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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: e45ab1b9ac5c9b99fdf7b3b1be396dc42c2c9620

workflow graph xenbase-sra-to-fastq-se.cwl

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

Path: subworkflows/xenbase-sra-to-fastq-se.cwl

Branch/Commit ID: 2b8146f76595f0c4d8bf692de78b21280162b1d0

workflow graph mpi_simple_wf.cwl

Simple 2 step workflow to check that workflow steps are independently picking up on the number of processes. First run the parallel get PIDs step (on the input num procs) then run (on a single proc) the line count. This should equal the input.

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

Path: tests/wf/mpi_simple_wf.cwl

Branch/Commit ID: 2710cfe731374cf7244116dd7186fc2b6e4af344

workflow graph scatter GATK HaplotypeCaller over intervals

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

Path: definitions/subworkflows/gatk_haplotypecaller_iterator.cwl

Branch/Commit ID: a7838a5ca72b25db5c2af20a15f34303a839980e

workflow graph createindex.cwl

https://github.com/yyoshiaki/virtus.git

Path: workflow/createindex.cwl

Branch/Commit ID: 49faf55f97c8f3084b426d2db6640519d6f2ce71

workflow graph joint genotyping for trios or small cohorts

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

Path: definitions/subworkflows/joint_genotype.cwl

Branch/Commit ID: 061d3a2fbcd8a1c39c0b38c549e528deb24a9d54

workflow graph scatter-valuefrom-wf4.cwl#main

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

Path: cwltool/schemas/v1.0/v1.0/scatter-valuefrom-wf4.cwl

Branch/Commit ID: 03af16c9df2ee77485d4ab092cd64ae096d2e71c

Packed ID: main

workflow graph count-lines2-wf.cwl

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

Path: cwltool/schemas/v1.0/v1.0/count-lines2-wf.cwl

Branch/Commit ID: 3e9bca4e006eae7e9febd76eb9b8292702eba2cb

workflow graph hmmsearch_wnode and gpx_qdump combined workflow to apply scatter/gather

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

Path: task_types/tt_hmmsearch_wnode_plus_qdump.cwl

Branch/Commit ID: 146df33e2e44afa2a608ac72c036e6b6b871af93

workflow graph dynresreq-workflow.cwl

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

Path: cwltool/schemas/v1.0/v1.0/dynresreq-workflow.cwl

Branch/Commit ID: 3e9bca4e006eae7e9febd76eb9b8292702eba2cb