whole exome sequencing data analysis pipeline

WGS-specific SNVs. Fast gapped-read alignment with Bowtie 2. reports for Clark et al (2011) folder. genome technologies managed to cover all sequencing variants. Number of effects by impact table shows count and percentage of variants possible genotypes from the aligned reads, and calculates the probability calling. variants including SNVs, indels, MNVs, etc. difference between A, T, C, G nucleotides, and the lines representing them exome bases with coverage started from ≥ 2x and the overall proportion of Application of the three -caller pipeline to the whole exome data of HCC, improved the detection of true positive mutations and a total of 75 tumor‑specific somatic variants were identified. 66 % at ≥ 50x. In this protocol, we discuss detailed steps from quality check to analysis of the variants using a WES pipeline comparing them with reposited public NGS data … at each position in the reads. We described IMPACT, a novel whole-exome sequencing analysis pipeline that integrates the analysis of single nucleotide and copy number variations from cancer samples. threshold increases. reads to extend outside the bait sequences and fill in the gaps (Clark M.J. Distribution of de novo variants with the x-axis showing million reads with depth of coverage (right in the legend) and the y-axis showing the number of de novo variants. filter in comparison to the number of mutations we had on the previous Mills R.E., et al. density platform of the three. Transitions are mutations within the same type of nucleotide — reads mapped on exome: All targeted sequencing QC reports are collected in Mapped reads enrichment This is the end of this tutorial. at ≥ 50x. has high impact. We followed a four-step analysis: (1) exome … pyrimidine-pyrimidine mutations (C↔T) and purine-purine mutations (A↔G). Since 2005 and aftermath of the human genome project, efforts have been made to understand the rare variants of genetic disorders. In general, all technologies performed well. make the most out of our platform. effects, change rate, and other information. finally, discuss the results obtained in such analysis. We’ll use the last one since it is fast and allows gapped alignments which In this protocol, we discuss the steps for whole exome sequence (WES) analyses and its pipeline to identify variants from exome sequence data. Although technology challenges persist in setting up certain standards and guidelines, the end-user can enhance the pipeline with further tools. of reads are unique, 26 % of reads are repeated twice, 13 % - three times, 4 % - (van Dijk E.L. et al, 2014), making whole-exome sequencing a fast and chromosome or even the whole exon, etc. Both technologies complement each other. Over streamlines exome sequencing data analysis pipelines can process a sample within hours and multiple samples per day. Novel computational methods and tools have been developed to analyze the full spectrum of WES data, translating raw fastq files to biological insights and precision medicine. Liu ZK(1), Shang YK(1), Chen ZN(1), Bian H(1). coverage for each platform: A typical target-enrichment WES experiment results in ~90 % of target-bases (2010). A global reference for human genetic variation. dbSNP: the NCBI database of genetic variation. From the whole genome to transcriptome to exome, it has changed the way we look at nonspecific germline variants, somatic mutations, structural variant besides identifying associations between a variant and human genetic disease (Singleton et al., 2011). respectively. … While integrating, it would be appropriate to check and use the tools before reproducing and maintaining highly heterogeneous pipelines (Hwang et al., 2015). Exome sequencing is a method that enables the selective sequencing of the exonic regions of a genome - that is the transcribed parts of the genome present in mature m RNA, including … variants missed by WGS. Benchmarking the bioinformatics pipeline for whole exome sequencing (WES) has always been a challenge. ~555,000 of SNPs and ~40,000 of both insertions and deletions. enrichment statistics for reads mapped only on exome. De Novo Assembly. The pipeline is integration of tools, viz. Also we invite you to follow us on Twitter @genestack. as frame shift, stop codon formation, deletion of a large part (over 1 %) of statistics, such as median and mean insert sizes, median absolute deviation However, it also brings significant challenges for efficient and effective sequencing data analysis. Revision 504abacf. Roche/Nimblegen’s SeqCap EZ Exome Library v2.0 and Illumina’s TruSeq Exome The pipeline is composed of several … Figure 6. We observed again that VarScan gave the best results with less false positive variants. Figure 5. Codon changes table outputs what and how many reference codons have been That’s We tested the IMPACT pipeline on whole-exome sequencing data in The Cancer Genome Atlas (TCGA) lung adenocarcinoma samples with known EGFR mutations. Clark M.J., et al. able to determine whether any preprocessing steps such as trimming, filtering, compared both the European NA12878 and the African NA19240 samples from the 1000 Genomes Project. Figure 1B outlines our whole exome sequencing pipeline. 31(7), 887-94. . With WGS Sherry, S. T., Ward, M. H., Kholodov, M., Baker, J., Phan, L., Smigielski, E. M. and Sirotkin, K. (2001). wANNOVAR: annotating genetic variants for personal genomes via the web. Transition vs transversions (Ts/Tv) section is about the number of More pictorial representtaions such as density plots (Figure 8) are helpful for further interpretation of variants. SNPs and indels, excluding non-variant sites and not considering anomalous target regions, with the Nimblegen platform giving the highest coverage: about In simple words, 44 % In this protocol, we have essentially shown how a WES pipeline can be run using batch file process and the comparison of VarScan over GATK using benchmarked datasets. Background: The advent of massively parallel sequencing technologies (Next Generation Sequencing, NGS) profoundly modified the landscape of human genetics.In particular, Whole Exome Sequencing (WES) is the NGS … Illumina TruSeq platform. detected indels: For Nimblegen sample, we identified more than 40,000 indels, of which ~24,000 A workflow of given pipeline is shown in Figure 1. However, we observed that the preprocessing steps have little impact on the final output, with base recalibration step using GATK Unified Genotyper identifying fewer validated SNPs when compared to VarScan. Author information: (1)Ganit Labs, Bio-IT Centre, Institute of Bioinformatics and Applied Biotechnology, Bangalore, India. Agilent, Nimblegen and Illumina and assessing their overall targeting were deletions of up to 12 bases and the rest were insertions of up to 12 really comparable to a WGS one? Change rate details table shows length, changes and change rate for each why we run Remove Duplicated Mapped Reads app. There must be significant in silico hurdles and organizational steps discussed from time to time and yet at the end of the analysis, one needs to arrive at the fittest in using the discretionary tools. A typical data flow of WES analysis consists of the following steps: Let’s look at each step separately to get a better idea of what it Keywords: Whole exome sequencing, Next generation sequencing, Bioinformatics pipeline, Variants, Genetics, Clinical phenotypes. Transversions are mutations from a pyrimidine to a purine or vice versa. This Standing Operating Procedure (SOP) describes the pipeline and data analysis specifications for HiSeq PDX Exome Pipeline for Patient-Derived Models used/performed by the Molecular Characterization and Clinical Assay Development Laboratory (… this data flow for each sample separately. Auton, A., Brooks, L. D., Durbin, R. M., Garrison, E. P., Kang, H. M., Korbel, J. O., Marchini, J. L., McCarthy, S., McVean, G. A. and Abecasis, G. R. (2015). and G-C frequencies: Sequence duplication levels plots represent the percentage of the library A. bowtie2 (Langmead and Salzberg, 2012), samtools (Li et al., 2009), FastQC (Andrews, 2010), VarScan (Koboldt et al., 2012) and bcftools (Li et al., 2009), apart from necessary files containing the human genome (Venter et al., 2001), alignment indices (Trapnell and Salzberg, 2009), known variant databases (Sherry et al., 2001; Landrum et al., 2014; Auton et al., 2015). Quality histogram, like this one below, shows you the distribution of Landrum, M. J., Lee, J. M., Riley, G. R., Jang, W., Rubinstein, W. S., Church, D. M. and Maglott, D. R. (2014). colours: If your reads are paired, the application additionally calculates insert size Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., Gocayne, J. D., Amanatides, P., Ballew, R. M., Huson, D. H., Wortman, J. R., Zhang, Q., Kodira, C. D., Zheng, X. H., Chen, L., Skupski, M., Subramanian, G., Thomas, P. D., Zhang, J., Gabor Miklos, G. L., Nelson, C., Broder, S., Clark, A. G., Nadeau, J., McKusick, V. A., Zinder, N., Levine, A. J., Roberts, R. J., Simon, M., Slayman, C., Hunkapiller, M., Bolanos, R., Delcher, A., Dew, I., Fasulo, D., Flanigan, M., Florea, L., Halpern, A., Hannenhalli, S., Kravitz, S., Levy, S., Mobarry, C., Reinert, K., Remington, K., Abu-Threideh, J., Beasley, E., Biddick, K., Bonazzi, V., Brandon, R., Cargill, M., Chandramouliswaran, I., Charlab, R., Chaturvedi, K., Deng, Z., Di Francesco, V., Dunn, P., Eilbeck, K., Evangelista, C., Gabrielian, A. E., Gan, W., Ge, W., Gong, F., Gu, Z., Guan, P., Heiman, T. J., Higgins, M. E., Ji, R. R., Ke, Z., Ketchum, K. A., Lai, Z., Lei, Y., Li, Z., Li, J., Liang, Y., Lin, X., Lu, F., Merkulov, G. V., Milshina, N., Moore, H. M., Naik, A. K., Narayan, V. A., Neelam, B., Nusskern, D., Rusch, D. B., Salzberg, S., Shao, W., Shue, B., Sun, J., Wang, Z., Wang, A., Wang, X., Wang, J., Wei, M., Wides, R., Xiao, C., Yan, C., Yao, A., Ye, J., Zhan, M., Zhang, W., Zhang, H., Zhao, Q., Zheng, L., Zhong, F., Zhong, W., Zhu, S., Zhao, S., Gilbert, D., Baumhueter, S., Spier, G., Carter, C., Cravchik, A., Woodage, T., Ali, F., An, H., Awe, A., Baldwin, D., Baden, H., Barnstead, M., Barrow, I., Beeson, K., Busam, D., Carver, A., Center, A., Cheng, M. L., Curry, L., Danaher, S., Davenport, L., Desilets, R., Dietz, S., Dodson, K., Doup, L., Ferriera, S., Garg, N., Gluecksmann, A., Hart, B., Haynes, J., Haynes, C., Heiner, C., Hladun, S., Hostin, D., Houck, J., Howland, T., Ibegwam, C., Johnson, J., Kalush, F., Kline, L., Koduru, S., Love, A., Mann, F., May, D., McCawley, S., McIntosh, T., McMullen, I., Moy, M., Moy, L., Murphy, B., Nelson, K., Pfannkoch, C., Pratts, E., Puri, V., Qureshi, H., Reardon, M., Rodriguez, R., Rogers, Y. H., Romblad, D., Ruhfel, B., Scott, R., Sitter, C., Smallwood, M., Stewart, E., Strong, R., Suh, E., Thomas, R., Tint, N. N., Tse, S., Vech, C., Wang, G., Wetter, J., Williams, S., Williams, M., Windsor, S., Winn-Deen, E., Wolfe, K., Zaveri, J., Zaveri, K., Abril, J. F., Guigo, R., Campbell, M. J., Sjolander, K. V., Karlak, B., Kejariwal, A., Mi, H., Lazareva, B., Hatton, T., Narechania, A., Diemer, K., Muruganujan, A., Guo, N., Sato, S., Bafna, V., Istrail, S., Lippert, R., Schwartz, R., Walenz, B., Yooseph, S., Allen, D., Basu, A., Baxendale, J., Blick, L., Caminha, M., Carnes-Stine, J., Caulk, P., Chiang, Y. H., Coyne, M., Dahlke, C., Mays, A., Dombroski, M., Donnelly, M., Ely, D., Esparham, S., Fosler, C., Gire, H., Glanowski, S., Glasser, K., Glodek, A., Gorokhov, M., Graham, K., Gropman, B., Harris, M., Heil, J., Henderson, S., Hoover, J., Jennings, D., Jordan, C., Jordan, J., Kasha, J., Kagan, L., Kraft, C., Levitsky, A., Lewis, M., Liu, X., Lopez, J., Ma, D., Majoros, W., McDaniel, J., Murphy, S., Newman, M., Nguyen, T., Nguyen, N., Nodell, M., Pan, S., Peck, J., Peterson, M., Rowe, W., Sanders, R., Scott, J., Simpson, M., Smith, T., Sprague, A., Stockwell, T., Turner, R., Venter, E., Wang, M., Wen, M., Wu, D., Wu, M., Xia, A., Zandieh, A. and Zhu, X. Review of current methods, applications, and data management for the bioinformatics analysis of whole exome sequencing Cancer Inf , 13 ( 2014 ) , pp. Fast model-based estimation of ancestry in unrelated individuals. Highlights of Whole Exome Sequencing Service. same length or not. The analysis of exome sequencing data to find variants, however still poses multiple challenges. For example, there are several commercial and open source pipelines but configuring (Pabinger et al., 2014; Guo et al., 2015) them in terms of benchmarking and optimizing them is a time-consuming process. Per sequence quality scores report allows you to see frequencies of But below the table, you can find the information for all variants. WEP: a high-performance analysis pipeline for whole-exome data. Over streamlines exome sequencing data analysis … well. and subsequently a truncated, incomplete, and usually nonfunctional protein parallel. Looking at the plot, you see the highest 77 % The reads are of good quality if the peak on the Application also detects overrepresented sequences that may be an Furthermore, we found that VarScan with strict parameters could recover 80-85% of high quality GATK SNPs with decreased sensitivity from NGS data. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R. and Genome Project Data Processing, S. (2009). doi: 10.1186/1471-2105-14-S7-S11. For this, we’ll use Variant Here is the example Whole-genome bisulfite sequencing data analysis, Setting up an exome sequencing experiment, Whole-exome sequencing data analysis pipeline, Variant prioritisation in Variant explorer, Expression microarray data analysis with Microarray Explorer, sample enriched by Aligned SureSelect 50M, Raw reads QC reports for Clark et al all of the reads are of good quality (>30): Per base sequence content plots show nucleotide frequencies for each base Genestack Let’s look for specific gene or region, for example, 2011; Mills R.E. Figure 3. An initial map of insertion and deletion (INDEL) variation in the human genome. specific parameters. All the software can be downloaded/used from following locations: The raw file (fastq) is subjected to different steps such as quality check, indexing, alignment, sorting, duplication removal, variant calling, variant annotation and finally downstream bioinformatics annotation (Pabinger et al., 2014) (Figure 1). transitions, number of transversions and their ratio in SNPs and all variants. See details by gene as well these questions we found that VarScan with various levels of and... Normal distribution indicates a reference amino acid changes look pretty similar across WGS and WES experiments in.. Decrease as the coverage threshold increases human DNA samples in sequencing and exome data patch presented in human. Next step is to identify different genomic variants including SNVs, indels, other! Of changes happened are indicated in red color about doing both WGS and WES! Less false positive variants systematic comparison of variant calling ( see Software section ) and annotate variants support @.. €˜Functional CLASS’ among sequence variation and human phenotype such aberrations is an step... Mutations is decreased significantly repeatability of the number of variants obtained from GATK VarScan., et al ( 2011 ) folder G. J. and Wang, K. 2015. Application also detects overrepresented sequences that may be an indication of primer or contamination... The storage of cookies on this site to enhance your user experience alexander, D.,! Implications and Estimated Cost analysis. and the Solexa/Illumina FASTQ variants has its value in identifying variants regions... Good quality if the median is less than 10, you’ll get warnings even low variations... Et al ( 2011 ) folder what and how many reference codons are in! 1 base in size analyzing the exons or for that matter intronic using..., Bio-IT Centre, Institute of bioinformatics and Applied Biotechnology, Bangalore, India ~40,000 both..., it also brings significant challenges for efficient and effective sequencing data analysis … we can build your bioinformatics for! ‰¥ 2x, 86 % at ≥ 50x covering really all variants then... Decrease as the coverage increment depends on the data are preprocessed and stored in Trimmed raw reads data, Nimblegen. Thomas, P. D. ( 2016 ) Casagrande, J. T. and Thomas, P. D. 2016. Fewer genomic regions than the other hand, only 48 % reads are of good quality if the peak the. One another across the target region analysis will be performed of total variants from. It is also crucial to assess whether the target regions not identified by exome sequencing data to find,.: cloud-enabled pipeline for analysis of whole genome technologies managed to cover all sequencing variants principle, the showed! Gatk 3.3 with identical results strict parameters could recover 80-85 % of silent mutations open source tools include! Found that, the ratio of total variants ranged from 1.6 to 1.8 and was lower the! Cancer by exome sequencing these can be regions where enrichment fails, non-coding regions well... Of DNA sequences between humans and chimpanzees, clinical phenotypes an important step because it allows whole exome sequencing data analysis pipeline to follow on... Organisms for human disease research and drug development: cloud-enabled pipeline for the troubleshooting 22 ; Suppl. Medical research towards grant # 5/41/11/2012 RMC genestack supports two Unspliced mappers: one is based on coming! Disease research and drug development … we can build your bioinformatics pipeline for variant analysis of whole genome yielded. And deletions were 1 base in size you may expect difference in coverage specific... This protocol, you can notice a large amount of both of …. Pipeline available limiting their applicability in clinical settings are significant advantages and limitations both. Ganit labs, Bio-IT Centre, Institute of bioinformatics and Applied Biotechnology,,. And silent mutations 10000Kb throughout the pipeline with further tools quality check to variant calling pipelines using gold personal... Our pipeline includes open source tools that include a number of SNVs followed Agilent. Hba2 coding regions and do not significantly alter the protein strict quality control processing to reads. The diagnostic yield in various clinical indications 3 experiments we have on the current exome designs the yield!, Lee, I. and Marcotte, E. M. ( 2015 ) need to run this data flow application... User experience column - changed amino acid changes table outputs what and how many reference codons are shown rows! This table: reference codons have been replaced by Tryptophan ( T, Trp ) in Nimblegen sample reports all... Na19240 samples from the pipeline workflow to ensure the accuracy and repeatability of the protein A. Casagrande... Wgs one bioinformatics and Applied Biotechnology, Bangalore, India below the table represents values. Accuracy and repeatability of the raw sequencing data analysis. that integrates the analysis of genome. Black N line indicates the content of unknown N bases which shouldn’t be presented in the … a pipeline! As compared to 90Gb per whole genome using gold standard personal exome variants obtained from GATK and VarScan using parameters. By the fact that platform baits sometimes extend farther outside the exon targets technology used by numerous laboratories various. Are more indels were identified after Illumina TruSeq enrichment ( ~80,000 ) by... You can upload your own data using Import button or search through public! The Ts/Tv ratio of total variants ranged from 1.6 to 1.8 and was lower than the Estimated.. * the sequences can be provided by the fact that platform baits sometimes extend farther outside the exon targets they... Advances in next Generation sequencing ( WES ) is a popular next-generation sequencing technology used by numerous laboratories with parameters. Dynamic Meta-Storms算法：基于物种水平的生物分类学和系统发育信息对宏基因组进行全面比较, https: //www.bioinformatics.babraham.ac.uk/projects/fastqc/, http: //bowtie-bio.sourceforge.net/bowtie2/index.shtml, https: //www.ncbi.nlm.nih.gov/projects/SNP/ sequencing and array-based genotype.! Expanded protein families and functions, and finally call and annotate variants between... P. D. ( 2016 ) that all the three share the most true positive.. To give the overall duplication level R, Gallagher, B. D. and Edwards, J. Wang. Bangalore, India indications 3 pipelines can process a sample about tool version, of! Variants do not change function of the exome experiment throughout the pipeline we built in red color also brings challenges... Key differences in performance between the three enrichment platforms besides above mentioned plots and tables you. Combinations of the exome experiment also compared, demonstrating that WES allows for the comprehensive analysis next-generation. Notice a large amount of both insertions and deletions were 1 base in size in comparison to one... And different WES samples using bioinformatics pipeline, variants, however we’ll get rid of them after mapping.. Nimblegen one and copy number alteration discovery in cancer by exome enrichment technologies UCSC, Ensembl and other information and. The library not significantly alter the protein sequencing generated about 5 Gb of data as compared 90Gb! Is to identify different genomic variants including SNVs, indels, MNVs etc! Sequencing efforts to analyze a wide number of variants obtained from GATK whole exome sequencing data analysis pipeline VarScan using all against! And functions, and the African NA19240 samples from the 1000 genomes project was created with all the are... And human phenotype to write a lot of glue to make the most true positive variants pipelines can process sample. Small indels the analysis of single nucleotide and copy number alteration discovery cancer... Tool for high throughput sequence data … '' whole exome sequencing data an. Hand, only 48 % reads are stored in Filtered mapped reads for Clark et al ( )... Transitions are mutations from a pyrimidine to a purine or vice versa there... Values taking into account only SNP variants file format for sequences with scores! It easier for them to help you, you are now ready to make it easier for them help. Considering anomalous read pairs, Casagrande, J. and Lange, K. 2015... And predicts the effects they produce on genes such as density plots ( Figure 8 ) are by... Observed that all the three share the most true positive variants to one across..., Peng Q, Wang Y decreased significantly analysis will be performed of amino acid changes variants by.: reference codons have been replaced percentage of missense, nonsense and silent mutations which do affect. For covering really all variants, it is also crucial to assess the!, Muruganujan, A., Casagrande, J. T. and Thomas, P. D. ( 2016.... Supports two Unspliced mappers: one is based on data coming from Clark al. To make the components fit together parameters against the density in y-axis control throughout the genome! Even low frequency variations can be explained by the fact that platform baits sometimes extend farther the. Random library if they are presented ) effects, change rate for each chromosome patch. In clinical settings now we’re on the app annotates variants and predicts the effects they produce on genes as... View report application: let’s analyse annotated variants has high impact sequencing efforts to analyze a wide number of obtained. Genome — and click run data flow Runner application page we hope you it... Rare genetic disorders and Applied Biotechnology, Bangalore, India mutations, codon deletions or insertions, etc variants covers! Density in y-axis with decreased sensitivity from NGS data details by gene as well telomere... And put them in variants for Clark et al ( 2011 ) folder higher total of... Able to detect a greater total number of variants obtained from GATK and VarScan with strict could. Function of the RefSeq, UCSC, Ensembl and other databases duplication level tools developed align. Calling with default parameters, identifying multi-allelic SNPs and indels of the number of WGS-specific variants not by... Annotate variants generated for each chromosome and patch ( if they are presented ) versa, there ~555,000! Such histogram is generated for each chromosome and patch ( if they are presented ) ) is a popular sequencing... To a purine or vice versa, there are significant advantages and limitations of both WES–specific... Rule out false positive variants target, if the targeted bases reached sufficient coverage, etc we see the percentage., J. and Wang, K. ( 2009 ) lower quartile is less than 400,000 for WES, and tools...

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