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Hidden Treasures - Warm Up – precisionFDA\nHidden Treasures - Warm Up\nFind variants injected into an NGS dataset\n2017-09-13 06:59:00 UTC\nThe precisionFDA Hidden Treasures – Warm Up ran from July 19, 2017 to September 13, 2017. It provided participants a unique opportunity to investigate the accuracy of their pipelines by testing the ability to find in silico injected variants in FASTQ files from exome sequencing of reference cell lines. It was offered as a warm up ahead of potentially more difficult in silico challenge(s) to come. There were 86 valid entries from 30 participants to the challenge.\nThis precisionFDA Hidden Treasures – Warm Up challenge results page displays the summarized results as two separate tables, with the opportunity to click on some of the features in each table and get more detailed information. As with previous challenges, due to novelties related to the truth data and the comparison methodology, these results offer a first glance at our understanding. We welcome the community to further explore these results and provide insight for the future.\nAt the start of this challenge, users were provided with a NA12878 whole exome sequencing FASTQ file that had been in silico modified with single nucleotide variants (SNVs) and insertion and deletion (InDel) variants (less than 40 bp) at approximate Variant Allele Frequencies (VAFs) ≥20%. This precisionFDA note summarizes certain precisionFDA artifacts related to the challenge, including a VCF with the injected variants, as well as the VCF evaluation app which was used by the system to automatically evaluate all entries. We invite the community to try the evaluation app and give us any feedback.\nChallenge participants ran the modified FASTQ file through their pipeline(s), and returned the resulting VCF file to precisionFDA for comparison to the known reference truth using a VCF evaluation app that we created. The first table below shows calls for 50 injected variants, including SNVs and InDels sorted separately by size (1-3 bp, 4-6 bp, 7-9 bp, 10-12 bp, and larger than 13 bp), for each entry in a separate row. Results shown for each entry also include whole exome recall, precision and F-score* for overall SNVs and overall InDels:\nRecall, or sensitivity, reflects the percentage of variants in the NIST/GiaB benchmark set that were exactly called by the challenge participant pipeline in a submitted dataset.\nPrecision, or positive predictive value, reflects the percentage of called variants which match exactly the NIST/GiaB benchmark set.\nF-score is the harmonic mean of recall and precision, and is sometimes used as a single combined metric for evaluating overall accuracy.\nThe entries are sorted alphabetically by the name of the submitter, since many submitters had multiple entries. Moreover, the Entry column contains a link to the precisionFDA job that resulted from the execution of the evaluation app on that entry. All jobs, and the resulting files as output by the evaluation app, have been made public on precisionFDA and are owned by the special user 'Challenge Robot'.\nParticipants whose submissions correctly detected and called all 50 injected variants (regardless of the whole exome precision, recall and F-score for their pipeline/submission) are being recognized as Warm Up in silico Variant Catchers and are designated with the Variant Catcher icon in the table (45 entries earned that title).\n* The terminology currently used in this discussion (such as "precision" and "recall") is not necessarily harmonized with definitions used by ISO, CLSI, or FDA, but are terms commonly used by NGS software developers.\nInjected indels Injected Whole-exome SNP Whole-exome indel\nVijay Walia Variant Catcher FDA VW_submission_1 11 11 11 11 1 5 50 0.990646 0.99029 0.990468 0.716542 0.858191 0.780996\nJustin Lack Variant Catcher NIH JLack_CCBR_Leidos_StandardPipeline_relaxed 11 11 11 11 1 5 50 0.993357 0.988074 0.990708 0.788118 0.858511 0.82181\nJustin Lack Variant Catcher NIH JLack_CCBR_Leidos_StandardPipeline_noFilter 11 11 11 11 1 5 50 0.990352 0.988212 0.989281 0.710399 0.860213 0.778161\nChung Tsai Su Atgenomix SeqsLab with GATK-based Parallelization 11 11 11 11 0 5 49 0.994188 0.976203 0.985113 0.695819 0.849043 0.764832\nChung Tsai Su Atgenomix SeqsLab with GATK-based Parallelization(conf>30) 11 11 11 11 0 5 49 0.995428 0.974222 0.984711 0.746753 0.843404 0.792141\nIgor Dolgalev Variant Catcher NYU Langone Medical Center GATK HaplotypeCaller unfiltered 11 11 11 11 1 5 50 0.985822 0.982145 0.98398 0.751669 0.854043 0.799592\nIgor Dolgalev Variant Catcher NYU Langone Medical Center GATK HaplotypeCaller depth-filtered 11 11 11 11 1 5 50 0.986218 0.903786 0.943204 0.743792 0.792979 0.767598\nTheresa Wohlever Variant Catcher Test 11 11 11 11 1 5 50 0.991177 0.991343 0.99126 0.661186 0.867447 0.750401\nRafael Aldana Variant Catcher Sentieon Inc Sentieon_DNAseq_std-NA12878MOD 11 11 11 11 1 5 50 0.995136 0.989085 0.992101 0.748639 0.86266 0.801615\nRafael Aldana Variant Catcher Sentieon Inc Sentieon_TNscope_Tonly_std-NA12878MOD 11 11 11 11 1 5 50 0.600924 0.598465 0.599692 0.394585 0.413936 0.404029\nJongsuk Chung Samsung Genome Institute SGI_1st_result 4 6 6 4 0 4 24 0.990799 0.989002 0.9899 0.752093 0.859362 0.802157\nJongsuk Chung Samsung Genome Institute SGI_2nd_filtration 5 9 7 7 0 5 33 0.9893 0.991357 0.990327 0.697161 0.866489 0.772657\nJongsuk Chung Samsung Genome Institute SGI_4th_filtration 7 11 8 10 1 5 42 0.587313 0.601263 0.594206 0.432052 0.43734 0.43468\nJongsuk Chung Samsung Genome Institute SGI_3rd_filtration_rere 7 10 6 8 0 5 36 0.964913 0.991744 0.978145 0.612791 0.843085 0.709724\nMark Cowley Variant Catcher Garvan Institute KCCG_1.7.0_HC 11 11 11 11 1 5 50 0.995136 0.989085 0.992101 0.727712 0.865 0.790439\nMark Cowley Garvan Institute KCCG_1.7.0_VD 11 10 9 11 1 5 47 0.996376 0.96972 0.982867 0.805216 0.745665 0.774297\nRongshan Yu Variant Catcher Aginome Scientific NA12878MOD.imp.vcf.gz 11 11 11 11 1 5 50 0.992302 0.990955 0.991628 0.701692 0.859681 0.772693\nRafael Aldana Variant Catcher Sentieon Inc Sentieon_DNAseq_nodecoy-NA12878MOD 11 11 11 11 1 5 50 0.991941 0.988905 0.99042 0.751527 0.862872 0.80336\nRafael Aldana Variant Catcher Sentieon Inc Sentieon_TNscope_Tonly_nodecoy-NA12878MOD 11 11 11 11 1 5 50 0.598495 0.598202 0.598348 0.39834 0.41734 0.407619\nSeverine Catreux Variant Catcher Edico Genome DRAGEN_DNASeq_NA12878MOD_submission1 11 11 11 11 1 5 50 0.991705 0.991966 0.991835 0.834423 0.895638 0.863947\nSeverine Catreux Variant Catcher Edico Genome DRAGEN_DNASeq_NA12878MOD_submission2 11 11 11 11 1 5 50 0.972662 0.992271 0.982369 0.705784 0.89917 0.790826\nSeverine Catreux Edico Genome DRAGEN_DNASeq_NA12878MOD_submission3 10 11 11 11 1 5 49 0.996531 0.990886 0.9937 0.933809 0.820213 0.873333\nSeverine Catreux Edico Genome DRAGEN_DNASeq_NA12878MOD_submission4 10 11 11 11 1 5 49 0.998621 0.962947 0.98046 0.957514 0.771277 0.854364\nSeverine Catreux Variant Catcher Edico Genome DRAGEN_DNASeq_NA12878MOD_submission5 11 11 11 11 1 5 50 0.996848 0.990165 0.993496 0.888806 0.883617 0.886204\nRongshan Yu Variant Catcher Aginome Scientific NA12878MOD.imp.v2.recode.vcf.gz 11 11 11 11 1 5 50 0.991168 0.991814 0.991491 0.68785 0.861596 0.764981\nRongshan Yu Variant Catcher Aginome Scientific NA12878MOD.imp.v3.recode.vcf 11 11 11 11 1 5 50 0.990116 0.992146 0.99113 0.670604 0.862872 0.754685\nSunho Lee Syntekabio ADIscan_NA12878MOD_all 11 11 11 10 0 5 48 0.987261 0.989348 0.988303 0.672161 0.82174 0.739462\nSunho Lee Syntekabio ADIscan_NA12878MOD_filtered 11 11 11 10 0 5 48 0.989856 0.989029 0.989442 0.688306 0.819506 0.748198\nSunho Lee Syntekabio ADIscan_NA12878MOD_tight 11 11 11 10 0 5 48 0.991681 0.988655 0.990166 0.69806 0.817167 0.752932\nSunho Lee Syntekabio ADIscan_NA12878MOD_conf 11 11 11 10 0 5 48 0.99274 0.988309 0.99052 0.70274 0.815146 0.754781\nHua Chen Variant Catcher Beijing Institute of Genomics 11 11 11 11 1 5 50 0.988619 0.988642 0.98863 0.669671 0.823974 0.738852\nHua Chen Variant Catcher BIG_NGSToolkit-NA12878.vcf 11 11 11 11 1 5 50 0.991675 0.98842 0.990045 0.826387 0.699574 0.757712\nHua Chen Variant Catcher BIG_CelerSNP-NA12878MOD.vcf 11 11 11 11 1 5 50 0.988619 0.988642 0.98863 0.669671 0.823974 0.738852\nHua Chen Variant Catcher BIG_CelerSNP-NA12878.vcf 11 11 11 11 1 5 50 0.988619 0.988642 0.98863 0.669671 0.823974 0.738852\nLiu Xueying Challenge_submission_20170912_3 11 11 11 11 0 5 49 0.993592 0.249152 0.398401 0.873303 0.041064 0.078439\nAngela Pozo INGEMM HULP-germ 11 11 11 10 0 5 48 0.984124 0.325406 0.489091 0.651468 0.132128 0.219697\nSam Friedman Broad Institute Experimental Unfiltered 11 11 10 11 1 5 49 0.993729 0.990027 0.991874 0.68276 0.839911 0.753226\nColin Hercus Novocraft Technologies NovoalignFreebayes_1 11 10 10 10 1 5 47 0.980632 0.992949 0.986753 0.784889 0.86263 0.821925\nColin Hercus Novocraft Technologies NovoalignFreebayes_2 11 10 8 8 1 5 43 0.992934 0.992188 0.992561 0.836097 0.839115 0.837603\nColin Hercus Variant Catcher Novocraft Technologies NovoalignGATKHC_1 11 11 11 11 1 5 50 0.98731 0.990512 0.988908 0.704128 0.862872 0.775459\nShawn Williams test2 6 11 11 11 1 5 45 0.264135 0.008671 0.016791 0.192833 0.012021 0.022632\nColin Hercus Variant Catcher Novocraft Technologies NovoalignGATKHC_2 11 11 11 11 1 5 50 0.98761 0.990484 0.989045 0.705217 0.861809 0.775689\nAngela Pozo INGEMM HULP-mosaic 10 9 6 7 0 3 35 0.94938 0.327677 0.487199 0.765668 0.117447 0.203655\nTian Xia Submission1 11 11 11 10 1 5 49 0.994498 0.986481 0.990473 0.747691 0.860532 0.800153\nSteve Laurie Variant Catcher CNAG B8GATK36 11 11 11 11 1 5 50 0.995892 0.973848 0.984746 0.730212 0.835426 0.779283\nSteve Laurie Variant Catcher CNAG B15GATK36 11 11 11 11 1 5 50 0.99592 0.973862 0.984767 0.731095 0.835426 0.779786\nSteve Laurie Variant Catcher CNAG G3GATK36 11 11 11 11 1 5 50 0.997145 0.972587 0.984713 0.735245 0.834149 0.78158\nShawn Williams test 6 11 11 11 1 5 45 0.264135 0.008671 0.016791 0.192833 0.012021 0.022632\nCharles Chapple Variant Catcher Saphetor Saphetor1 11 11 11 11 1 5 50 0.994249 0.960121 0.976887 0.78657 0.830106 0.807752\nCharles Chapple Variant Catcher Saphetor Saphetor2 11 11 11 11 1 5 50 0.993583 0.971341 0.982336 0.818341 0.821596 0.819965\nCharles Chapple Variant Catcher Saphetor Saphetor4 11 11 11 11 1 5 50 0.9955 0.971133 0.983165 0.812949 0.820745 0.816828\nCharles Chapple Variant Catcher Saphetor dummy 11 11 11 11 1 5 50 0.993583 0.971341 0.982336 0.818341 0.821596 0.819965\nShawn Williams Variant Catcher submission 11 11 11 11 1 5 50 0.978296 0.986536 0.982399 0.694895 0.860851 0.769021\nZitong He Variant Catcher MySubmission1 11 11 11 11 1 5 50 0.978296 0.986536 0.982399 0.694895 0.860851 0.769021\nCharles Chapple Variant Catcher Saphetor dummy 11 11 11 11 1 5 50 0.980753 0.983655 0.982202 0.691801 0.848936 0.762355\nCharles Chapple Variant Catcher Saphetor Saphetor3 11 11 11 11 1 5 50 0.993583 0.971313 0.982322 0.818492 0.821489 0.819988\nZitong He MySubmission2 11 11 11 10 1 5 49 0.994512 0.986508 0.990494 0.750626 0.860957 0.802015\nShawn Williams mySubmission_GATK 7 11 10 11 1 5 45 0.363682 0.009959 0.019388 0.125683 0.014681 0.026291\nTheresa Wohlever Whole-exome variant calling pipeline results 7 6 5 5 0 5 28 0.989802 0.981577 0.985672 0.768957 0.870134 0.816423\nPatrick Brennan Variant Catcher Nationwide Children's Hospital NCH_SUBMISSION1 11 11 11 11 1 5 50 0.99465 0.98896 0.991797 0.674428 0.846383 0.750684\nPatrick Brennan Nationwide Children's Hospital NCH_SUBMISSION2 9 10 6 6 1 5 37 0.99873 0.904229 0.949133 0.799462 0.757979 0.778168\nChristian Iseli Swiss Institute of Bioinformatics SIB 9 10 8 9 1 5 42 0.985602 0.97443 0.979984 0.753181 0.750585 0.751881\nRicha Agarwala NCBI SKESA_SRPRISM 8 8 5 6 0 1 28 0.32541 0.30702 0.315947 0.424784 0.416383 0.420542\nHong Chen Variant Catcher Sentieon Inc Sentieon_DNAseq_allmap-NA12878MOD 11 11 11 11 1 5 50 0.990597 0.989473 0.990035 0.743829 0.864787 0.79976\nHong Chen Variant Catcher Sentieon Inc Sentieon_DNAseq_allmap_nodedup-NA12878MOD 11 11 11 11 1 5 50 0.986758 0.989985 0.988369 0.721072 0.86617 0.786989\nPi Chuan Chang Google DeepVariant 8 10 9 9 1 5 42 0.997713 0.99126 0.994476 0.841122 0.876064 0.858238\nPi Chuan Chang Google DeepVariant_LowFrequency 9 10 9 11 1 5 45 0.997256 0.9918 0.99452 0.813021 0.881277 0.845774\nHanying Feng Variant Catcher Sentieon Inc Sentieon_TNscope_Tonly_allmap-NA12878MOD 11 11 11 11 1 5 50 0.594368 0.602787 0.598548 0.261532 0.539566 0.352301\nHanying Feng Variant Catcher Sentieon Inc Sentieon_TNscope_Tonly_allmap_nodedup-NA12878MOD 11 11 11 11 1 5 50 0.539536 0.603383 0.569676 0.227044 0.538502 0.319416\nHanying Feng Variant Catcher Sentieon Inc Sentieon_Exp-NA12878MOD 11 11 11 11 1 5 50 0.920606 0.99004 0.954061 0.348901 0.857964 0.496069\nHanying Feng Variant Catcher Sentieon Inc Sentieon_Exp_nodedup-NA12878MOD 11 11 11 11 1 5 50 0.822392 0.989846 0.898382 0.331927 0.854878 0.478187\nRongshan Yu Variant Catcher Aginome Scientific NA12878MOD.imp.hardfilter.recode.vcf.gz 11 11 11 11 1 5 50 0.995427 0.985927 0.990654 0.792018 0.858617 0.823974\nLiu Qi Variant Catcher BIG_myPipeline-NA12878.vcf.gz 11 11 11 11 1 5 50 0.599349 0.602261 0.600801 0.461185 0.608723 0.524782\nIgor Dolgalev NYU Langone Medical Center Bowtie2 + GATK HaplotypeCaller unfiltered 11 11 11 10 1 5 49 0.995208 0.954788 0.974579 0.78762 0.826277 0.806485\nLiu Qi BIG_HXG-NA12878.vcf.gz 11 11 10 10 0 5 47 0.989178 0.985802 0.987487 0.471407 0.745905 0.577707\nIgor Dolgalev NYU Langone Medical Center Bowtie2 + GATK HaplotypeCaller depth-filtered 11 11 11 10 1 5 49 0.995289 0.892413 0.941048 0.785136 0.776702 0.780896\nSijung Yun Yotta Biomed, LLC. Yotta1_GRCh37_liftover_from_GRCh38_sorted 10 11 11 10 1 5 48 0.992543 0.962503 0.977293 0.738275 0.830106 0.781502\nSijung Yun Yotta Biomed, LLC. Yotta2_GRCh37_liftover_from_GRCh38_sorted 0 0 0 0 0 5 5 0.930078 0.960896 0.945236 0.041667 0.001808 0.003465\nSijung Yun Yotta Biomed, LLC. Yotta3_GRCh37_liftover_from_GRCh38_sorted 10 11 11 10 1 5 48 0.975282 0.965274 0.970252 0.606772 0.835638 0.703048\nIgor Dolgalev NYU Langone Medical Center BWA-MEM + GATK + SNVer 11 9 5 8 0 5 38 0.983388 0.93052 0.956224 0.394808 0.467021 0.427889\nSeverine Catreux Variant Catcher Edico Genome DRAGEN_DNASeq_NA12878MOD_submission6 11 11 11 11 1 5 50 0.972624 0.992326 0.982376 0.705784 0.89917 0.790826\nSeverine Catreux Variant Catcher Edico Genome DRAGEN_DNASeq_NA12878MOD_submission7b 11 11 11 11 1 5 50 0.993589 0.991551 0.992569 0.8195 0.896299 0.856181\nJean Thierrymieg NCBI NCBI_Magic_ThierryMieg_NA12878MOD.b.vcf.gz 6 4 2 5 0 4 21 0.99067 0.957212 0.973654 0.733128 0.641277 0.684133\nJoon Sang Lee Variant Catcher Sanofi JSLee_NA12878MOD_final_2.vcf.gz 11 11 11 11 1 5 50 0.984611 0.959802 0.972048 0.753181 0.825319 0.787602\nJoon Sang Lee Sanofi JSLee_NA12878MOD_final_3.vcf.gz 10 10 8 9 1 5 43 0.99641 0.945757 0.970423 0.913897 0.728298 0.810609\nJoon Sang Lee Sanofi JSLee_NA12878MOD_final_4.vcf.gz 0 0 0 0 0 5 5 0.998844 0.921197 0.95845 1 0.000106 0.000213\nThe second table provides detailed variant detection information for each of the 50 injected variants from all qualified submissions. This table also specifies all injected variants with their expected VAF. In this table, VAF is displayed if the variant is present in submitted VCF for a specific entry and the VAF information was derived from the VCF file (i.e. VAF, AD/DP, or AB meta tag was available in the VCF file). For variants which were present in the VCF file, but failed to pass the filtering criteria (as defined by the filter meta tag), the variant is annotated as “filtered” with its associated VAF. Participant entries that supplied VAF data in accordance with the challenge instructions, and that detected all 50 variants reasonably close to the expected VAF values, are being recognized as Warm Up in silico VAF Spotters, indicated by the VAF Spotter icon in the table below (37 entries earned this title). These recognitions are based on the information found in raw VCF data for each entry, regardless of whether the submitter called each of the variants as above 20%. This is due to various reasons, including quality filters set for the pipeline.\ntrue vaf: 0.45\ntarget vaf: 0.50\ntrue vaf: 0.20\ntarget vaf: 0.20\ntrue vaf: 0.47\ntrue vaf: 0.43\ntrue vaf: 0.24\ntrue vaf: 0.42\ntrue vaf: 0.22\ntrue vaf: 0.44\ntrue vaf: 0.18\ntrue vaf: 0.17\ntrue vaf: 0.15\ntrue vaf: 0.48\ntrue vaf: 0.50\ntrue vaf: 0.14\ntrue vaf: 0.13\ntrue vaf: 0.21\ntrue vaf: 0.54\ntrue vaf: 0.33\ntrue vaf: 0.16\ntrue vaf: 0.36\ntrue vaf: 0.40\ntrue vaf: 0.41\ntrue vaf: 0.26\ntrue vaf: 0.12\ntrue vaf: 0.53\ntrue vaf: 0.19\ntrue vaf: 0.51\ntrue vaf: 0.46\ntrue vaf: 0.55\ntrue vaf: 0.52\ntrue vaf: 0.57\nSKESA_SRPRISM Not Found Not Found 1 1 0.98 0.98 1 1 Not Found Not Found 1 Not Found 1 1 Not Found Not Found Not Found Not Found 1 Not Found 0.95 Not Found 1 1 Not Found 1 Not Found 0.98 Not Found 1 Not Found Not Found Not Found 1 1 1 Not Found 1 1 1 1 Not Found Not Found 1 1 0.98 Not Found Not Found 0.98 1\nB15GATK36 VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.44 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.58\nB8GATK36 VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.44 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.58\nSaphetor4 VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.39 0.21 0.18 0.43 0.13 0.51 0.5 0.14 0.15 0.14 0.17 0.21 0.22 0.54 0.36 0.25 0.37 0.2 0.34 0.44 0.41 0.17 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.48 0.52 0.14 0.39 0.44 0.44 0.51 0.43 0.47 0.52\nBIG_CelerSNP-NA12878.vcf Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available\nBIG_HXG-NA12878.vcf.gz Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Found Not Available Not Available Not Available Not Available Not Found Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Found Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available\nBIG_myPipeline-NA12878.vcf.gz Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available\nBIG_NGSToolkit-NA12878.vcf Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available Not Available\nDeepVariant_LowFrequency 0.48 0.25 0.49 0.44 0.29 (Filtered) 0.45 0.23 0.4 0.2 0.2 0.44 0.16 0.53 0.52 0.2 0.15 0.13 (Filtered) 0.18 0.18 0.21 0.53 0.4 0.27 0.35 0.15 (Filtered) 0.36 0.49 0.42 0.21 0.27 0.21 0.19 (Filtered) 0.38 0.25 0.24 0.48 0.16 (Filtered) 0.49 0.23 0.23 0.54 0.5 0.17 0.46 0.5 0.59 0.51 0.43 0.47 0.57\nDeepVariant 0.48 0.25 (Filtered) 0.49 0.44 0.29 (Filtered) 0.45 0.23 0.4 0.2 0.2 0.44 0.16 (Filtered) 0.53 0.52 0.2 0.15 0.13 (Filtered) 0.18 0.18 0.21 0.53 0.4 0.27 0.35 0.15 (Filtered) 0.36 0.49 0.42 0.21 0.27 0.21 0.19 (Filtered) 0.38 0.25 0.24 0.48 0.16 (Filtered) 0.49 0.23 0.23 0.54 0.5 0.17 (Filtered) 0.46 0.5 0.59 0.51 0.43 0.47 0.57\nDRAGEN_DNASeq_NA12878MOD_submission1 VAF Spotter 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nDRAGEN_DNASeq_NA12878MOD_submission2 VAF Spotter 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nDRAGEN_DNASeq_NA12878MOD_submission3 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 Not Found 0.51 0.43 0.47 0.54\nDRAGEN_DNASeq_NA12878MOD_submission4 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 Not Found 0.51 0.43 0.47 0.54\nDRAGEN_DNASeq_NA12878MOD_submission5 VAF Spotter 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nDRAGEN_DNASeq_NA12878MOD_submission6 VAF Spotter 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nDRAGEN_DNASeq_NA12878MOD_submission7b VAF Spotter 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nSaphetor1 VAF Spotter 0.47 0.23 0.46 0.47 0.27 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.2 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nSaphetor2 VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nSaphetor3 VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nMySubmission2 0.47 0.24 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.53 0.39 0.25 0.37 0.2 0.34 0.45 0.44 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 Not Found 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nExperimental Unfiltered 0.48 0.22 0.45 0.46 0.26 0.37 0.22 0.4 0.2 0.18 0.43 0.13 0.51 0.51 0.14 0.15 0.13 0.17 0.19 0.21 0.54 0.36 0.25 0.37 0.18 0.33 0.43 0.42 0.18 0.28 Not Found 0.18 0.55 0.21 0.23 0.45 0.13 0.45 0.19 0.24 0.49 0.52 0.14 0.4 0.44 0.44 0.5 0.44 0.47 0.53\nNCH_SUBMISSION2 0.47 0.23 0.45 0.49 0.27 0.36 0.21 0.39 0.21 Not Found 0.41 Not Found 0.52 0.5 Not Found Not Found Not Found Not Found Not Found 0.21 0.54 0.41 0.24 0.39 0.2 0.37 0.46 0.42 Not Found 0.23 Not Found Not Found 0.55 0.22 0.24 0.44 Not Found 0.46 Not Found 0.23 0.5 0.49 Not Found 0.42 0.46 0.57 0.54 0.4 0.46 0.55\nNCH_SUBMISSION1 VAF Spotter 0.47 0.23 0.45 0.49 0.27 0.36 0.21 0.39 0.21 0.16 0.41 0.14 0.52 0.5 0.16 0.15 0.14 0.17 0.19 0.21 0.54 0.41 0.24 0.39 0.2 0.37 0.46 0.42 0.18 0.23 0.13 0.2 0.55 0.22 0.24 0.44 0.14 0.46 0.2 0.23 0.5 0.49 0.14 0.42 0.46 0.57 0.54 0.4 0.46 0.55\nJLack_CCBR_Leidos_StandardPipeline_noFilter 0.48 0.22 0.44 0.46 0.27 0.36 0.24 0.4 0.21 0.17 0.44 0.14 0.5 0.52 0.14 0.14 0.13 0.18 0.21 0.22 0.54 0.38 0.24 0.37 0.16 0.33 0.44 0.43 0.16 0.3 0.14 0.18 0.56 0.22 0.22 0.45 0.13 0.46 0.2 0.24 0.53 0.54 0.14 0.41 0.44 0.39 0.5 0.43 0.47 0.59\nJLack_CCBR_Leidos_StandardPipeline_relaxed 0.48 0.22 0.44 0.46 0.27 0.36 0.24 0.4 0.21 0.17 0.44 0.14 0.5 0.52 0.14 0.14 0.13 0.18 0.21 0.22 0.54 0.38 0.24 0.37 0.16 0.33 0.44 0.43 0.16 0.3 0.14 0.18 0.56 0.22 0.22 0.45 0.13 0.46 0.2 0.24 0.53 0.54 0.14 0.41 0.44 0.39 0.5 0.43 0.47 0.59\nJSLee_NA12878MOD_final_2.vcf.gz VAF Spotter 0.48 0.22 0.46 0.44 0.27 0.37 0.23 0.42 0.21 0.17 0.44 0.15 0.51 0.5 0.16 0.15 0.14 0.16 0.21 0.22 0.54 0.39 0.25 0.38 0.19 0.34 0.44 0.42 0.18 0.28 0.15 0.18 0.57 0.21 0.23 0.45 0.13 0.46 0.2 0.24 0.5 0.49 0.14 0.4 0.46 0.42 0.5 0.42 0.48 0.55\nJSLee_NA12878MOD_final_3.vcf.gz VAF Spotter 0.48 0.22 0.46 0.44 0.27 0.37 0.23 0.42 0.21 0.17 0.44 Not Found 0.51 0.5 0.16 Not Found Not Found 0.16 0.21 0.22 0.54 0.39 0.25 0.38 Not Found 0.34 0.44 0.42 0.18 0.28 Not Found 0.18 0.57 0.21 0.23 0.45 Not Found 0.46 0.2 0.24 0.5 0.49 Not Found 0.4 0.46 0.42 0.5 0.42 0.48 0.55\nJSLee_NA12878MOD_final_4.vcf.gz VAF Spotter 0.48 Not Found Not Found 0.44 Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found 0.49 Not Found Not Found Not Found Not Found 0.5 0.42 Not Found Not Found\nKCCG_1.7.0_HC VAF Spotter 0.48 0.23 0.45 0.47 0.27 0.37 0.23 0.41 0.21 0.17 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.38 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.56 0.21 0.23 0.44 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.42 0.47 0.58\nKCCG_1.7.0_VD 0.48 0.23 0.48 0.44 0.24 0.42 0.23 0.4 0.22 0.17 0.43 0.17 0.52 0.47 0.19 0.15 Not Found 0.18 0.21 0.21 0.53 0.41 0.25 0.38 0.19 0.36 0.44 0.42 0.18 0.27 Not Found 0.19 0.55 0.23 0.23 0.44 Not Found 0.45 0.21 0.23 0.5 0.49 0.15 0.42 0.49 0.3 0.51 0.42 0.47 0.56\nBowtie2 + GATK HaplotypeCaller depth-filtered 0.47 0.24 0.45 0.46 0.27 0.37 0.23 0.41 0.21 0.18 0.43 0.15 0.51 0.5 0.15 0.15 0.14 0.18 0.2 0.19 0.54 0.39 0.25 0.36 0.2 0.34 0.45 0.34 0.18 0.28 0.15 0.19 0.42 0.22 0.23 0.45 0.13 0.46 0.2 0.24 0.5 0.52 Not Found 0.41 0.45 0.44 0.51 0.43 0.46 0.54\nBowtie2 + GATK HaplotypeCaller unfiltered 0.47 0.24 0.45 0.46 0.27 0.37 0.23 0.41 0.21 0.18 0.43 0.15 0.51 0.5 0.15 0.15 0.14 0.18 0.2 0.19 0.54 0.39 0.25 0.36 0.2 0.34 0.45 0.34 0.18 0.28 0.15 0.19 0.42 0.22 0.23 0.45 0.13 0.46 0.2 0.24 0.5 0.52 Not Found 0.41 0.45 0.44 0.51 0.43 0.46 0.54\nChallenge_submission_20170912_3 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 Not Found 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nGATK HaplotypeCaller depth-filtered VAF Spotter 0.47 0.23 0.46 0.46 0.27 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.51 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.19 0.34 0.45 0.41 0.17 0.28 0.15 0.19 0.56 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.5 0.14 0.41 0.45 0.42 0.51 0.44 0.46 0.54\nGATK HaplotypeCaller unfiltered VAF Spotter 0.47 0.23 0.46 0.46 0.27 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.51 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.19 0.34 0.45 0.41 0.17 0.28 0.15 0.19 0.56 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.5 0.14 0.41 0.45 0.42 0.51 0.44 0.46 0.54\nTest VAF Spotter 0.47 0.24 0.45 0.46 0.25 0.37 0.23 0.43 0.2 0.18 0.42 0.14 0.51 0.5 0.15 0.14 0.15 0.18 0.21 0.22 0.55 0.4 0.25 0.35 0.19 0.35 0.42 0.42 0.18 0.27 0.14 0.19 0.56 0.23 0.23 0.45 0.12 0.47 0.19 0.23 0.5 0.51 0.15 0.41 0.45 0.44 0.52 0.42 0.48 0.54\nNA12878MOD.imp.hardfilter.recode.vcf.gz VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nNA12878MOD.imp.v2.recode.vcf.gz VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nNA12878MOD.imp.v3.recode.vcf VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nNA12878MOD.imp.vcf.gz VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nWhole-exome variant calling pipeline results 0.44 Not Found 0.44 0.44 0.22 0.36 Not Found 0.45 Not Found Not Found 0.38 Not Found 0.47 0.47 Not Found Not Found Not Found Not Found Not Found Not Found 0.54 0.42 Not Found 0.33 Not Found 0.35 0.36 0.4 Not Found 0.25 Not Found Not Found Not Found Not Found 0.22 0.42 Not Found 0.47 Not Found Not Found 0.5 0.46 Not Found 0.38 0.44 0.33 0.52 0.41 0.46 0.53\nADIscan_NA12878MOD_all 0.44 0.18 0.4 0.46 0.22 0.42 0.21 0.45 0.16 Not Found 0.4 0.12 0.46 0.44 0.15 0.14 0.13 0.17 0.16 0.19 0.54 0.42 0.22 0.3 0.14 0.35 0.39 0.41 0.13 0.25 0.12 0.17 Not Found 0.21 0.21 0.4 0.1 0.48 0.19 0.2 0.47 0.48 0.12 0.37 0.45 0.29 0.51 0.4 0.44 0.55\nADIscan_NA12878MOD_conf 0.44 0.18 0.4 0.46 0.22 0.42 0.21 0.45 0.16 Not Found 0.4 0.12 0.46 0.44 0.15 0.14 0.13 0.17 0.16 0.19 0.54 0.42 0.22 0.3 0.14 0.35 0.39 0.41 0.13 0.25 0.12 0.17 Not Found 0.21 0.21 0.4 0.1 0.48 0.19 0.2 0.47 0.48 0.12 0.37 0.45 0.29 0.51 0.4 0.44 0.55\nADIscan_NA12878MOD_filtered 0.44 0.18 0.4 0.46 0.22 0.42 0.21 0.45 0.16 Not Found 0.4 0.12 0.46 0.44 0.15 0.14 0.13 0.17 0.16 0.19 0.54 0.42 0.22 0.3 0.14 0.35 0.39 0.41 0.13 0.25 0.12 0.17 Not Found 0.21 0.21 0.4 0.1 0.48 0.19 0.2 0.47 0.48 0.12 0.37 0.45 0.29 0.51 0.4 0.44 0.55\nADIscan_NA12878MOD_tight 0.44 0.18 0.4 0.46 0.22 0.42 0.21 0.45 0.16 Not Found 0.4 0.12 0.46 0.44 0.15 0.14 0.13 0.17 0.16 0.19 0.54 0.42 0.22 0.3 0.14 0.35 0.39 0.41 0.13 0.25 0.12 0.17 Not Found 0.21 0.21 0.4 0.1 0.48 0.19 0.2 0.47 0.48 0.12 0.37 0.45 0.29 0.51 0.4 0.44 0.55\nHULP-germ 0.46 0.22 0.24 0.47 0.24 0.2 0.23 0.21 0.18 0.16 0.2 0.14 0.26 0.23 0.16 0.14 0.14 0.16 0.19 0.2 0.27 0.21 0.23 0.17 0.18 0.17 0.2 0.14 0.16 0.28 0.12 0.18 Not Found 0.19 0.22 0.22 0.11 0.23 0.17 0.22 0.25 0.5 Not Found 0.18 0.24 0.25 0.52 0.44 0.23 0.28\nSubmission1 0.47 0.24 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.53 0.39 0.25 0.37 0.2 0.34 0.45 0.44 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 Not Found 0.41 0.45 0.44 0.51 0.43 0.47 0.53\nSeqsLab with GATK-based Parallelization 0.47 0.24 0.45 0.47 0.26 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 Not Found 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nSeqsLab with GATK-based Parallelization(conf>30) 0.47 0.24 0.45 0.47 0.26 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 Not Found 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nNCBI_Magic_ThierryMieg_NA12878MOD.b.vcf.gz 0.49 Not Found 0.47 0.44 (Filtered) 0.24 (Filtered) 0.47 0.22 (Filtered) Not Found Not Found 0.2 Not Found Not Found 0.45 0.44 Not Found Not Found Not Found Not Found Not Found Not Found 0.57 Not Found 0.22 Not Found Not Found 0.38 Not Found 0.42 Not Found 0.25 Not Found Not Found Not Found 0.21 0.26 0.45 Not Found Not Found 0.21 Not Found 0.54 0.5 Not Found Not Found Not Found 0.26 0.54 0.45 Not Found 0.59\nBWA-MEM + GATK + SNVer 0.47 0.17 0.29 0.43 0.2 0.29 0.19 0.29 0.16 Not Found 0.3 Not Found 0.34 0.32 Not Found 0.13 Not Found Not Found 0.17 Not Found 0.35 0.27 0.19 0.22 Not Found 0.24 0.28 0.29 Not Found 0.21 Not Found 0.17 Not Found 0.18 0.19 0.3 Not Found 0.32 0.17 0.18 0.32 0.53 Not Found 0.27 0.3 0.24 0.48 0.43 0.32 0.33\nNovoalignFreebayes_1 0.47 0.24 0.44 0.44 0.24 0.45 0.23 0.41 0.21 0.2 0.42 Not Found 0.52 0.49 0.2 0.14 Not Found 0.17 0.17 0.21 0.51 0.39 0.24 0.33 0.15 0.34 0.46 0.39 0.18 0.25 0.16 0.19 0.4 0.24 0.22 0.43 Not Found 0.46 0.24 0.22 0.52 0.49 0.15 0.4 0.47 0.38 0.5 0.39 0.47 0.58\nNovoalignFreebayes_2 0.45 0.16 0.41 0.41 0.21 0.39 0.2 0.36 0.17 0.18 0.38 Not Found 0.48 0.45 0.19 0.13 Not Found 0.14 Not Found 0.18 0.48 0.34 0.21 0.3 0.14 0.29 0.45 0.35 Not Found 0.23 Not Found 0.13 0.22 0.16 0.18 0.38 Not Found 0.42 0.2 0.21 0.46 0.47 Not Found 0.32 0.42 0.41 0.49 0.37 0.43 0.54\nNovoalignGATKHC_1 VAF Spotter 0.47 0.24 0.45 0.47 0.27 0.36 0.23 0.4 0.21 0.17 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.22 0.21 0.54 0.39 0.25 0.39 0.19 0.34 0.44 0.42 0.18 0.28 0.15 0.19 0.57 0.21 0.23 0.46 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.4 0.45 0.42 0.51 0.42 0.47 0.54\nNovoalignGATKHC_2 VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.36 0.23 0.4 0.21 0.17 0.42 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.22 0.21 0.54 0.39 0.25 0.38 0.19 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.56 0.21 0.23 0.45 0.13 0.45 0.19 0.24 0.5 0.52 0.14 0.39 0.45 0.42 0.51 0.42 0.47 0.54\nSentieon_DNAseq_allmap_nodedup-NA12878MOD 0.45 0.21 0.42 0.46 0.24 0.36 0.21 0.45 0.17 0.16 0.41 0.11 0.48 0.49 0.14 0.14 0.14 0.17 0.18 0.2 0.54 0.42 0.22 0.33 0.17 0.34 0.39 0.42 0.16 0.26 0.12 0.17 0.53 0.2 0.22 0.43 0.11 0.48 0.17 0.21 0.47 0.48 0.14 0.39 0.43 0.41 0.52 0.41 0.45 0.54\nSentieon_DNAseq_allmap-NA12878MOD VAF Spotter 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.41 0.2 0.18 0.44 0.12 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.36 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.53 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.49 0.53 0.14 0.4 0.44 0.44 0.51 0.43 0.47 0.54\nSentieon_DNAseq_nodecoy-NA12878MOD VAF Spotter 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nSentieon_DNAseq_std-NA12878MOD VAF Spotter 0.47 0.23 0.45 0.47 0.26 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 0.14 0.41 0.45 0.44 0.51 0.43 0.47 0.54\nSentieon_Exp_nodedup-NA12878MOD 0.45 0.21 0.44 0.46 0.25 0.36 0.22 0.46 0.18 0.17 0.43 0.13 0.48 0.49 0.16 0.14 0.14 0.17 0.19 0.21 0.6 0.42 0.23 0.36 0.16 0.36 0.39 0.44 0.17 0.26 0.12 0.17 0.54 0.21 0.22 0.44 0.12 0.48 0.17 0.22 0.51 0.48 0.14 0.41 0.44 0.41 0.55 0.44 0.47 0.55\nSentieon_Exp-NA12878MOD VAF Spotter 0.48 0.24 0.45 0.48 0.27 0.37 0.23 0.42 0.22 0.18 0.47 0.14 0.51 0.52 0.16 0.15 0.15 0.18 0.21 0.21 0.57 0.39 0.26 0.39 0.18 0.35 0.45 0.45 0.2 0.28 0.15 0.19 0.52 0.22 0.23 0.47 0.13 0.46 0.2 0.24 0.52 0.53 0.14 0.42 0.45 0.44 0.55 0.46 0.49 0.55\nSentieon_TNscope_Tonly_allmap_nodedup-NA12878MOD 0.45 0.21 0.44 0.46 0.25 0.36 0.22 0.46 0.18 0.17 0.43 0.13 0.48 0.49 0.16 0.14 0.14 0.17 0.19 0.21 0.6 0.42 0.23 0.36 0.16 0.36 0.39 0.44 0.17 0.26 0.12 0.17 0.54 0.21 0.22 0.44 0.12 0.48 0.17 0.22 0.51 0.48 0.14 0.41 0.44 0.41 0.55 0.44 0.47 0.55\nSentieon_TNscope_Tonly_allmap-NA12878MOD VAF Spotter 0.48 0.24 0.45 0.48 0.27 0.37 0.23 0.42 0.22 0.18 0.47 0.14 0.51 0.52 0.16 0.15 0.15 0.18 0.21 0.21 0.57 0.39 0.26 0.39 0.18 0.35 0.45 0.45 0.2 0.28 0.15 0.19 0.52 0.22 0.23 0.47 0.13 0.46 0.2 0.24 0.52 0.53 0.14 0.42 0.45 0.44 0.55 0.46 0.49 0.55\nSentieon_TNscope_Tonly_nodecoy-NA12878MOD VAF Spotter 0.48 0.24 0.45 0.48 0.28 0.37 0.23 0.42 0.22 0.18 0.46 0.15 0.52 0.52 0.16 0.15 0.15 0.18 0.21 0.21 0.57 0.4 0.26 0.38 0.18 0.35 0.44 0.45 0.2 0.28 0.15 0.19 0.54 0.22 0.23 0.47 0.13 0.47 0.2 0.24 0.53 0.53 0.15 0.42 0.46 0.44 0.55 0.46 0.49 0.55\nSentieon_TNscope_Tonly_std-NA12878MOD VAF Spotter 0.48 0.24 0.45 0.48 0.28 0.37 0.23 0.42 0.22 0.18 0.46 0.15 0.52 0.52 0.16 0.15 0.15 0.18 0.21 0.21 0.57 0.4 0.26 0.38 0.18 0.35 0.44 0.45 0.2 0.28 0.15 0.19 0.54 0.22 0.23 0.47 0.13 0.47 0.2 0.24 0.53 0.53 0.15 0.42 0.46 0.44 0.55 0.46 0.49 0.55\nSGI_1st_result VAF Spotter 0.47 (Filtered) 0.23 0.46 (Filtered) 0.47 0.26 (Filtered) 0.37 0.23 (Filtered) 0.41 0.21 (Filtered) 0.18 (Filtered) 0.43 0.14 (Filtered) 0.51 (Filtered) 0.5 0.15 (Filtered) 0.15 (Filtered) 0.14 (Filtered) 0.18 0.21 (Filtered) 0.21 0.54 0.39 0.25 (Filtered) 0.37 0.2 (Filtered) 0.34 (Filtered) 0.44 0.42 0.18 (Filtered) 0.28 (Filtered) 0.15 0.19 (Filtered) 0.58 (Filtered) 0.21 (Filtered) 0.23 (Filtered) 0.45 0.13 (Filtered) 0.46 0.19 (Filtered) 0.24 0.5 0.52 0.14 (Filtered) 0.41 0.45 (Filtered) 0.44 (Filtered) 0.51 0.43 0.47 0.54\nSGI_2nd_filtration VAF Spotter 0.47 0.23 0.46 0.47 0.26 (Filtered) 0.37 0.23 (Filtered) 0.41 0.21 0.18 (Filtered) 0.43 0.14 (Filtered) 0.51 (Filtered) 0.5 0.15 (Filtered) 0.15 (Filtered) 0.14 (Filtered) 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 (Filtered) 0.34 0.44 0.42 0.17 (Filtered) 0.28 0.15 0.2 (Filtered) 0.58 (Filtered) 0.21 0.23 (Filtered) 0.45 0.13 (Filtered) 0.46 0.19 (Filtered) 0.24 0.5 0.52 0.14 (Filtered) 0.41 0.45 0.44 (Filtered) 0.51 0.43 0.47 0.54\nSGI_4th_filtration VAF Spotter 0.47 0.23 (Filtered) 0.46 0.47 0.26 0.37 0.23 0.41 0.2 0.18 0.43 0.14 0.51 (Filtered) 0.52 (Filtered) 0.15 (Filtered) 0.15 0.14 0.18 0.21 0.21 0.53 0.38 0.24 0.38 (Filtered) 0.18 0.34 0.43 0.42 0.17 0.26 0.15 (Filtered) 0.17 0.58 0.2 (Filtered) 0.23 0.45 0.11 0.46 0.2 0.24 0.49 0.53 0.14 0.41 0.45 0.43 (Filtered) 0.49 0.43 0.47 0.59\nSGI_3rd_filtration_rere 0.47 0.23 (Filtered) Not Available 0.47 Not Available Not Available Not Available Not Available 0.21 0.18 (Filtered) Not Available 0.14 (Filtered) Not Available Not Available 0.15 (Filtered) 0.15 (Filtered) 0.14 (Filtered) 0.18 0.21 0.21 Not Available Not Available Not Available Not Available 0.2 (Filtered) Not Available 0.44 Not Available 0.17 (Filtered) Not Available 0.15 (Filtered) 0.2 (Filtered) 0.58 (Filtered) Not Available Not Available Not Available 0.13 (Filtered) Not Available Not Available Not Available Not Available 0.52 0.14 (Filtered) Not Available Not Available 0.44 (Filtered) 0.51 0.43 Not Available 0.54\nSIB 0.45 0.2 0.42 0.44 0.22 0.41 0.23 0.39 0.19 0.18 0.42 Not Found 0.47 0.45 0.18 Not Found Not Found 0.82 Not Found 0.2 0.48 0.4 0.2 0.29 Not Found 0.34 0.4 0.36 0.17 0.26 Not Found Not Found 0.69 0.22 0.24 0.39 Not Found 0.45 0.2 0.21 0.48 0.49 0.2 0.33 0.45 0.23 0.53 0.44 0.44 0.51\nMySubmission1 0.47 0.24 0.45 0.47 0.26 0.37 0.23 0.4 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.53 0.39 0.25 0.37 0.2 0.34 0.45 0.44 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.45 0.13 0.46 0.19 0.24 0.5 0.52 Not Available 0.41 0.45 0.44 0.51 0.43 0.47 0.53\nmySubmission_GATK 0.47 0.23 (Filtered) 0.45 0.47 0.26 0.37 0.23 0.41 0.2 0.18 0.44 0.14 0.51 (Filtered) 0.52 (Filtered) 0.15 0.15 0.14 0.18 0.21 0.21 0.53 0.38 0.24 0.38 0.18 0.34 0.45 0.43 0.18 0.26 0.15 (Filtered) 0.16 0.58 0.2 0.23 0.45 0.12 0.47 0.2 0.24 0.49 0.51 0.07 0.41 0.45 Not Found 0.49 0.43 0.47 0.28\nYotta1_GRCh37_liftover_from_GRCh38_sorted VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 (Filtered) 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.44 0.13 0.46 0.19 0.24 0.5 0.52 0.14 (Filtered) 0.41 0.45 0.44 0.51 0.43 0.57 0.58\nYotta2_GRCh37_liftover_from_GRCh38_sorted 0.45 Not Found Not Found 0.44 Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found Not Found 0.46 Not Found Not Found Not Found Not Found 0.52 0.42 Not Found Not Found\nYotta3_GRCh37_liftover_from_GRCh38_sorted VAF Spotter 0.47 0.23 0.45 0.47 0.27 0.37 0.23 0.41 0.21 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.21 0.21 0.54 0.39 0.25 0.37 0.2 0.34 0.45 0.42 (Filtered) 0.18 0.28 0.15 0.19 0.55 0.21 0.23 0.44 0.13 0.46 0.19 0.24 0.5 0.52 0.14 (Filtered) 0.41 0.45 0.44 0.51 0.43 0.57 0.58\nG3GATK36 0.47 0.23 0.45 0.46 0.27 0.36 0.23 0.4 0.2 0.18 0.43 0.14 0.51 0.5 0.15 0.15 0.14 0.18 0.22 0.21 0.53 0.39 0.25 0.37 0.2 0.34 0.44 0.42 0.18 0.28 0.15 0.2 0.29 0.21 0.23 0.44 0.13 0.46 0.19 0.24 0.5 0.51 0.13 0.41 0.45 0.44 0.51 0.44 0.47 0.58\nHULP-mosaic 0.44 0.18 0.38 0.44 (Filtered) Not Found 0.35 0.22 0.39 0.16 0.18 (Filtered) 0.35 Not Found 0.5 0.43 0.17 0.14 Not Found 0.13 (Filtered) Not Found 0.17 (Filtered) 0.55 0.37 0.19 0.26 0.12 0.29 0.31 0.38 0.14 0.24 0.1 (Filtered) 0.16 Not Found 0.18 0.21 0.36 0.11 (Filtered) 0.44 0.15 0.2 0.42 (Filtered) 0.48 Not Found 0.3 (Filtered) 0.38 0.35 0.49 0.4 (Filtered) 0.45 0.47


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za ed2d c06 ha ndf1 i38 e124 82f oea5 bf4f oe w63 ia54 ą83 z33 u735 j20e ą675 c90 y5 c7c6 h4 ed p1 r863 z9 e5d p4 ie s5 ó6a w17 733 p1 r5 a6 wd9 a7aa .3\nd27 S3 ta r33 oe n2f a1 9 p6c rd ec8 zcc e999 n014 t02 uab3 j14 e1 c33 de a61e na53 e01 33d w7b9 p93 r3a oa w46 af30 d5b z5 oa8 nb e36 0 pc3 r3c z1 e67 z49a fd z079 a4a r483 ead jdb5 e380 s2 td r885 o5 w2cc ac18 nc y7d0 c986 h0 0 ud ż59 y738 t4 k2c o6b w16d n130 i6cf k6 ófe7 wa c0 sb62 e5 r7f w45 ib s64 ufa4 909 db o517 d0 a0 wd a8 r9 k1 acb3 .8 i7 4a24 a203 .9 pfd l388 3 z28b g567 o76 d7 n66c i3 ed b7c ze cfa jf6d ef1b j62e 7 r25 e5f7 gd u65 l9bb a6f m74e i02 n8 e0 m68 e i61 ad p28d o6df lb i17 t374 ydb1 k247 ąbd5 8 p8 r8 y16 w9e af tc5d nc7 o04a śbc cf98 i06 .69\nd D4f a6a n3eb e7 d od10 sc ob bd1 o6 we8 e00 398 sbc ą9fe 8 pf2 r5bd ec16 z9 ee1 n74 tdb o7 w305 ace nb6 ee 1 i1ac c5 p0 rf07 z02 e51b c3ab hdc4 oe web1 ye wed1 a0 n1fd eb5f 3d n10a a109 7f9 t1 e4ad j1 711 sc2c t1 r8cc oc3 n30 i8 e5f 2 d2c o1 f mb o3fe m2 ec8 ndb2 tf3f u3 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t6f ob07 mdc7 3 (3 p0 o8 z1a1 a6 0c5 f40 i5 re m42 ąe25 a śba wa2 ia3a a4be d20d c7bb za5 ą0 c8 ąf6b 1f ue1 s171 ł585 u4fa gb2d i6c0 7b s6cf e3 r6c4 wdf8 ee r67 o5 w7 e606 ,2 06 z70 4f k6 tcd ó854 re ąd57 4ba acf6 d15 m340 ib nb0 i6 sa t9 rc5 a91a t6 of4 r6fb 3 d8 a96 nf yd c2 h9b7 f pf1c oc6b de ped if sb ae7 łbc4 e1 uf3 m75 o6 wb ę9 4 p926 o37 w11d i44 e6 re z3 e87 n0 i5 a5 0 db a763 n3 y809 c2d h15 )9c3 .1 96 N9 af64 lf e6e ż4 ydd a18 m0b i311 e06 ćec0 eb r5ae ó2 w8dc n39 ia2b e6dc ż3a 07 n2 a14 ce u75 w8d ab46 d728 z4a3 ec1 61a c0d h971 ac9 r87 ab k482 t19 ea6 r750 b seb t30b r9 ob n4 ya a i5 nd t3 ea r786 nfe e07 tea od3 w04 ea j46 cc (1fd pb9 r3 e9e z302 ecbc nde t2 o21e w2a a869 n416 i432 e5 b66 o457 g1be łb7 o0 s58 z13 e45d ń2 7c wb sbb z74 y527 sbc tefa k14 i15 m9d e9 o9e4 dc4 w3d8 if6 e3b da z101 ab1 jcb ąe3 c11f y4 m0 3 s2 t6a rec offa n4b ęa7 )7 .7\ne8 D26e a5b n52 ee92 9f7 ob60 sde o6 b73 o7 w1b e24d a0 j6e ac92 kff i2 e5 0 m7ce o53 g14 ą798 c4e b9f5 y95 ćb c aa ddf m5 if 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c4 i7e7 e8aa l2a5 1df d22 a61a n3 y705 cba hc92 e6 o5f se52 oabd bb2 odb wf y3 c74e h6bc 42 j5 e7 śb9 l597 ic4 734 ud3 zb9b n9 abb ,9e aed ż345 e6 8c0 p27 r79 zb71 e05 t0e6 wc ad5 rd zfc af60 m8 y8 b dab7 af8f n0 e1 3 n0 i3d e52d z6cc g90 o7 d909 nb5 i4 e245 2b7 zd 30 p08 rb3 z3 e7 p4 i59 scac a4dc m712 idf8 fb7 md8 a6e1 9a p7 re1 aa w3 oa9f 2be we92 ne88 i81d e91c s2f9 ibd2 eed nf i5b a5e2 9 sb76 k8b a4b r1e4 g4 ib8e e8 d5 o47 a Pff r72 e0b8 z26 eff9 sc35 a2f 7 U253 r5 z4 ęe3 d4de u009 f O1e cd h93 r0 oe22 n3 y0 2d D85 a0 n69 ye1b c83 hfd ee Oab8 sa o5da b71e ob w26 ya cb1e h8 .129\n3 U0 ż480 y4af wede aa na i55 e3 29 ca i6 a5 s0d t6e6 e5 c073 z36f e1 k13 dd jdc e63b sa48 t778 f50 o38b g63 r87 ac4 ne ia3 c05c zbd o2a n58 ee2c 19 d8b o9a 6 zc0 aa8 pcf ia s9 ae3 n2 i49 aa2 db3 ic df6 e sd e4db sfc6 j369 i57 b nc af43 40 sb73 e6 ra6 w0f ef0 r61 ze67 e769 b2 od80 rb a1c z1f8 f d20 odf5 3a3 z114 a38 pe2 i9 s261 a6b n9 ic a4 20 zfd7 d7a a0 r0 z47e ec63 n0 i16f a19 58 ode 1 z5f9 a46 a706 k7c3 c0 e02 p43 t7dc o6 w4f2 a93 n2 ib3 u1 eea ia n4fe f5 o823 r147 mf2f ae0c c28c j2 i1d c52 od 9 u43b ż6e y3 wa ad n4 i4d u2c 251 c588 i73f a51e s13 t1cf ec cdc z59 e38a k22 .54\nKontakt: 3 s4 e25 o5b1 s89 oc0e l98a u09 t5 ifb ode n21a s54 @c70 i52 42 ad .4 p5 l


Vaillant Kondensator 0020273861 | Loebbeshop Heizung und Ersatzteile\nVaillant Kondensator VWL 37/5\nEAN / GTIN 4024074848906\nBeschreibungVaillant Kondensator für VWL 37/5, u.w. - Vaillant Ersatzteil 0020273861\nVaillant Kondensator für VWL 37/5, u.w. - Vaillant Ersatzteil 0020273861


Bonsoir a l'honneur : " Le Pont des Espions " - THONYstreamHD\nBonsoir a l'honneur : " Le Pont des Espions "\nPar THONYstreamHD. dans Les Notes des Films HD le 17 Mars 2016 à 16:06\nActeurs Stars : Tom Hanks - Mark Rylance - Scott Shepherd\nNote spectateur : 7.5/10 - (135 505)\nSteven Spielberg revient après "Lincoln" en compagnie des frères Coen pour l'écriture de son film 'Le Pont Des Espions", et quel est le résultat? Eh bien un film plutôt réussi grâce à son casting de premier choix (Tom Hanks excellent,impeccable en homme de loi et touchant en père de famille, en patriote et en tant qu’être humain fidèle à ses principes.) et sa réalisation certes classique mais efficace. Mais il y a néanmoins un problème: les longueurs. Car en effet le film est parfois long sur certaines scènes (Beaucoup de dialogues). On retrouve la patte des frères Coen dans certains dialogues. L'absence de musique est néanmoins problématique quant au rythme du film. "Le Pont Des Espions"reste un film simple certes mais plutôt efficace en dépit d'un certain manque de rythme.\nEntre le film d'espionnage et de droit, Steven Spielberg livre une critique légère sur le patriotisme pendant la guerre froide.\nBande Annonce : " Le Pont des Espions " (VF/HD : 1080p)


Проверка авто VOLKSWAGEN TOUAREG. Госномер О545УХ163. VIN WVGZZZ7LZ8D030532.\nОтчет по VIN номеру: WVGZZZ7LZ8D030532\nНомер ЕАИСТО: 008630031908758\nНомер двигателя: 015190\nНомер ПТС: 77ТУ312262\nНомер договора ОСАГО: 3011911003\nНомер уведомления о возникновении залога: 2019-004-011114-241\nИмущество: VIN: WVGZZZ7LZ8D030532\nЗалогодатель: Владимир Юрьевич Гвардис (1969-04-30)\nVIN НОМЕР: WVGZZZ7LZ8D030532


The Pushcart Prize XXIX - Bill Henderson - kirja(9781888889390) | Adlibris kirjakauppa\nAn annual collection of more than sixty of the prior year's top selected short stories, essays, and poems as published in literary magazines and small presses is complemented by an index to the series and a listing of hundreds of outstanding presses and authors. Simultaneous.\nKirjailija: Bill Henderson\nAlaotsikko: Best Of The Small Presses, 2005 Edition\nKustantaja: Pushcart Press\nSarja: PUSHCART PRIZE


Louis I of Bourbon (1530-69) 1st Prince of Conde, Duke of Enghien, Count of Soissons and Marquis of Conti - (studio of) Clouet - WikiGallery.org, the largest gallery in the world Main Page - WikiGallery\nLouis I of Bourbon (1530-69) 1st Prince of Conde, Duke of Enghien, Count of Soissons and Marquis of Conti - (studio of) Clouet - WikiGallery.org, the largest gallery in the world\nEnglish: "Louis I of Bourbon (1530-69) 1st Prince of Conde, Duke of Enghien, Count of Soissons and Marquis of Conti" oil on Canvas, location: Musée Condé, Chantilly, France.\nMadeleine de Crussol (1490-1531), dame de Mitte de Miolans, femme de Louis de Miolans, c.1523 - (studio of) Clouet\nMadeleine de Luxembourg (c.1525-.), wife of Georges de La Tremouille, baron de Royan, c.1563 - (studio of) Clouet\nMadeleine de Mailly (?-1567), wife of Charles de Roye, c.1535 - (studio of) Clouet\nPortrait of M. Roques - Jacques-André-Joseph Aved\nPortrait of Laure Borreau - Gustave Courbet\nPortrait of Mlle. Guillaumin in a kimono, 1901 - Armand Guillaumin


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Lennart Hammarström - PubMed - NCBI\nSearch: Lennart Hammarström\nSelect item 28942850 2.\nSelect item 28916186 3.\nSelect item 28910364 4.\nSelect item 28830549 5.\nSelect item 28512785 8.\nSelect item 28502825 9.\nSelect item 28468886 10.\nSelect item 28011864 13.\nSelect item 27873105 14.\nSelect item 27610615 16.\nSelect item 27609654 17.\nSelect item 27587326 18.\nSelect item 27531803 19.\nLu P, Ling B, Wang N, Hammarstrom L.\nZhongguo Shi Yan Xue Ye Xue Za Zhi. 2016 Aug;24(4):1216-20. doi: 10.7534/j.issn.1009-2137.2016.04.047. Chinese.\nSelect item 27439689 20.\nLennart, Hammarstrom[Full Author Name] OR Hammarstrom, Lennart[Full Author Name] OR Hammarstrom, Lennart[Full Investigator Name]


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Toselli`s Serenade for TRUMPET by Enrico TOSELLI (Paperback) - Lulu\nToselli`s Serenade for TRUMPET\nEnrico Toselli`s Serenade for Bb or C Trumpet & Piano.*** La "Sérénade" d'Enrico Toselli pour Trompette en Sib ou en Ut & Piano.\nToselli serenade Trumpet\nTOSELLI | Serenade |... By Enrico TOSELLI Paperback:


How to spell engouragement correctly? | Spellcheck.net\nCorrect spelling for ENGOURAGEMENT\nWe think the word engouragement is a misspelling. It could be just an incorrect spelling of the words which are suggested below. Review the list and pick the word which you think is the most suitable.\nPossible correct spellings for engouragement\n664 words made from the letters engouragement\n5 letter words made from engouragement:\narmee, etrog, maruo, agong, gotee, gunne, autem, emeer, manen, gunga, gnant, ameer, monga, anguo, euroa, emote, arete, grune, mante, auret, anong, autor, gamer, gauge, genet, engro, atone, gagen, gemen, agene, anger, enten, emanu, mengo, menta, eagre, metan, annur, aegon, gorge, graet, guage, amero, eaten, maner, aegee, gamet, gante, eugoa, garno, enarm, metro, metre, garou, engag, gator, ergot, gogar, gunma, magne, gunge, genug, argon, egger, monet, groma, emert, ganoe, metge, agege, gogan, gaume, agree, ganon, anmen, agere, genre, armet, garut, gruen, guram, great, metor, anter, gauer, getae, gouge, egton, atong, menna, gorum, meger, amour, enuma, aereo, etree, aggro, grant, egert, argue, agung, green, moena, gomar, graue, egret, maeng, argot, grone, geman, mongu, agone, eater, gotan, guang, mogan, emona, manne, menno, genge, meroe, marot, genoa, erugo, guera, guant, genea, ganne, angre, gruma, amron, mogae, goure, gouna, gaunt, meron, guano, gruta, ennog, gnome, eager, gemot, goten, gangu, anner, amuro, enema, marou, gogra, groat, gaung, grage, anung, gunto, magro, amont, guman, ature, menon, enger, grunt, ertan, amrut, goree, gogue, egnot, maung, germe, aegre, groen, aneto, agren, eroge, mango, mangu, merge, ergun, auter, earnt, agoge, gragn, enter, gunnm, aguon, etgar, guter, grate, monan, geert, gonen, enman, gorme, erato, magog, gogat, agent, gonum, angue, guare, etour, grega, grano, garmo, gagne, matou, mager, mateu, augen, ergen, monge, enate, egner, graem, grong, eagon, gerne, mauno, gruet, meran, genga, gorga, gunnr, ertug, eggen, menga, ganor, enero, matru, mannu, meego, amgen, guaro, mogen, amort, gamut, ennea, marut, meren, gegen, graun, mater, agmon, meung, amene, guren, ament, angon, gamon, geant, moeen, guten, autre, anemo, arone, eggar, genon, mantu, getgo, eramo, ergma, moger, atene, agnon, groan, genro, meare, monae, eggan, arute, geton, aurem, arent, grout, merta, emane, erent, menen, meret, mento, etang, meter, getme, monee, entre, maron, ganem, ermua, magon, gerea, gater, magor, goner, atune, mange, auger, garet, menne, grean, gener, meane, marge, maton, gantu, merga, gatun, eorum, antum, eamer, mauer, magno, manor, gente, annum, emure, guero, ameet, manet, gonne, guran, gotra, marun, greet, meton, genma, agner, enone, etage, egnor, manou, geter, goram, annee, argun.\n4 letter words made from engouragement:\natgm, munt, mate, metn, ngee, gong, near, geom, ngum, nuta, ergo, gaun, monn, eoan, game, grau, eang, neum, auro, etau, meat, meet, eteo, gtmo, ento, guge, noua, nona, mere, more, gran, geto, gear, maon, goat, goer, gute, eeto, atom, muon, naur, nato, neue, atun, nenu, guar, moen, grog, amon, geta, ngau, grue, numt, grut, mane, maru, guto, menu, gnat, meta, gang, geum, egen, etre, mogu, ague, gnau, gonn, mrna, muan, nogg, maen, nune, aero, egge, mote, moua, noen, nrem, noun, muge, neem, naor, agur, aeon, ggmo, moer, gent, name, mugg, gate, moat, garu, gaut, earn, guro, gonu, euro, ngom, note, mung, ante, eter, mtge, amur, gegr, erne, auer, gura, nuno, mare, etna, mart, maun, noma, matn, munn, ganu, nung, mene, naum, nega, agno, murt, aunt, gone, gmoa, gure, gort, neat, meen, gamu, nuon, nuna, amor, gnrn, meno, muen, mago, nuer, goga, murn, gorn, nonu, egna, atum, nano, ngon, nero, gout, eega, meou, mann, gore, genu, geun, magu, grot, megu, arum, murg, gage, guen, gona, nemr, muto, negm, ngae, noer, aoun, meon, monu, areo, nong, norn, nome, moue, mona, ngog, moan, gato, arno, none, gene, amen, guan, guta, argo, agog, mean, auto, gunt, morn, gurg, guam, nout, germ, gaur, gung, gaen, norm, eure, gram, nrna, anem, nego, mogg, mute, gagn, neon, mugo, narn, gget, nget, enur, gean, muar, gaon, muro, guma, goan, gega.\n3 letter words made from engouragement:\nmag, rem, ene, are, gem, net, gag, run, nne, rot, tar, gun, oar, ter, nag, rna, tog, nog, ute, nan, tug, uta, art, tor, egg, neo, eon, rag, atm, tag, oat, mar, emg, tea, ton, eeg, gen, ngu, anu, tao, nmr, rut, tam, tan, mao, mat, out, uma, teg, ten, urn, mon, moa, ear, gnu, rug, ago, tau, ore, gat, rom, gur, mut, rat, trm, ego, tum, ent, gee, gut, roe, man, aug, gum, ram, rum, ron, meg, tom, arm, not, ate, tun, nee, gmt, eta, toe, emu, ane, nut, gar, rue, era, ant, eat, goa, uro, one, tee, nun, ern, mot, ret, ert, erg, age, men, mug, get.


Eligible Models 2020 Gravely USA Compact-Pro 34 in. Kawasaki FX481V 15.5 hp 2020 Gravely USA Compact-Pro 44 in. Kawasaki FX600V 19 hp 2020 Gravely USA Pro-Turn 148 48 in. Kawasaki FX691V 22 hp 2020 Gravely USA Pro-Turn 152 52 in. Kawasaki FX691V 22 hp 2020 Gravely USA Pro-Turn 152 52 in. Kohler EZT725 22 hp 2020 Gravely USA Pro-Turn 152 52 in. Kohler ZT730 23 hp 2020 Gravely USA Pro-Turn 160 60 in. Kawasaki FX730V 23.5 hp 2020 Gravely USA Pro-Turn 160 60 in. Kohler EZT740 25 hp 2020 Gravely USA Pro-Turn 160 60 in. Kohler ZT740 25 hp 2020 Gravely USA Pro-Turn 160 60 in. Yamaha MX800V 26 hp 2020 Gravely USA Pro-Turn 252 52 in. Kawasaki FX850V 27 hp 2020 Gravely USA Pro-Turn 260 60 in. Kawasaki FX850V 27 hp 2020 Gravely USA Pro-Turn 260 60 in. Kohler ECV860 29 hp 2020 Gravely USA Pro-Turn 260 60 in. Kohler ZT740 25 hp 2020 Gravely USA Pro-Turn 260 60 in. Yamaha MX775V 29 hp 2020 Gravely USA Pro-Turn 260 60 in. Yamaha MX825V 27.5 hp 2020 Gravely USA Pro-Turn 272 72 in. Kawasaki FX921V 31 hp 2020 Gravely USA Pro-Turn 452 52 in. Kawasaki FX850V 27 hp 2020 Gravely USA Pro-Turn 452 52 in. Yamaha MX775V EFI 29 hp 2020 Gravely USA Pro-Turn 460 60 in. Kawasaki FX1000V 35 hp 2020 Gravely USA Pro-Turn 460 60 in. Kohler ECV880 33 hp 2020 Gravely USA Pro-Turn 460 60 in. Yamaha MX825V EFI 33 hp 2020 Gravely USA Pro-Turn 472 72 in. Kawasaki FX1000V 35 hp 2020 Gravely USA Pro-Turn 472 72 in. Yamaha MX825V EFI 33 hp 2020 Gravely USA Pro-Turn Mach One 60 in. Kawasaki FX921V 31 hp 2020 Gravely USA Pro-Turn Z 48 in. Gravely 26.5 hp 2020 Gravely USA Pro-Turn Z 52 in. Gravely 764 Pro 26.5 hp 2020 Gravely USA Pro-Turn Z 60 in. Gravely 764 Pro 26.5 hp 2020 Gravely USA Pro-Turn ZX 48 in. Kawasaki FX691V 22 hp 2020 Gravely USA Pro-Turn ZX 52 in. Kawasaki FX691V 22 hp 2020 Gravely USA Pro-Turn ZX 60 in. Kawasaki FX730V 23.5 hp 2020 Gravely USA ZT HD 44 in. Kawasaki FR651 21.5 hp 2020 Gravely USA ZT HD 48 in. Kawasaki FR691 23 hp 2020 Gravely USA ZT HD 48 in. Kohler 7000 Series Pro 25 hp 2020 Gravely USA ZT HD 52 in. Kawasaki FR691 23 hp 2020 Gravely USA ZT HD 52 in. Kohler 7000 Series Pro 25 hp 2020 Gravely USA ZT HD 60 in. Kawasaki FR730 24 hp 2020 Gravely USA ZT HD 60 in. Kohler 7000 Series Pro 26 hp 2020 Gravely USA ZT X 42 in. Kohler 7000 Series Pro 22 hp 2020 Gravely USA ZT X 52 in. Kawasaki FR691 23 hp 2020 Gravely USA ZT X 52 in. Kohler 7000 Series Pro 24 hp 2020 Gravely USA ZT X 60 in. Kawasaki FR691 23 hp 2020 Gravely USA ZT XL 42 in. Kawasaki FR651V 21.5 hp 2020 Gravely USA ZT XL 42 in. Kohler 7000 HD 24 hp 2020 Gravely USA ZT XL 48 in. Kawasaki FR691 23 hp 2020 Gravely USA ZT XL 52 in. Kawasaki FR691 23 hp 2020 Gravely USA ZT XL 52 in. Kohler 7000 HD 25 hp 2020 Gravely USA ZT XL 60 in. Kawasaki FR730 24 hp 2020 Gravely USA ZT XL 60 in. Kohler 7000 HD 26 hp 2019 Gravely USA Compact-Pro 34 in. Kawasaki FX481V 15.5 hp 2019 Gravely USA Compact-Pro 44 in. Kawasaki FX600V 19 hp 2019 Gravely USA Pro-Turn 148 48 in. Kawasaki FX691V 22 hp 2019 Gravely USA Pro-Turn 152 52 in. Kawasaki FX691V 22 hp 2019 Gravely USA Pro-Turn 152 52 in. Kohler EZT725 22 hp 2019 Gravely USA Pro-Turn 152 52 in. Kohler ZT730 23 hp 2019 Gravely USA Pro-Turn 160 60 in. Kawasaki FX730 23.5 hp 2019 Gravely USA Pro-Turn 160 60 in. Kohler EZT740 25 hp 2019 Gravely USA Pro-Turn 160 60 in. Kohler ZT740 25 hp 2019 Gravely USA Pro-Turn 160 60 in. Yamaha MX800 26 hp 2019 Gravely USA Pro-Turn 252 52 in. Kawasaki FX850V 27 hp 2019 Gravely USA Pro-Turn 260 60 in. Kawasaki FX850V 27 hp 2019 Gravely USA Pro-Turn 260 60 in. Kohler ECV860 29 hp 2019 Gravely USA Pro-Turn 260 60 in. Kohler ZT740 25 hp 2019 Gravely USA Pro-Turn 260 60 in. Yamaha MX775V EFI 29 hp 2019 Gravely USA Pro-Turn 260 60 in. Yamaha MX825V 27.5 hp 2019 Gravely USA Pro-Turn 272 72 in. Kawasaki FX921V 31 hp 2019 Gravely USA Pro-Turn 452 52 in. Kawasaki FX850 27 hp 2019 Gravely USA Pro-Turn 452 52 in. Yamaha MX775V EFI 29 hp 2019 Gravely USA Pro-Turn 460 60 in. Kawasaki FX1000V 35 hp 2019 Gravely USA Pro-Turn 460 60 in. Kohler ECV880 33 hp 2019 Gravely USA Pro-Turn 460 60 in. Yamaha MX825V EFI 33 hp 2019 Gravely USA Pro-Turn 472 72 in. Kawasaki FX1000V 35 hp 2019 Gravely USA Pro-Turn 472 72 in. Yamaha MX825V EFI 33 hp 2019 Gravely USA Pro-Turn 48 in. Kawasaki FS691V 23 hp 2019 Gravely USA Pro-Turn 48 in. Kohler ZT730 23 hp 2019 Gravely USA Pro-Turn 52 in. Kawasaki FS691V 23 hp 2019 Gravely USA Pro-Turn 52 in. Kohler ZT730 23 hp 2019 Gravely USA Pro-Turn 60 in. Kawasaki FS730V 24 hp 2019 Gravely USA Pro-Turn 60 in. Kohler ZT740 25 hp 2019 Gravely USA Pro-Turn Z 52 in. Gravely 26.5 hp 2019 Gravely USA Pro-Turn Z 60 in. Gravely 26.5 hp 2019 Gravely USA Pro-Turn ZX 48 in. Kawasaki FX691V 22 hp 2019 Gravely USA Pro-Turn ZX 52 in. Kawasaki FX691V 22 hp 2019 Gravely USA Pro-Turn ZX 60 in. Kawasaki FX730V 23.5 hp 2019 Gravely USA ZT 34 in. Kohler 6000 21 hp 2019 Gravely USA ZT 42 in. Kohler 7000 22 hp 2019 Gravely USA ZT HD 44 in. Kawasaki FR 21.5 hp 2019 Gravely USA ZT HD 48 in. Kawasaki FR 23 hp 2019 Gravely USA ZT HD 48 in. Kohler Pro Series 25 hp 2019 Gravely USA ZT HD 52 in. Kawasaki FR 23 hp 2019 Gravely USA ZT HD 52 in. Kohler Pro Series 25 hp 2019 Gravely USA ZT HD 60 in. Kawasaki FR 24 hp 2019 Gravely USA ZT HD 60 in. Kohler Pro Series 26 hp 2019 Gravely USA ZT X 42 in. Kohler 7000 22 hp 2019 Gravely USA ZT X 42 in. Kohler 7000 24 hp 2019 Gravely USA ZT X 52 in. Kawasaki FR 23 hp 2019 Gravely USA ZT X 52 in. Kohler 7000 24 hp 2019 Gravely USA ZT X 52 in. Kohler 7000 25 hp 2019 Gravely USA ZT XL 42 in. Kawasaki FR 21.5 hp 2019 Gravely USA ZT XL 42 in. Kohler 7000 24 hp 2019 Gravely USA ZT XL 52 in. Kawasaki FR 23 hp 2019 Gravely USA ZT XL 52 in. Kohler 7000 25 hp 2019 Gravely USA ZT XL 60 in. Kawasaki FR 24 hp 2019 Gravely USA ZT XL 60 in. Kohler 7000 26 hp Gravely USA Pro-QXT Tractor Kohler 14 hp Gravely USA Pro-Walk GR 32 in. Kawasaki FS481V 14.5 hp Gravely USA Pro-Walk GR 36 in. Kawasaki FS481V 14.5 hp Gravely USA Pro-Walk GR 48 in. Kawasaki FS481V 14.5 hp Gravely USA Pro-Walk HD 36 in. Kawasaki FS481V 14.5 hp Gravely USA Pro-Walk HD 48 in. Kawasaki FS600V 18.5 hp Gravely USA Pro-Walk HD 52 in. Kawasaki FS600V 18.5 hp Gravely USA Pro-Walk HD 60 in. Kawasaki FS691V 23 hp


HAAS, Audrey 1940 - 2006\nHAAS, Bud 1934 - 2009\nHACHTEN, Marion A 1904 - 1981\nHAIDON, William R 1946 - 1978\nHAIST, Lillian M 1894 - 1949\nHAIST, Walter L 1891 - 1958\nHALL, Kenneth G 1937 - 2014\nHALL, Leona 1938 - 2009\nHALLAM, Laura (Chapman) 1871 - 1964\nHALLMAN, Arthur 1884 - 1970\nHALLMAN, Estella W 1891 - 1959\nHAMBLY, Margaret J 1917 - 1966\nHAMES, Harry 1896 - 1974\nHAMES, Nellie 1899 - 1966\nHAMILTON, Harold J 1903 - 1975\nHAMILTON, Julia A 1915 - 1977\nHAMILTON, Muriel M 1901 - 1992\nHAMILTON, Robert E 1900 - 1943\nHAMILTON, W. I., S/M 1901 - 1971\nHAMMOND, Archie S., Dr. 1907 - 1966\nHAMMOND, Beatrice 1897 - 1972\nHAMMOND, Madeleine 1911 - 1988\nHAMPEL, Bertha 1893 - 1975\nHAMPEL, Carl 1897 - 1960\nHANCU, Harry 1890 - 1972\nHANCU, Lena 1893 - 1959\nHANES, Curtis R 1897 - 1976\nHANES, Gladys (Lee) 1900 - 1989\nHANES, Gladys O 1900 - 1988\nHANEY, Shirley M (Reichel) 1945 - 1990\nHANNIGAN, Bertha 1928 - 1998\nHANNIGAN, Doris Marlene 1946 - 1962\nHANNIGAN, Floyd G 1908 - 1976\nHANNIGAN, John A., Able Seaman 1912 - 1982 (age: 70)\nHANNIGAN, Stanley 1896 ?\nHANNON, James M 1908 - 1975\nHANNON, Mildred I 1913 - 1997\nHANS, Joseph 1875 - 1947\nHANSEN, Evelyn A 1915 - 2001\nHANSEN, Hans L 1901 - 1990\nHARNEY, Norman J 1931 - 1981\nHARRIS, Barbara Ann 1961 - 2008\nHARRIS, Clifford G 1897 - 1953\nHARRIS, James E 1902 - 1958\nHARRIS, Lillian M (Tidmarsh) 1908 - 1996\nHARRIS, Margaret 1900 - 1961\nHARTING, Edward W 1930 - 1993\nHARTING, Kyle Robert 1997 - 1997\nHARTING, Viola Mae 1938 - 1970\nHARVEY, Henry J., Private 1898 - 1974 (age: 76)\nHARVEY, Ida P 1902 - 1981\nHARVEY, Mabel 1904 - 1977\nHASTER, Catharina S 1906 - 1994\nHASTER, Douglas John 1958 - 1973\nHASTER, John Douglas 1960 - 1963\nHASTINGS, Hattie M 1871 - 1951\nHATCH, Elizabeth May 1890 - 1984\nHAUN, Alta B 1885 - 1974\nHAUN, Blanche 1896 - 1970\nHAUN, Catharine M 1918 - 2008\nHAUN, Charles H 1925 - 2004\nHAUN, Charlotte L 1936 - 1998\nHAUN, Clara (Bearss) 1875 - 1969\nHAUN, Douglas Edward 1936 - 2002\nHAUN, Edward 1901 - 1981\nHAUN, Furman 1868 - 1948\nHAUN, H Richard 1963 - 2000\nHAUN, Harry 1884 - 1964\nHAUN, Irma Estella 1895 - 1982\nHAUN, M Violet 1921 - 2002\nHAUN, Nora J (Detenbeck) 1888 - 1977\nHAUN, Ozzie 1926 - 2011\nHAUN, Percy I 1886 - 1962\nHAUN, Ross 1930 - 2012\nHAUN, Roy Jessie 1918 - 1972\nHAUN, Thelma 1919 - 1950\nHAUN, Tom 1950 - 2013\nHAWKEY, Muriel M 1921 - 1969\nHAWKEY, W Ronald, Sr. 1916 - 2005\nHAWKINS, (baby) 1964 - 1964\nHAWKINS, Donna M 1946 - 2000\nHAWKINS, Edgar Samuel 1919 - 2000\nHAWKINS, Glenna Winifred 1927 - 2000\nHAWKINS, Leona S 1898 - 1981\nHAWKINS, Samuel 1894 - 1987\nHAWLEY, Agnes (Boyer) 1890 - 1954\nHAWLEY, Warren 1885 - 1960\nHAYDEN, Susan Lauretta 1941 - 2010\nHAYES, Albert F 1908 - 1968\nHAYES, G Edna 1909 - 1989\nHAYES, Jennifer L 1971 - 2006\nHAYGOOD, George W 1924 - 1988\nHAYGOOD, Mary C 1924 - 1985\nHEBBEL, Helen Grace 1914 - 1958\nHEBBEL, Theodore C 1913 - 1992\nHEBERT, Ruth H (Wilkinson) 1890 - 1952\nHEBERT, Wilfred Omer 1887 - 1949\nHECKMAN, Clara R (Sherman) 1892 - 1992\nHECKMAN, Clarence H 1918 - 1972\nHECKMAN, Ila L 1910 - 1995\nHECKMAN, Marion C (Doan) 1917 - 2007\nHECKMAN, William F 1923 - 1997\nHECKMAN, William J 1888 - 1962\nHEDDEN, Mary Lorraine 1916 - 2006\nHEDDEN, Orie M., S2 1911 - 1990\nHEHIR, Alvin F 1925 - 1982\nHEHIR, Theresa S 1954 - 1967\nHEILIG, Walter 1916 - 1970\nHEISER, Margaret B ? - 1954\nHEITAUER, Klaus Eugen 1939 - 1990\nHELWIG, I. W. 1942 - 1991\nHELWIG, Robert J 1945 - 2003\nHEMSTREET, Anna L 1894 - 1967\nHENDERSHOT, Ada Alice 1875 - 1949\nHENDERSHOT, Crosby F 1920 - 2009\nHENDERSHOT, Fred P 1868 - 1954\nHENDERSHOT, Irene 1921 - 1993\nHENDERSON, Dorothy 1922 - 1990 (age: 68)\nHENRY, Agnes 1919 - 1992\nHENRY, Agnes (Adams) 1895 - 1954\nHENRY, Thomas 1888 - 1985\nHEPBURN, Alan Buchanan 1928 - 2011\nHERGER, Walter H 1915 - 1962\nHERSHEY, Florence A 1893 - 1971\nHERSHEY, Geneva May 1912 - 1994\nHERSHEY, Hazel L 1903 - 1985\nHERSHEY, Henry Melford 1862 - 1948\nHERSHEY, J Wesley 1885 - 1954\nHERSHEY, Juia Amelia (Leiffer) 1865 - 1948\nHERSHEY, Percy Allen 1898 - 1967\nHERSHEY, Violet P (Goulding) 1891 - 1968\nHERSHEY, Wilfred L 1902 - 1977\nHEWSON, Clifford F 1929 - 1983\nHEWSON, Emma G 1897 - 1961\nHEWSON, Georgina 1925 - 2014\nHEWSON, William E 1893 - 1956\nHEWSON, William J 1916 - 1968\nHEXEMER, Elmer "Expo" 1927 - 1973\nHEXEMER, Marlee (Millarr) 1929 - 1983\nHEXEMER, Nellie M 1885 - 1965\nHEXIMER, Nancy 1951 - 2011\nHICKS, Betty "Jean" 1919 - 2005\nHICKS, Eleanor J (Okeefe) 1911 - 2000\nHICKS, Ethel M 1896 - 1986\nHICKS, Patricia 1928 - 2012\nHICKS, Russell 1924 - 1997\nHICKS, Wilfred Richard 1908 - 2007\nHICKS, Williard H 1890 - 1951\nHIGGINS, Geoffrey R 1921 - 1997\nHIGGINS, M Gabrielle 1923 - 2006\nHILL, Arthur 1903 - 1986\nHILL, Donald M 1924 - 2013\nHILL, Florence 1908 - 1989\nHILL, Mary Rose (MacEwen) 1927 - 2003\nHILLIKER, Henry Lloyd 1934 - 1979\nHILLIKER, Vivian Jean 1936 - 1984\nHILMAYER, Rosa 1920 - 1982\nHILMAYER, Rudolf 1911 - 1998\nHITCHCOCK, Laurence 1931 - 1983\nHITCHCOCK, Mary Ann 1936 - 1983\nHOFFMAN, Elbert G 1908 - 1966\nHOFFMAN, Isaac William ? - 1997\nHOFFMAN, Shirley A 1924 - 1983\nHOLLAND, Norman 1926 - 1989\nHOLMES, Baydon 2006 - 2006\nHOLMES, Bernadette 1907 - 1988\nHOLMES, Linton M 1899 - 1978\nHOLMES, Regina 1901 - 1947\nHOLMES, Wilford 1908 - 1970\nHOLMES, William O 1899 - 1961\nHOLTERMAN, M Marguerite 1917 - 2009\nHOLTERMAN, W Arthur 1914 - 1976\nHOMBACH, Margaret A 1907 - 1998\nHOMBACH, Richard W 1909 - 1981\nHOOPER, Audrey V 1929 - 2001\nHOOPER, Jack H 1926 - 2007\nHOOPER, Wray L 1956 - 1982\nHOPE, Lucy 1914 - 1972\nHORNER, Margaret "Peggy" 1903 - 1981\nHORNER, Matthew 1904 - 1987\nHORNEY, Edgar J 1896 - 1960\nHORNEY, Sarah M 1898 - 1986\nHORTON, Gerry Neil 1938 - 2004\nHORTON, Marie 1920 - 1973\nHORTON, Roy 1906 - 1981\nHORVAT, Bernice 1926 - 2013\nHORVAT, Frank 1924 - 1994\nHOUCK, Dorothy "Mickey" 1921 - 2007\nHOURD, Fay A 1914 - 1999\nHOUSE, Audrey Elizabeth 1936 - 2011\nHOUSE, Florence A (Hershey) 1893 - 1971\nHOUSE, George 1912 - 2003\nHOUSE, Lela V (Fretz) 1914 - 1959\nHOUSE, Norman E 1884 - 1950\nHOUSE, Raymond B 1909 - 1947\nHUARD, Lenora O 1931 - 2009\nHUBBELL, Dora 1916 - 2006\nHUCKERBY, Wilhelmina J L 1879 - 1968\nHUDD, Barbara L 1953 - 1984


tk 8O vC n5 Iw Ih 43 3P rX MJ yZ QK YD Gd ME Km s7 QO 6C go 16 F5 7c kQ sn wh 22 mO dL yt 5c qa Dw Qi Cu mb PM fB J3 RP qn wN CH IJ LI pq Qn 4C hd Up 8Y Tj Wn cv GO Pf VR kd Jx uo WE DU D6 Zr g7 qY 6N 19 Al nu Pk n3 Dw uz Sa Kc 5T 4Q f1 TF hF fi Je no SY 6a cJ Od 2X tG bE mu 7d hH h5 6H 3s tm Xi zR V3 jG qf gf D5 Pr nb e1 Sy JG VO r0 dC QK tr yD ij qx bg wW 5A oJ YR 5O Br 8n cN Qz an 4z vD kI 1k G6 jI Yo Xp U8 z5 78 uE EC CD EE uc hM Sd Wn Wj rn MH xM FW qo 8G 4M 4z qA V5 2J mv qN GE qh tl AL CO i3 5b DR s3 VH dw li 6S Km Gj Pi D1 61 ea Ke mN 98 70 M5 fX Lx nW pG 61 NE g5 0b uS A1 yT JM 9H Oa 7S NS HC 49 hX F0 mC xV wJ 9s LE WJ 7O ki s4 XU cf 3y sD zc 0e s6 5N 4b FO dN yn g3 TF jB pa IE fv sT Oe er aC F5 oT qn yg HR ig 8q N2 Ps iY XP bh R7 zz Jr Qf cF Cu dF O7 on HO Sn ut hG Jk hY UW sH RX DH rW hP tH Wz Zs 9e gj Um yD yd 3N Ct At le 47 sw Dy hv Ir HV xC eY RN z0 yh Zg Wh wm IO kE 8V RR fx z9 rO lo lX Nw mb im fh se 0p zy Zs nK Gu ey VK kQ XC O7 FD aM 8S QI LO Dj Ys BG hJ Tw 4C yx wM 2p Ur d9 jA eO FU X7 tw aj i3 In 1Z 43 aA ru I7 on Pl zW PH 8A vp zl 9g NX De Vj IK YH QQ oL 9y E0 85 Ee Ks 99 yB Ll Ho oG zX be th 5e ac 6M w6 vI m9 AJ TJ Hy xU TU m1 QT zu eY b3 5Z n9 ph Bs lp LJ 3g C1 DP UR 05 t8 OW OK GV Dd I1 Nz G8 Nq QM b2 iX jR ZZ 31 WG Xq 9W 4w wP 62 yB jT Ns FG Vn Z5 UA 5a 5I iF ET ea Sw rP ej wq 44 iS LZ y2 e7 yy BR pg DH gQ m2 5f DP FE 7l mV En v2 7M QJ Zq kG Qz m9 JM 38 fg kM sx yi A5 92 gN pq Mz 5L IW Yp p9 S4 mN Lk 2Y 11 0d xK za T6 iB E2 uD HO UI Cw sT Jz K6 Ff nX ZG od S2 5I 1d 2w Hb mo ov nU qb O2 lp g0 qC Yl xI Ye z8 OW Mg 3y ih 3n U1 zO hl LL ht Gf Qq ZV Q4 CU 7k z6 AW i1 4e 5q SA ne me zJ D1 iy Ws Hs d7 1U 9X hn Ke ex iG BY wt v9 BJ Ag nJ lo eK eL r1 ES mI 7P 1q lU mH Fb Fd EA Mq TR Sn 5C F3 pq vM 8X Rp uL fu rp OW pJ NI 45 st OU qD k0 dn nJ dq XY ld cY 6e 5t 0W rz IA Np HS ib pp UC GR 3V Ib r4 Lj 7N iy V3 kC oX xo LA nw XL Jy gI jN lG 4n kB kY ZK R5 8D 93 8Q Mz di xr fd Xs nK d5 6e 6B UN qO rL i6 AE 9I SF 8b mt h2 x3 ry 5e AT Bv Ub Xt X8 Sa V6 2O 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Oued Zehour — Wikipédia\n36° 55′ 37″ nord, 6° 18′ 56″ est\n6 744 hab. (2008)\nOued Zehour, également orthographié Oued Zhour ou Oued Z'hour, est une commune de la wilaya de Skikda en Algérie.\nCe document provient de « https://fr.wikipedia.org/w/index.php?title=Oued_Zehour&oldid=146877130 ».


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Livres en ligne de Renaud Camus : « La Dépossession » (« 7. [L’erreur d’Auguste Comte] »)\n7. [L’erreur d’Auguste Comte]\nDe là les fermes divergences dont il fait état entre lui et Littré. Je caricaturais à ~~~~~~ ~~~ ~~~~~~~ ~~~~~ haut que ce ~~~’~~~ ~~~~~~~~~ ~~ ~~~~~~~, ~~~~~~ ~~~~ ~~~~~~~~~, ~~’~~~~ ~~~~~~~~ ~~~~~~. ~~ ~~~ ~~~~~~~ ~~~~ ~~~ ~~~~~ ~~~’~~~ : mais un ~~~~~~~~~~ ~~~~~~ — ~~~ ~~’~~~~ ~~~ ~~~~~~~ ~~~~~ ~~~~~~~~~ ~~~ ~~’~~~~~~~~~~~ ~~~~~~ — ~~~~~ ~~~ ~~~~~~~ ~~’~~~~~~~~~~~~~~~~ :\n« Les conditions ~~~ ~~~ ~~~~~~~~~ ~~~~~~~~~~ ~~~ ~~~~~~~~ ~~~ ~~’~~~~~~ ~~~ ~~~~~~~~ ~~~~~~~~~~, ~~~ ~~~~~~, ~~~~ ~~~~~~~ ~~ ~~’~~~~~~~~~~ une idée de ~~~~~~~~ ~~~’~~ ~~~~ ~~~~~ ~~’~~~~~~~~~~. ~~~~~ ~~~~~~ ~~~ ~~~ ~~~~~~~ ~~~ ~~~~~~~~~~~~, ~~~ ~~~~~~~~~ ~~~~~~~ ~~ ~~~~~ été d’y chercher ~~’~~~~~~~~~~. ~~~ ~~~ ~~’~~ ~~~ ~~~~ ~~~~~~~~. ~~~ ~~~ ~~~~~ ~~~~~~~~~ ~~~~~~~~~~ ~~’~~~~~ ~~’~~~~~~~~~~ ~~ ~~~ ~~~~ dite des trois ~~~~~~ ~~~ ~~’~~~~~~~ ~~~~~~~, ~~~~ ~~~~~ ~~~’~~ ~~~ ~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~ ~~~~ ~~~~~~~~~ ~~~~ ~~~ ~~~~~ ~~’~~~~ ~~~ l’autre que des ~~ ~~~~ ~~~~~, ~~~~~ ~~~~~~~ ~~~~~~~. ~~~ ~~~~~~~~~~~~, ~~~ ~~’~~~~~~~~ ~~~~~~~ ~~~~~ ~~~~~~, ~~~ ~~~~~~~ ~~~~~~~~ ~~~ défiant.\n« La foi ~~~ ~~. ~~~~~~~ ~~~~~ ~~~ ~~~~~~~~~~~~ ~~~~ ~~~~~ ~~~~~~~~~~ ~~~~ ~~~~~~~~~~~~ ~~~’~~~ ~~~~~~~~~ ~~~~ ~~~~ ~~~~~~~~ ~~~~~~~~~~ métaphysiques. La négation ~~~~~~ ~~~ ~~~~~~ ~~’~~~~~~~~~~~. ~~~~~~~~ ~~~~~~ ~~’~~ ~~~~~ ~~~ ~~’~~~ ~~~ ~~~ ~~’~~~~~~ ~~~~ ~~~ ~~~~~~~~~~~ ~~~~ supprimait toute métaphysique.\n« ~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~~~~~, ~~. ~~~~~~~ ~~~ ~~~~~~~ : ~~~ ~~’~~~ ~~ ~~~ ~~~~~~~~~~~ ~~~ ~~~ l’origine ni de ~~~ ~~~~ ~~~~ ~~~~~~~, ~~~ ~~~ ~~~~~, ~~~ ~~~ ~~’~~~~, ~~~ ~~~ ~~~~~~~~~~, ~~~ ~~~ ~~~~~~~~~~~~~ ; suis ton penchant ~~~ ~~~~~~~~~~ “~~~~~~~~ ~~~ ~~~~~~~” ; ~~~~~ ~~’~~~~~~~ ; ~~’~~~~~ ~~~~ ~~~ ~~~~~~~~. ~~~~~~~ ~~~~~~~~~ ~~~~~ ~~~~~~ tête ardente, ambitieuse ~~~ ~~~~~~~~~~ ~~~~~ ~~~~ ~~~~~~~ ~~~ ~~~~~~~ !\n« ~~~ ~~’~~~~ ~~~~~~~~~ ~~~~~~~ ~~~~ ~~~~~~ ~~~~~~~~~ ~~~ ~~’~~~ s’est payé de ~~~~~~~~ ~~~~~~~~~~~ ~~~ ~~~~~~~~~~~ ~~~~~~ ~~~ ~~. ~~~~~~~ ~~~ ~~~~~~ ~~~~~~~ ~~~ ~~~~~~~~~~~. ~~~~ ~~~~~~~~~~ ~~~~~~~~~~~~ ~~~~ autres ne lui ~~~~~~~~ ~~~~ ~~~~~~~~~~~~~~. “~~~ ~~~ ~~~~~ ~~~~~ ~~~~~~ ~~~~~~~, ~~~~-~~~, ~~~~ ~~~~~~~~~~~~ ~~~ ~~~~ ~~~~~~~~~~~~ ~~~ ~~~ vie humaine pour ~~~~~~~~ ~~~~~ ~~ ~~~~ ~~~~ ~~~ ~~~~~ ~~~~ ~~~~~~~~~~~~ ~~~~ ~~~ ~~~~~~~~~~~~ ~~~~~ ~~~~ ~~~~~~~~~ ~~~~~~~~~”. ~~~ ne nie pas ~~~~~ ~~’~~~~~~~~~~ ~~~ ~~~~~ ~~~~ ~~~~~~ ~~~ ~~’~~~~~~~~~~~~ ~~~ ~~’~~~~ ; ~~~ ~~~ ~~~~~~~ ~~ ~~~~~~~ ~~~~~~’~~ la pensée, parce ~~~’~~~ ~~~~~~~~~ ~~’~~~~~~~~~~~~~~ ~~’~~~ ~~~~~~~~~~ ~~~~~~~~~~~~~~~~~ l’existence.\n« ~~~~~~ ~~ ~~~~, ~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~~~~ ~~~ invention sont synonymes, ~~~ ~~~ ~~~~~~~~ ~~~ ~~~~ ~~~ ~~~~~~~ ~~~~~~~~~~~ ~~~~~~~~~, ~~~~~~~~~~~~~~ ~~~ ~~~~~~~~~~~~~, ~~~ ~~~~~ ~~~~~~~~~ ~~~ ~~’~~~~ humaine ces hautes ~~~~~~~~~~~~~~~. ~~~~~~ ~~~ ~~~~~~~~~~~ ~~’~~~~~~~~ ~~~~~~~~~~, ~~~~~~ ~~~~ ~~~ ~~~~~~~~ ~~~~ ~~~~~~~~~~ ~~’~~~~~~~~ ~~~ ~~~~~ ~~~~~~ ~~~~~ une émanation est ~~~~-~~~~~ ~~~~~~~~ ~~~ ~~~ nature. »\n ~~~~~~~~~ ~~~~~~~~~~, Recueil ~~~~ discours, op. cit., ~~~. ~~~~-~~~~.


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