGATO TGATAACAGTAACACACT TCTGTTAACCT TAAGAT TACTTGATCCACTGAT TCAACGTACCGTAACGAACG TATCAAT TGAGACTA IACCAT TAAGAGCTACCGTGCAACAGTAACACACT T CTGT TAACCTTAAGAT TACTTGATCCACTGAT TCAACGTACCG TAACGA TGATAACAGTAACACACT TCTGTTAACCT IAAGAT TACTTGATCCACTGATTCAACGTA evi T RN pe ZGTACCGTAACGAACGTATCAT TAAGAT TACTTGATCCACTGATTCAACGTACCGTAACGAACG TATCAAT TGAGACTAAA t CT SAT CACICA CAACGITAAGATTACTTGAICCACTGATI CAACGTACCGIAACGAACGTATCAATTGAGCTTC TOT TAAG GAAAAGAATGATAACAGTAACACACT TCTGTTAACCTTAAGATTACTTGATCCACTGATTCAACGTACCGTAAAGAT TACTTGATG a O eg TCACAAGGTTTACCACAA iemcuerAoGTACAACA HTCMMGCGAAAGACAGGTTACCAT FOR RESEARCH USE ONLY ILLUMINA PROPRIETARY Part 15040893 Rev C June 2015 This document and its contents are proprietary to Illumina
18. GAAT GATA TGATAACAGTAACACACTTCTGTT papell AAGATTACTTGATCCACTGAT ICAACGTACCGT EA CGTATCAAT TGAGAC TAAATAT TAACGTACCAT TAAGAGC TACCGTCTTCTGTTAACCTTAAGATTACTTGATCCACTGATTCAAC CTTGATCCACTGATTCAACGTIAAGAT TACTTGATCCACT GATTCAACGTACCGTAACGAACGTATCAAT TGAGCT TCTGT TAACCT TAAGATTACT TGATCCACTGAT TCAACG TACCG T ARD DSL CU GA C A CAAT TGAGACTAAATATTAACGTACCAT TAAGAGTCTGTTAACCTTAAGA TRAC HIGATCCAGT GATT CANCE TACO TAA CGAACGTATCAATIGAGACT AAATATTAACGTACCATTAAGAGC TACCGTGCAACGAAAAGAATGATAACAGT Pe Ma EPA LETT M eMe ALTO M A TAER ONO TA ALTA tlw a al UM SAR E NA ACO GATO TO TAARET CTTGATCCACTGATTCAACGTTAAGATTACTTGATCCACTGATT CAACGTACCGTAACGAACGTAT CAATTGAGCTTICTGTTAACCTTAAGAT TACT TGATCCACTGAT TCAACGTACCGTAACGAACG TATCAAT TGAGACTAGCAACGAC GAAAAGAATGAT TGTTAACCTTAAG TT TACCGT CGTACC GAACGTA GAGACT CGTA GA CACTGAT ICAACGTACCAAGAT TACTIGATCCACTGAT TCAACGTACCGTAACGAACGTATCAAT TGAGAC TAAATAT TAACGTACCAT TAAGAGCTA QUEUE Ue IE SAEC AR Sept ACCGTAACG AAAAGAATGATAACAGTAACACACTTCTGTTAACCTTAAGATTACTTGATCCACTGATTCAACGTACCGTAAAGATTACTTGATCCACTGATTCAACGTACCGTAACGAACGTATCAATTGAGACTAAATAT TAACGTACCAT TAAGAGCTAC IGATAACAGTAACAGAGT ICIGI TAACCTTAAGATIAGT TGATOGACT GATT GAAGGTAGGGTAACGAACGTAT CAAT IGAGACTAAATAT AAC TAGCAT TAAGAGC IAGUGTCT TETA AACG TANGA IAG IGATCCAGTGATTGAAG TTGAGACTAAATAT TAACGTTGTTAACCTTAA E GATTCAACGTACCGTAACGAACGTATCAATT GAGACTAAATAT TAACGTACCAT TAAGAGCTTCTGT TAACCT TAAGAT TA Mee i TATCAAT TGAGACTAAATAT TAACGTACT TAACCT TAAGAT TACT TGATCCACTGATTCAACGTA
19. NGAGCTACCGTGCANCAGTAACAGACTI GTO TARGO TARA ACT RAT CAC IAA CA OGIA CSTM CGM CE TAC RAT CAB AC TARATAT TAA GTACCATTAAGAGU TACT GC AACCACGANANGAATOATAL GATAACAGTAACACACT TCTGTTAACCT TAAGAT T ee ME Mc Eer CTAAATATT d C e eee ee ILIA ao GTACCGTAACGAACGTATCATTAAGAT TACTTGATCCACTGATTCAACG GTAACGAACGTATCAA GACTAAATAT TAACGTACCATTAAGAGCTACCGTGCAACGACGAAAAGAATGATAACAG TAACACACT TCTGT TAACC T T OENE CACICA CAACGITAAGATTACTIGATGCACTGATI CAACGIACCCTAACGAACGTATCAATT CASC LICTOLIAAGC TAAGATTAC LIGATCCAGT GATT AAC CAC GE TAACGAACGTATCARTTOAGACTAGCAACGACE GAAAAGAATGATAACAGTAACACACT TCTGTTAACCT TAAGATTACTTGATCCACTGATTCAACGTACCGTAAAGAT TACT TGATCCACTGAT TCAACGTACCGTAACGAACGTAT CAAT TGAGACTAAATAT TAACGTACCAT TAAGAGCTAC E E Illumina 5200 Illumina Way San Diego California 92122 U S A 1 800 809 ILMN 4566 1 858 202 4566 outside North America techsupport illumina com www illumina com
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21. NVs are reported if the normal genotype is equal to the reference and Q ssnv ntype gt 15 Somatic indels are reported if the normal genotype is equal to the reference and Q somatic indel ntype 30 NOTE i The value Q ssnv ntype is associated with the VCF key QSS_NT The value Q somatic indel ntype is associated with the VCF key QSI_NT Part 15040893 Rev C 23 Isaac Structural Variant Caller Isaac Structural Variant SV Caller is a structural variant caller for short sequencing reads It can discover structural variants of any size and score these variants using both a diploid genotype model and a somatic model when separate tumor and normal samples are specified Structural variant discovery and scoring incorporate both paired read fragment spanning and split read evidence Method Overview Isaac SV Caller works by dividing the structural variant discovery process into 2 primary steps scanning the genome to find SV associated regions and analysis scoring and output of SVs found in such regions 1 Build SV association graph In this step the entire genome is scanned to discover evidence of possible SVs and large indels This evidence is enumerated into a graph with edges connecting all regions of the genome that have a possible SV association Edges can connect 2 different regions of the genome to represent evidence of a long range association or an edge can connect a region to itself to capture a local indel small
22. SV association These associations are more general than a specific SV hypothesis in that many SV candidates can be found on 1 edge although typically only 1 or 2 candidates are found per edge 2 Analyze graph edges to find SVs The second step is to analyze individual graph edges or groups of highly connected edges to discover and score SVs associated with the edges These substeps of this process include Inference of SV candidates associated with the edge Attempted assembly of the SVs break ends Scoring and filtration of the SV under various biological models currently diploid germline and somatic Output to VCF Capabilities Isaac SV Caller can detect all structural variant types that are identifiable in the absence of copy number analysis and large scale de novo assembly Detectable types are enumerated in this section For each structural variant and indel Isaac SV Caller attempts to align the break ends to base pair resolution and report the left shifted break end coordinate per the VCF 4 1 SV reporting guidelines Isaac SV Caller also reports any break end microhomology sequence and inserted sequence between the break ends Often the assembly fails to provide a confident explanation of the data In such cases the variant is reported as IMPRECISE and scored according to the paired end read evidence alone The sequencing reads provided as input to Isaac SV Caller are expected to be from a paired end sequencing assay that resul
23. a minimum fraction of supporting reads among the sample reads for candidacy For more information on the Isaac Variant Caller see the Whole Genome Sequencing Services User Guide part 15040892 Realignment For every read that intersects a candidate alignment the Isaac Somatic Variant Caller attempts to find the most probable alignments including the candidate indel and excluding the candidate indel Typically the alignment excluding the candidate indel aligns to the reference but occasionally an alternate indel that overlaps or interferes with the candidate is found to be more likely The indel caller uses the probabilities of both alignments as part of the indel quality score calculation whereas only a single alignment usually the most probable is preserved for SNV calling Somatic Caller 21 The Isaac Somatic Variant Caller uses a Bayesian probability model similar to the one used for germline variant calling in the Isaac Variant Caller or in external tools such as GATK Using this model our objective is to compute the posterior probability P 0 D which is the probability of the model state O conditioned on the observed sequencing data In a germline variant caller the state space of the model is conventionally a discrete set of diploid genotypes For SNVs the set of possible states is G AA CC GG TT AC AG AT CG CT GT The Isaac Somatic Variant Caller model instead approximates continuous allele frequencies for each alle
24. al somatic analysis deliverable Normal and paired tumor samples are batched together at delivery but each folder follows the same underlying format Though results from our Whole Genome Sequencing Service Pipeline are reported for tumor samples the algorithms used have been designed for and tested on diploid samples and not heterogenetic tumor samples The files and folders generated for the cancer normal somatic analysis results are all keyed off the unique sample identifiers for both the cancer CancerSampleBarcode and normal sample NormalSampleBarcode Usually these unique identifiers are the barcodes associated with the cancer and normal samples in the lab eg LP600001_DNA A01 but can be a known sample ID for reference samples eg HCC1187 Analysis Deliverables D Part 15040893 Rev C Result Folder Structure Under each paired tumor normal sample folder you can find the following file structure that contains analysis results Due to the quantity of DNA samples run using our Nano service will not have genotyping information For detailed information on assembly genotyping variations files and descriptions of the algorithms used to generate them see the Whole Genome Sequencing Services User Guide part 15040892 Cancer CancerSampleBarcode Normal NormalSampleBarcode CancerSample Barcodel Assembly El Sample Barcode bam Archival bam file for sample E Sample Barcode bam bai Index for bam file
25. ants VCF NOTE e For a detailed overview of Isaac Somatic Variant Caller methods go to www ncbi nlm nih gov pubmed 22581179 Candidate Indel Search The Isaac Somatic Variant Caller caller scans through the genome using sequence alignments from the normal sample and tumor sample together to find a joint set of candidate indels The information in sequence alignments is supplemented with externally generated candidate indels discovered by the Isaac Structural Variant SV Caller Isaac SV Caller provides external candidate indels to Isaac Somatic Variant Caller for indels of size 50 and below Cancer Analysis Services User Guide 2 O J9 29 JUBA oewos oees Analysis Overview Candidate indels are used for realignment of reads during which each candidate indel is evaluated as a potential somatic indel Any other types of indels are considered noise indels If a better alignment is not found these indels are allowed to remain in the read alignments otherwise they are not used The candidate indel thresholds are designed so that the joint candidate indel set is at least the combined set found if the Isaac Variant Caller is run on the individual samples Specifically where a minimum number of nominating reads is required for candidacy in Isaac Variant Caller Isaac Somatic Variant Caller requires the same minimum number of nominating reads from the combined input Isaac Somatic Variant Caller requires that at least one sample contains
26. ate Structural variants of less than 50 kb are passed to Isaac Somatic Variant Variant Caller Caller SENECA 2 2 2 Somatic copy number aberration CNA caller d NOTE The BAM files from the whole genome workflow are used as input Part 15040893 Rev C Data Delivery Ilumina FTS currently provides data delivery through the following choices Illumina Hard Drive Data Delivery Illumina FastTrack Services ships data on 1 or more hard drives The hard drives are formatted with the NTFS file system and can optionally be encrypted The data on the hard drive are organized in a folder structure with 1 top level folder per sample or analysis Illumina Cloud Data Delivery Illumina FastTrackServices uploads data to a cloud container Ilumina currently supports uploads to the Amazon S3 service Upload data are organized per upload batch by date under an Ilumina FTS prefix For example a sample in a batch uploaded on February 1 2014 would be found with the prefix Ilumina FTS 20140201 SAMPLE BARCODE in the container Contact your FastTrack Services project manager to enable cloud delivery Cancer Analysis Services User Guide 3 Aiguigac e1eq Analysis Deliverables Analysis Folder Structure Overview Result Folder Structure SomaticVariations Summary Report Data Integrity Cancer Analysis Services User Guide A c Je1deuo Analysis Folder Structure Overview This section details the files and folder structure for the cancer norm
27. cf format El Cancer CancerSampleBarcode Normal NormalSampleBarcode somaticIndel vcf gz Small Insertion Deletion somatic calls 1 bp 50 bp in vcf format El Cancer CancerSampleBarcode Normal El Cancer CancerSampleBarcode Normal NormalSampleBarcode somaticSNVs vcf gz Single nucleotide variant somatic calls in vcf format El Cancer CancerSampleBarcode Normal NormalSampleBarcode somaticSVs vcf gz Somatic Structural Variation somatic calls 51 bp 10 kb in vcf format md5sum txt checksum file for confirming file consistency Part 15040893 Rev C NOTE All the vcf files that Ilumina provides are compressed and indexed using tabix For details about tabix see the tabix manual in SAMtools at samtools sourceforge net tabix shtml The tabix index shows up as an additional Sample_Barcode TYPE vcf gz tbi file It can be used for fast retrieval of targeted regions in the associated vcf gz file The tabix index shows up as an additional Cancer CancerSampleBarcode _Normal NormalSampleBarcode TYPE vcf gz tbi file and can be used for fast retrieval of targeted regions in the associated vcf gz file NOTE For some VCF files a binary format of the annotations and their indexes are contained in corresponding vcf ant and vcf ant idx files respectively If the vcf ant file is maintained in the same directory as its VCF file the annotation information can be visualized alongside the variant call information w
28. e plot Green links Segmental duplications at the center of the circle Green boxes Inversions the first inner track Purple boxes Deletions the second track The width of the boxes indicates the length of SVs Purple bars Insertion breakpoints the third track Red links Translocations The end of the links indicates the 2 breakpoints of SVs The density of PASS somatic indels reported in Cancer CancerSampleBarcode Normal NormalSam pleBarcode somaticIndels vcf gz in 1 Mb windows The scale of Y axis in the histogram indicates the counts The density of PASS somatic SNVs reported in Cancer CancerSampleBarcode Normal NormalSam pleBarcode somaticIndels vcf gz in 1 Mb windows arbitrarily scaled in a histogram with Y axis pointing inward The LOH regions with SNP calls in the normal genome but a homozygous reference call in the tumor genome in Cancer CancerSampleBarcode _Normal NormalSampleBarcode CNAs vcf gz Part 15040893 Rev C TIA CAST Looe TTLL DPYD ge TTC ch VAV3 STXBP3 WARS2 PDE4DIP NBPFio OTUD7B LRRC71 FCGR3A DIGENi E DM FH usus Legend E Label From Inner Circle to Outer Circle B allele frequency Called level Karyotype Chromosome position Chromosome number HGNC symbols for genes harboring variants Genes of nonsynonymous variants Depth B Allele Plot The B allele plot provides the B allele frequ
29. een Uncapped values are reported in a VCF file generated in VCF 4 1 format Analysis Overview CNV VCF The following metadata is used in INFO fields of the Copy Number Variations CNV VCF file ID Description lt CNV gt Indicates that the alternate allele is reported SV TYPE Specifies the structural variant type which is CNV in a CNV VCF file CN Reports the copy number of each segment LOH A binary indicator of the presence or absence of LOH for a given segment The following VCF example record shows a copy number gain of 6 chr2 140982000 chr2 141842999 G lt CNV gt 1 75 PASS SVTYPE CNV END 141842999 CN 6 LOH 0 The following VCF example record shows a copy number gain of 3 and an LOH event chr2 141843000 chr2 205542999 A lt CNV gt 3 71 PASS SVTYPE CNV END 205542999 CN 3 LOH 1 y Fi Part 15040893 Rev C Appendix Illumina FastTrack Services Annotation Pipeline Cancer Analysis Services User Guide 28 Appendix Ilumina FastTrack Services Annotation Pipeline The Illumina FastTrack Services Annotation Pipeline provides variant annotation for Single Nucleotide variants SNVs insertions and deletions indels All annotations are provided in the INFO field of Sample_Barcode vcf gz file and documented in the header Larger variants CNAs SVs are not annotated with the full pipeline The annotation database is queried for each of the small variants input to the pipeline Both pos
30. ency detected by SENECA sensitive detection copy numbers in cancer package Description The B allele ratios calculated by SENECA are used in the ploidy and purity estimation The copy number aberrations from Cancer CancerSampleBarcode _Normal NormalSampleBarcode CNAs vcf gz file The scale of Y axis in the histogram indicates the called level The standard Circos ideogram defining the chromosome position identity and color of cytogenetic bands The reference coordinates along the chromosome in megabases Chromosome number 1 2 22 X Y HGNC genes impacted by somatic SNVs Genes containing SNVs in the coding region with an HGNC symbolare labeled Genes identified in J resulting in nonsynonymous changes in the coding region are highlighted in red uodey Aeuluns The top graph provides the ratio of the tumor read depth to the normal read depth after normalizing for sequencing coverage Each point represents a 20 kb genomic region Points are classified as either copy number gain red copy number loss green or copy number unchanged black Figure 1 Example Graph e 7 i le gain d noch H IW he 3 i loh L s d Us M i r nay maai wm su mn PI P en mo J Paid tona Clann MEE ste aca LI E je ua ov Lu j v s KI e 9 H 2 d e 9 e E e e o N o or BOSH x The bottom graph provides the variant allele frequencies in the tumor sample at dbSNP
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32. eport pdf Summary report in pdf format Genotyping 3 Sample Barcode idats Folder containing genotyping intensity data files for the sample idat files and genotyping sample sheet El Sample Barcode Genotyping vcf gz Genotyping SNPs mapped to reference in vcf format El Sample Barcode GenotypingReport txt Genotyping SNPs tab delimited report Variations El Sample Barcode CNV vcf gz Copy number calls 10 kb in vcf format E Sample Barcode Indels vcf gz Small Insertion Deletion calls in vcf format El Sample Barcode SNPs vcf gz Single nucleotide polymorphism SNVs calls in vcf format El Sample Barcode SV vcf gz Large Structural Variation calls 51 bp 10 kb in vcf format El Sample Barcode genome vcf gz Genome vcf file containing SNVs indels and reference covered regions El Sample Barcode vcf gz vcf file containing basic annotations and SNV and indel calls md5sum txt checksum file for confirming file consistency 7 SomaticVariations E Cancer CancerSample Barcode Normal NormalSample Barcode SummaryReport pdf Summary report in pdf format Metrics El Cancer CancerSample_Barcode _Normal NormalSample_ Barcode Metrics json Metrics in json format E Cancer CancerSample Barcode Normal NormalSample Barcode somaticCNVs vcf gz Somatic calls for regions with copy number aberrations CNAs 10 kb and loss of heterozygosity LOH in v
33. ethods or for specific nucleic acid biomarkers sequences or combinations of biomarkers or sequences are examples of Application Specific IP Consumable s means Illumina branded reagents and consumable items that are intended by Illumina for use with and are to be consumed through the use of Hardware Documentation means Illumina s user manual for this Product including without limitation package inserts and any other documentation that accompany this Product or that are referenced by the Product or in the packaging for the Product in effect on the date of shipment from Illumina Documentation includes this document Hardware means Illumina branded instruments accessories or peripherals Ilumina means Illumina Inc or an Illumina affiliate as applicable Product means the product that this document accompanies e g Hardware Consumables or Software Purchaser is the person or entity that rightfully and legally acquires this Product from Illumina or an Illumina authorized dealer Software means Illumina branded software e g Hardware operating software data analysis software All Software is licensed and not sold and may be subject to additional terms found in the Software s end user license agreement Specifications means Illumina s written specifications for this Product in effect on the date that the Product ships from Ilumina 2 Research Use Only Rights Subject to these terms and conditions and unless otherwise agreed upon
34. gth approaches the fragment size The method cannot detect nontandem repeats While Isaac SV Caller classifies novel DNA adjacencies it does not infer the higher level constructs implied by the classification For instance a variant marked as a deletion by Isaac SV Caller indicates an intrachromosomal translocation with a deletion like break end pattern However there is no test of depth b allele frequency or intersecting adjacencies to infer the SV type directly Part 15040893 Rev C Copy Number Aberrations SENECA The copy number aberrations module is also referred to as SENECA SEnsitive detection of copy NumbErs in CAncer It identifies copy number aberrations CNAs in heterogeneous tumor samples that exhibit contamination with normal tissues aneuploidy and loss of heterozygosity LOH that can confound correct copy assignment and lead to erroneous CNA calls The algorithm workflow comprises 2 distinct steps Segmentation of data into regions with putatively distinct copy numbers Calculation of ploidy and purity with a final copy number assignment As input SENECA uses aligned sequences from tumor and matched normal samples in bam format and annotation information about the location of known variants in dbSNP regional alignability and the location of gaps in dbSNP Segmentation SENECA is a count based method to assign copy number state It compares coverage between tumor and normal samples Specifically it bi
35. hen imported to VariantStudio Cancer Analysis Services User Guide 8 eJnjonJ1g JOp 04 US Analysis Deliverables SomaticVariations The somatic variations folder contains all the variant calls produced for the somatic analysis The variant files that Illumina provides conform to the variant call format VCF 4 1 specifications For more information on the details of the VCF format see www 1000genomes org wiki Analysis V ariant 20Call 20Format vcf variant call format version 41 Cancer CancerSampleBarcode Normal NormalSampleBarcode somaticSNVs vcf gz SNV files contain single nucleotide variations called through Isaac Somatic Variant Caller for somatic analysis in VCF 4 1 format Table 1 INFO Fields ID Description O55 Quality score for any somatic SNV ie the ALT allele to be present at a significantly different frequency in the tumor and normal TOSS Data tier used to compute QSS NT Genotype of the normal in all data tiers as used to classify somatic variants One of ref het hom conflict OSS NT Quality score reflecting the joint probability of a somatic variant and NT TOSS NT Data tier used to compute OSS NT SGT Most likely somatic genotype excluding normal noise states SOMATIC Somatic mutation flag Table 2 FORMAT Fields ID Description DP Read depth for tier 1 used filtered FDP Number of base calls filtered from original read depth for tier 1 SDP Number of reads with deletions spanning thi
36. hts expressly granted to Purchaser hereunder or any breach by Purchaser of these terms and conditions iii the use of this Product in combination with any other products materials or services not supplied by Illumina iv the use of this Product to perform any assay or other process not supplied by Illumina or v Illumina s compliance with specifications or instructions for this Product furnished by or on behalf of Purchaser each of i v is referred to as an Excluded Claim Indemnification by Purchaser Purchaser shall defend indemnify and hold harmless Illumina its affiliates their non affiliate collaborators and development partners that contributed to the development of this Product and their respective officers directors representatives and employees against any claims liabilities damages fines penalties causes of action and losses of any and every kind including without limitation personal injury or death claims and infringement of a third party s intellectual property rights resulting from relating to or arising out of i Purchaser s breach of any of these terms and conditions ii Purchaser s use of this Product outside of the scope of research use purposes iii any use of this Product not in accordance with this Products Specifications or Documentation or iv any Excluded Claim Conditions to Indemnification Obligations The parties indemnification obligations are conditioned upon the party seeking indemnif
37. ication i promptly notifying the other party in writing of such claim or action ii giving the other party exclusive control and authority over the defense and settlement of such claim or action iii not admitting infringement of any intellectual property right without prior written consent of the other party iv not entering into any settlement or compromise of any such claim or action without the other party s prior written consent and v providing reasonable assistance to the other party in the defense of the claim or action provided that the party reimburses the indemnified party for its reasonable out of pocket expenses incurred in providing such assistance Third Party Goods and Indemnification Illumina has no indemnification obligations with respect to any goods originating from a third party and supplied to Purchaser Third party goods are those that are labeled or branded with a third party s name Purchaser s indemnification rights if any with respect to third party goods shall be pursuant to the original manufacturer s or licensor s indemnity Upon written request Illumina will attempt to pass through such indemnity if any to Purchaser Part 15040893 Rev C Revision History Part Revision Date 15040893 C June 2015 15040893 B November 2014 15040893 A July 2013 Cancer Analysis Services User Guide Description of Change Revised documentation to reflect changes in version 4 of the Illumina FastTrack Cancer Analysis
38. illumina Cancer Analysis Services User Guide OBAT C E EE R TAG e MID ANE ALTAS C TOT POS CCC E CET CCE RAGE ET AR pp pa ali A GTACCATTAAGAGCTAC TGATAACAG TAACACACT TCTGTTAACCT TAAGAT TACTTGT TGATCCACTGATTCAACGTACCG TATCAAT TGAGAC TAAATAT TAACG TACCAT TAAGAGC TACCGTCTTCTGTTAACCTTAAGAT TACTTGATCCACTGATTCAACGTACCG CACT GAT TGAACGTACCAAGATTAGT IGATCCACTGATI CAAGGIAGGGI subscr qe SO CATT O TA CO A RE RI A E SC ILI Go GUE NL GAAAAGAATGATAACAGTAACACACTTCTGTTAACCTT VAR C AGT GA eae TACCG TO OO NTE CAACGTACCGTAACGAACGTATCAAT TGAGACTAAATAT TAACGTACCAT TAAGAGCTAC TGATAACAG IAACACACT TCTGTTAACCTTAAGAT T ACT GATCCACTGATTCAACGTACCGTAACGAACG TATCAAT TGAGAC TAAATATTAACGTACCAT TAAGAGCTACCGTCTTCTGT TAACCT TAA CATH ACTTGATCCACTGAT TCAAC ITIGAGACTAAATAT AGG LG TAACCT TAAGAT TAC GATCCACTGAT IGAAGG TACCGTAACGAACG TAI AA GAGAC IAMATALIAAGG TACCAT IAAGAGC EE VA LO E Ek EEN E TGATTCAACGT E AACGAACGTCTTCTGTTAACCTTAAGAT TACTTGATCCACTGATT CAACGTACCGTAACGAA ART EE e E CTAAATA CGTACCAT TAAGAGCTACAACCT T TAGATOCAG TGATTCAACGTACCGTAACGAACGTATCAAT TGAGACTAAATAT TAACG TACCAT TAAGAGC TACCGTGCAACGACGAAAAGAA GTAACAC IGATAACAGTAACAGAGT GG TRACE TAGAT TACT IGATGOAG GAT GAACGIAGGG TAAGGAAGG ATCAATTGAGACTAAATAT TAACGTACCATTAAGAGCTACCGTCTTCT E TAAGA MAG LTGATCCAGTOATICAAC e er GATTACTTGATCCACT RATIO UAE AAA TET TS AAAT AT AER ACCATTAAGAGCTACCGTGCAACGACGAACTTCTGTTAACCT TAAGAT TACT T ion GCTACCGTGCAACGAAAATAA AAGATTACTTGATCCACTGATTCAACG AACCTTAAGATTACTTGATCCACTGATTCAACGTACCGTAACGA
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40. itional and allelic annotations can be returned for a given variant After querying the annotation database novel variants variants for which no annotation exists are then processed with VEP If VEP does not return an annotation for the variant it will remain unannotated Annotation Database Sources 29 The following table includes sources for the annotation databases Table 15 List of Annotation Database Sources Source Version Variant Effect Predictor 72 1000 Genomes Allele Frequencies v3 Release 20110521 ClinVar 20130905 COSMIC 65 dbSNP 137 HGNC RefSeq Mapping Updated daily NHLBI Exome Variant Server v 0 0 20 ESP6500SI V2 phastCons N A Release Date 06 01 2013 04 30 2012 09 05 2013 05 28 2013 06 16 2012 07 01 2013 06 07 2013 12 06 2009 Part 15040893 Rev C Technical Assistance For technical assistance contact Illumina Technical Support Table 16 Illumina General Contact Information Website www illumina com Email techsupport illumina com Table 17 Illumina Customer Support Telephone Numbers Region Contact Number Region Contact Number North America 1 800 809 4566 Italy 800 874909 Australia 1 800 775 688 Netherlands 0800 0223859 Austria 0800 296575 New Zealand 0800 451 650 Belgium 0800 81102 Norway 800 16836 Denmark 80882346 Spain 900 812168 Finland 0800 918363 Sweden 020790181 France 0800 911850 Switzerland 0800 563118 Germany 0800 180 8994 United Kingdom 0800 917 0041 Ireland 1 800 812949 Othe
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42. le f f_A C GfT The allele frequencies are restricted to allow a maximum of 2 nonzero frequencies Any additional alleles observed in the data are treated as noise Another departure from typical germline calling methods is that the state space of the model is the allele frequency of both the tumor and the normal sample O f t f n In the equation above f t and f n represent the allele frequencies of the tumor and normal samples respectively The final somatic variant quality value reported by the model is computed from the probability that the allele frequencies are unequal ie f t f n given the observed sequence data Part 15040893 Rev C Post Call Filtration Heuristic filters remove several types of improbable calls resulting from data artifacts that cannot be easily represented in the somatic probability model These filters act as a final step to separate out the final set of somatic calls reported by Isaac Somatic Variant Caller Input Data Filtration Isaac Somatic Variant Caller uses 2 tiers of input data filtration during somatic small variant calling Tier 1 A more stringent filtering to ensure high quality calls Tier 2 A lower filtration stringency Initially candidates are called using a subset of the data with more stringent tier 1 filtering If the method produces a nonzero quality score for any SNV or indel the potential somatic variant is called again using data with a lower tier 2 stringency The l
43. lect negligence accident improper storage or use contrary to the Documentation or Specifications ii improper handling installation maintenance or repair other than if performed by Illumina s personnel iii unauthorized alterations iv Force Majeure events or v use with a third party s good not provided by Illumina unless the Product s Documentation or Specifications expressly state such third party s good is for use with the Product d Procedure for Warranty Coverage In order to be eligible for repair or replacement under this warranty Purchaser must i promptly contact Illumina s support department to report the non conformance ii cooperate with Illumina in confirming or diagnosing the non conformance and iii return this Product transportation charges prepaid to Cancer Analysis Services User Guide Illumina following Illumina s instructions or if agreed by Ilumina and Purchaser grant Ilumina s authorized repair personnel access to this Product in order to confirm the non conformance and make repairs Sole Remedy under Warranty Ilumina will at its option repair or replace non conforming Product that it confirms is covered by this warranty Repaired or replaced Consumables come with a 30 day warranty Hardware may be repaired or replaced with functionally equivalent reconditioned or new Hardware or components if only a component of Hardware is non conforming If the Hardware is replaced in its entirety the warranty per
44. ns read coverage using nonoverlapping 1 kb windows to derive counts in tumor and normal samples and it then takes the ratio of the 2 counts Bins are skipped during segmentation when they overlap low alignability regions in more than 20 of their size Independently SENECA calculates B allele ratios at dbSNP positions from a tumor BAM file and it keeps only SNVs that are heterozygous in the corresponding normal sample Segmentation is carried out independently for copy number and B allele ratios Ploidy and Purity Calculation Following segmentation SENECA performs ploidy and purity calculations These calculations are based on the principle that for each value of ploidy and purity and a selected copy number the values of B allele and read count ratios are inferred For example for copy number state 1 1 deleted allele of a diploid genome the B allele ratio is always near 0 because only 1 allele is present However if a tumor sample has only 70 percent purity because of the presence of the normal genome as background the B allele ratio increases due to the presence of a heterozygous normal allele The low percentage of purity results in a final B allele ratio of 0 15 SENECA fits a multivariate Gaussian distribution to copy data and B allele ratio data on a two dimensional grid of varying ploidy and purity On the grid each state encodes ploidy and purity values In addition SENECA uses a separate state encoding copy neutral LOH and copy
45. nto the classes of variants called and their overlap with annotated genes All counts are based on PASS filter variants Circos Plot of Somatic Variations Depth B allele Plot For more information about this summary report see the technical support note Molecular Characterization of Tumors Using next generation sequencing The Sample Barcode SummaryReport pdf report contains an overview of the germline analysis results from the normal sample For detailed information on this report see the Whole Genome Sequencing Services User Guide part 15040892 Circos Plot of Somatic Variations The Circos plot provides visualization of somatic small variation ploidy and structural variations reported in the somatic variation files VCF The Circos plot displays somatic variation data in tracks with chromosomes circularly arranged Following is an example legend Labels are described from inside the circle to the outside Cancer Analysis Services User Guide 1 4 uodey Aeuluns Analysis Deliverables 15 Table 13 Circos Plot Legend Legend A Label From Inner Circle to Outer Circle Somatic structural variants Number of somatic indels per Mb Number of somatic SNVs per Mb Copy neutral loss of heterozygosity LOH X X b K Description The somatic structural variants detailed in Cancer CancerSampleBarcode _Normal NormalSam pleBarcode somaticSVs vcf gz are plotted in the center of th
46. of proven algorithms that are optimized for the complexities of tumor samples to deliver a set of accurate somatic variants High quality sequence reads are aligned using the Isaac Alignment Software and somatic variant calling is performed using Isaac Somatic Variant Caller Strelka a combined Bayesian caller Two complementary approaches enable detection of large somatic structural variations Read depth analysis by SENECA for somatic structural variant events See Copy Number Aberrations SENECA on page 26 Discordant paired end analysis by Isaac Structural Variant Caller Manta See Isaac Structural Variant Caller on page 24 Identified small somatic variants are reported with RefSeq annotations COSMIC annotations functional consequence predictions and overlap with gene structure components and regulatory motifs This document provides an overview of the source and contents of the main files Ilumina creates these files using the informatics pipeline and information about key algorithms like Isaac Somatic Variant Caller Isaac Structural Variant Caller and SENECA The main files are to help you understand the Cancer Analysis Service data package that you receive from Ilumina The following versions of software packages are utilized in the Cancer Analysis Service v4 0 2 pipeline Software Version Purpose Isaac Somatic 2 0 14 Somatic SNV and indel caller Variant Caller Isaac 0 23 1 Germline and somatic structural variant caller Candid
47. ot match the somatic calls from a combined caller For example you can find a somatic variant that was not called in the tumor WGS sample because the combined caller is operating on the reads Figure 2 Cancer Analysis Pipeline Alignment Variant Analysis Data Output Tumor Data Isaac Isaac VCF Bere uz Somatic Variant Caller Somatic SNVs Normal Data A VCF Isaac Isaac Somatic Indels BCLs IF o EAN gt Structural Variant Caller gt VCF Somatic SVs SENECA gt Copy number Aberration VCF Somatic CNAs 1 Q Part 15040893 Rev C Isaac Somatic Variant Caller The Isaac Somatic Variant Caller detects somatic SNVs and indels in sequencing data from a tumor and matched normal sample based on the following assumptions The normal sample is a mixture of diploid germline variation and noise The tumor sample is a combination of the normal sample and somatic variation It is assumed that the somatic variation and the normal noise can occur at any allele frequency ratio For SNVs but not for indels the normal noise component is further modeled as a combination of single strand and double strand noise Figure 3 Isaac Somatic Variant Caller Method Normal Sample Tumor Sample Alignments BAM Candidate Indel Alignments BAM Search Candidate Indels Realignment Realignment Normal Realigned Tumor Realigned Reads Reads Somatic Caller Unfiltered Somatic Variants Post Call Filtration Somatic Vari
48. ower quality from the 2 tiers is selected for output However if the tier 2 quality is 0 the call is eliminated For somatic SNVs and indels Isaac Somatic Variant Caller produces a general somatic quality score Q ssnv or Q somatic indel This score indicates the probability of the somatic variant and a joint probability of the somatic variant and a specific normal genotype O ssnv ntype or O somatic indel ntype The 2 tier evaluation is applied to each of these qualities separately as follows Q ssnv min Q ssnv tier1 O ssnv tier2 Q ssnv ntype min O ssnv ntypel tier1 O ssnv ntypel tier2 The tier used for each quality value is provided in the Isaac Somatic Variant Caller output record for each somatic variant If the most likely normal genotype is not the same at tier 1 and tier 2 then the normal genotype is reported as a conflict in the output Using 2 data tiers enables an initial somatic call based on high quality data Given a potential call using 2 data tiers removes support for the putative somatic allele in the normal sample from lower quality data The following table lists the primary data filtration levels that are changed between tier 1 and tier 2 Table 14 Tiered Filtration Parameters Parameter Tier 1 Value Tier 2 Value Min paired end alignment score 20 0 Min single end alignment score 10 0 Single end score rescue No Yes Include unanchored pairs No Yes Include anomalous pairs No Yes Include
49. r countries 44 1799 534000 Safety Data Sheets Safety data sheets SDSs are available on the Illumina website at support illumina com sds html Product Documentation Product documentation in PDF is available for download from the Illumina website Go to support illumina com select a product then click Documentation amp Literature Cancer Analysis Services User Guide 3 O S9UBISISSY JEOIUYDS RM STAT A e mapa EE E Lage BLL pie ig Oly allel Ee FGATAACAGTAACACACTTCTGTTAACCTT TTGTTGATCCACTGATTCAACGTACCGTATCAAT TGAGAC TAAATAT IAACGTACCAT TAAGAGCTACCGTCTTCTGTTAACCTTAAGAT TACTI GATCCAC TGATTCAACGTACCGI GACT GATT GAACGACCAAGAT TACT IGATGCACT GAT I CAAGG TACUGTAACGAACGTAT CAAT EE GTTAACCTTAAGATTACTTGATCCACTGATTCAACGTACCGTAACGZ GAATGATAACAGTAACACACTTCTGTTAACCTTAAGAT TACTTGATCCACTGAT TCAACGTACCGTAAAGATTAC T TGATCCACTGAT TCAACGTACCGTAACGAACGTATCAAT TGAGAC T DEREN ACH e e GATAACAGTAACACACT TCTGTTAACCTTAAGAT TACTTGATCCACTGAT TCAACGTACCGTAACGAACG TATCAAT TGAGAC TAAATATTAACG TACCAT TAAGAGCTACCGTCT TC TGT TAACCT TAAGATTACT T CTGATT Uu yeso Slat tg SAE AIL al CR ER CRIE APE ARE AR Ue a RENE EEE TAACGAACGTATCAAT IGAGACTAAATAT TAACGTACCAT TAAGAGCT GTG AACGAAGAT ACT GATGCAC GA GAACGIACOG El ee Kee AR TAE LASTI E ET SAU RA A TRA UAR NARRA TG TT CTGTTAACCTT AGAT BL RATE CAGE TTC ATE eS ET Roe MAGENTA ACTE ART AACGACG CTAAATA CAT TAAGAGCTAC TTACTTGATCCACTGATTCAACGTACCGTAACGAACQG TATCAAT TGAGACTAAATAT TAACG TACCAT TAAGAGC TACCGTGCAAC GAAAAG AACAGTAACAC
50. s site in tier 1 SUBDP Number of reads below tier 1 mapping quality threshold aligned across this site AU Number of A alleles used in tiers 1 and 2 CU Number of C alleles used in tiers 1 and 2 GU Number of G alleles used in tiers 1 and 2 TU Number of T alleles used in tiers 1 and 2 Part 15040893 Rev C Table 3 FILTER Fields ID DR Greater than 3x chromosomal mean depth in the normal sample BCNoise SpanDel QSS ref Description Fraction of base calls filtered at this site in either sample is gt 0 4 Fraction of reads crossing this site with spanning deletions in either sample is gt 0 75 Normal sample is not homozygous with the reference or the SNV quality score ssnv is lt 15 ie calls with NT ref or OSS NT lt 15 Cancer CancerSampleBarcode Normal NormalSampleBarcode somaticlndels vcf gz Indel files contain indels called through Isaac Somatic Variant Caller for somatic analysis in VCF 4 1 format Small indels are limited to 50 bp Table 4 INFO Fields ID OSI TOSI NT OVERLAP QSI NT TOSI NT SGT SOMATIC SMIRE RU INC IC IHP Table 5 FORMAT fields ID DP Read depth for tier 1 Cancer Analysis Services User Guide Description Quality score for any somatic variant ie the ALT haplotype to be present at a significantly different frequency in the tumor and normal sample Data tier used to compute QSI Genotype of the normal sample in all data tiers
51. singleton pairs No Yes Mismatch density filter max mismatches in window 3 10 Additional Filtration Additional filters are applied after the somatic caller completes A single candidate somatic call can be annotated with several filters as described in the FILTER fields tables SomaticVariations on page 9 Cancer Analysis Services User Guide 2 2 J9 29 JUBA oewos oees Analysis Overview Figure 4 Additional Filtration All Small Variants DP Greater than 3x chromosomal mean depth in the normal sample Quality Filtration Levels Only somatic calls originating from homozygous reference alleles in the normal sample are SNVs BCNoise Fraction of base calls filtered at this site in either sample is 2 0 4 SpanDel Fraction of reads crossing this site with spanning deletions in either sample is gt 0 75 QSI ref Normal sample is not homozygous with the reference or the quality score ssnv is lt a ie calls with NT ref or QSS_NT lt 15 Repeat Sequence repeat of more than 8x in the reference sequence iHpol Overlaps an interrupt ed homopolymer longer than 14x in the reference sequence BCNoise Average fraction of filtered base calls within 50 bases of the indel is gt 0 3 QSI ref Normal sample is not homozygous with the reference or the quality score somatic indel is lt 30 ie calls with NT ref or QSS NT lt 30 reviewed for validation and included in the output Somatic S
52. tic score is less than 30 Cancer CancerSampleBarcode Normal NormalSampleBarcode CNAs vcf gz The somatic CNA file contains copy number aberrations and loss of heterozygosity calls from the CNA module This file is in VCF 4 1 format and contains the following fields Table 11 INFO Fields ID Description SVY RE Type of structural variant see ALT fields END End position of the variant described in this record CN Copy number genotype for imprecise events LOH Loss of heterozygosity indicator Table 12 ALT Field ID Description CNV Copy number variable region 1 3 Part 15040893 Rev C Summary Report The Cancer CancerSampleBarcode _Normal NormalSampleBarcode SummaryReport pdf report contains an overview of the somatic analysis results for the samples including the following sections Sample Information This section contains information associated with the samples from the provided sample manifest Purity Ploidy Estimates This section details the estimated purity and ploidy for the cancer sample output from the Copy Number Aberration module For more details see Ploidy and Purity Calculation on page 26 Somatic Small Variants Summary These 2 tables provide the total number of SNVs and Somatic Indels overlapping known variants and genes exons and coding regions All counts are based on annotation and use only PASS filter variants Somatic Structural Variants Summary This table breaks CNA and Somatic SV output i
53. ts in an inwards orientation between the 2 reads of each DNA fragment Each read presents a read from the outer edge of the fragment insert inward Cancer Analysis Services User Guide 2 4 J9 29 JUBULA esnJONI1S oees Analysis Overview Detected Variant Classes Isaac SV Caller is able to detect all variation classes that can be explained as novel DNA adjacencies in the genome Simple insertion deletion events can be detected down to a configurable minimum size cutoff defaulting to 51 All DNA adjacencies are classified into the following categories based on the break end pattern Deletions Insertions Inversions Tandem Duplications Interchromosomal Translocations Known Limitations 20 Isaac SV Caller cannot detect the following variant types Nontandem repeats amplifications Large insertions The maximum detectable size corresponds to approximately the read pair fragment size but note that detection power falls off to impractical levels well before this size Small inversions The limiting size is not tested but in theory detection falls off below 200 bases So called microinversions might be detected indirectly as combined insertion deletion variants More general repeat based limitations exist for all variant types Power to assemble variants to break end resolution falls to 0 as break end repeat length approaches the read size Power to detect any break end falls to nearly 0 as the break end repeat len
54. y responsible for determining whether Purchaser has all intellectual property rights that are necessary for Purchaser s intended uses of this Product including without limitation any rights from third parties or rights to Application Specific IP Illumina makes no guarantee or warranty that purchaser s specific intended uses will not infringe the intellectual property rights of a third party or Application Specific IP Part 15040893 Rev C 3 Regulatory This Product has not been approved cleared or licensed by the United States Food and Drug Administration or any other regulatory entity whether foreign or domestic for any specific intended use whether research commercial diagnostic or otherwise This Product is labeled For Research Use Only Purchaser must ensure it has any regulatory approvals that are necessary for Purchaser s intended uses of this Product 4 Unauthorized Uses Purchaser agrees a to use each Consumable only one time and b to use only Illumina consumables reagents with Ilumina Hardware The limitations in a b do not apply if the Documentation or Specifications for this Product state otherwise Purchaser agrees not to nor authorize any third party to engage in any of the following activities i disassemble reverse engineer reverse compile or reverse assemble the Product ii separate extract or isolate components of this Product or subject this Product or components thereof to any analysis not expressly author

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