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Graph Name Retrieved From View
workflow graph QuantSeq 3' mRNA-Seq single-read

### Pipeline for Lexogen's QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina [Lexogen original documentation](https://www.lexogen.com/quantseq-3mrna-sequencing/) * Cost-saving and streamlined globin mRNA depletion during QuantSeq library preparation * Genome-wide analysis of gene expression * Cost-efficient alternative to microarrays and standard RNA-Seq * Down to 100 pg total RNA input * Applicable for low quality and FFPE samples * Single-read sequencing of up to 9,216 samples/lane * Dual indexing and Unique Molecular Identifiers (UMIs) are available ### QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina The QuantSeq FWD Kit is a library preparation protocol designed to generate Illumina compatible libraries of sequences close to the 3’ end of polyadenylated RNA. QuantSeq FWD contains the Illumina Read 1 linker sequence in the second strand synthesis primer, hence NGS reads are generated towards the poly(A) tail, directly reflecting the mRNA sequence (see workflow). This version is the recommended standard for gene expression analysis. Lexogen furthermore provides a high-throughput version with optional dual indexing (i5 and i7 indices) allowing up to 9,216 samples to be multiplexed in one lane. #### Analysis of Low Input and Low Quality Samples The required input amount of total RNA is as low as 100 pg. QuantSeq is suitable to reproducibly generate libraries from low quality RNA, including FFPE samples. See Fig.1 and 2 for a comparison of two different RNA qualities (FFPE and fresh frozen cryo-block) of the same sample. ![Fig 1](https://www.lexogen.com/wp-content/uploads/2017/02/Correlation_Samples.jpg) Figure 1 | Correlation of gene counts of FFPE and cryo samples. ![Fig 2](https://www.lexogen.com/wp-content/uploads/2017/02/Venn_diagrams.jpg) Figure 2 | Venn diagrams of genes detected by QuantSeq at a uniform read depth of 2.5 M reads in FFPE and cryo samples with 1, 5, and 10 reads/gene thresholds. #### Mapping of Transcript End Sites By using longer reads QuantSeq FWD allows to exactly pinpoint the 3’ end of poly(A) RNA (see Fig. 3) and therefore obtain accurate information about the 3’ UTR. ![Figure 3](https://www.lexogen.com/wp-content/uploads/2017/02/Read_Coverage.jpg) Figure 3 | QuantSeq read coverage versus normalized transcript length of NGS libraries derived from FFPE-RNA (blue) and cryo-preserved RNA (red). ### Current workflow should be used only with the single-end RNA-Seq data. It performs the following steps: 1. Separates UMIes and trims adapters from input FASTQ file 2. Uses ```STAR``` to align reads from input FASTQ file according to the predefined reference indices; generates unsorted BAM file and alignment statistics file 3. Uses ```fastx_quality_stats``` to analyze input FASTQ file and generates quality statistics file 4. Uses ```samtools sort``` and generates coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 2 (after running STAR) 5. Uses ```umi_tools dedup``` and generates final filtered sorted BAM(+BAI) file pair 6. Generates BigWig file on the base of sorted BAM file 7. Maps input FASTQ file to predefined rRNA reference indices using ```bowtie``` to define the level of rRNA contamination; exports resulted statistics to file 8. Calculates isoform expression level for the sorted BAM file and GTF/TAB annotation file using GEEP reads-counting utility; exports results to file

https://github.com/datirium/workflows.git

Path: workflows/trim-quantseq-mrnaseq-se.cwl

Branch/Commit ID: bf80c9339d81a78aefb8de661bff998ed86e836e

workflow graph protein annotation

Proteins - predict, filter, cluster, identify, annotate

https://github.com/MG-RAST/pipeline.git

Path: CWL/Workflows/protein-filter-annotation.workflow.cwl

Branch/Commit ID: 932da3abed7166bd5a962871386ba2c31d47b85c

workflow graph trnascan_wnode and gpx_qdump combined

https://github.com/ncbi/pgap.git

Path: bacterial_trna/wf_scan_and_dump.cwl

Branch/Commit ID: 55b6ee46b0c9fb1c9949cd0888b388c6f11b73b1

workflow graph pipeline_v2.cwl#openoil_pipeline

Animation of an oil spill with openoil

https://github.com/ILIAD-ocean-twin/application_package.git

Path: openoil/pipeline_v2.cwl

Branch/Commit ID: bdc301ea10f1a16e8db894c6a6115c829484f80e

Packed ID: openoil_pipeline

workflow graph varscan somatic workflow

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/varscan.cwl

Branch/Commit ID: 641083e9ed933d388f36fa04c00c20a810599e94

workflow graph workflow.cwl

https://github.com/NAL-i5K/Organism_Onboarding.git

Path: flow_create_genomics-workspace_yml/flow_create_yml/workflow.cwl

Branch/Commit ID: 096a9feffe292a1aeb329552661d27bb579e084c

workflow graph checkm_wnode

https://github.com/ncbi/pgap.git

Path: task_types/tt_checkm_wnode.cwl

Branch/Commit ID: 2d851682ba1bf2aaaacb3677253b55ceb59c8568

workflow graph count-lines10-wf.cwl

https://github.com/common-workflow-language/cwltool.git

Path: cwltool/schemas/v1.0/v1.0/count-lines10-wf.cwl

Branch/Commit ID: bfe56f3138e9e6fc0b9b8c06447553d4cea03d59

workflow graph align_and_count_multiple_report.cwl

https://github.com/common-workflow-lab/wdl-cwl-translator.git

Path: wdl2cwl/tests/cwl_files/align_and_count_multiple_report.cwl

Branch/Commit ID: e910788d1f62bf470cc71f19af0713b79893f4ee

workflow graph tt_univec_wnode.cwl

https://github.com/ncbi/pgap.git

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: 5282690e0f634a5f83107ba878fe62cbbb347408