Galaxy | Accessible Workflow | RNASeq FastQ to DESEQ

RNASeq FastQ to DESEQ

Annotation:

Step	Annotation
Step 1: Input dataset collection input select at runtime
Step 2: HISAT2 Source for the reference genome Use a built-in genome Select a reference genome hg38 Is this a single or paired library Paired-end Dataset Collection Paired Collection select at runtime Specify strand information Reverse (RF) Paired-end options Use default values Summary Options: Output alignment summary in a more machine-friendly style. True Print alignment summary to a file. False Advanced Options: Input options Use default values Alignment options Use default values Scoring options Use default values Spliced alignment options Specify spliced alignment options Penalty for canonical splice sites 0 Penalty for non-canonical splice sites 12 Penalty function for long introns with canonical splice sites Natural logarithm [f(x) = B + A * log(x)] Constant term (B) -8.0 Coefficient (A) 1.0 Penalty function for long introns with non-canonical splice sites Natural logarithm [f(x) = B + A * log(x)] Constant term (B) -8.0 Coefficient (A) 1.0 Minimum intron length 20 Maximum intron length 500000 Disable spliced alignment False GTF file with known splice sites select at runtime Transcriptome assembly reporting Report alignments tailored for transcript assemblers including StringTie Disable automatic template length adjustment for RNA-seq reads False Reporting options Use default values Output options Use default values Other options Use default values Job Resource Parameters Use default job resource parameters	Make sure to choose strand correctly after manual inspection with a preliminary mapping of one sample and filtering reads to view on IGV
Step 3: Input dataset input select at runtime
Step 4: Trimmomatic Single-end or paired-end reads? Paired-end (two separate input files) Input FASTQ file (R1/first of pair) Output dataset 'output' from step 1 Input FASTQ file (R2/second of pair) Output dataset 'output' from step 1 Perform initial ILLUMINACLIP step? True Select standard adapter sequences or provide custom? Standard Adapter sequences to use TruSeq3 (paired-ended, for MiSeq and HiSeq) Maximum mismatch count which will still allow a full match to be performed 2 How accurate the match between the two 'adapter ligated' reads must be for PE palindrome read alignment 30 How accurate the match between any adapter etc. sequence must be against a read 10 Minimum length of adapter that needs to be detected (PE specific/palindrome mode) 8 Always keep both reads (PE specific/palindrome mode)? True Trimmomatic Operations Trimmomatic Operation 1 Select Trimmomatic operation to perform Sliding window trimming (SLIDINGWINDOW) Number of bases to average across 4 Average quality required 20 Job Resource Parameters Use default job resource parameters	choose the right options for Paired-end vs single read adaptors
Step 5: Filter SAM or BAM, output SAM or BAM SAM or BAM file to filter Output dataset 'output_alignments' from step 2 Header in output Include header Minimum MAPQ quality score 20 Filter on bitwise flag yes Only output alignments with all of these flag bits set Read is paired Read is mapped in a proper pair Skip alignments with any of these flag bits set Nothing selected. Select alignments from Library Empty. Select alignments from Read Group Empty. Output alignments overlapping the regions in the BED file select at runtime Use inverse selection False Select regions (only used when the input is in BAM format) Empty. Select the output format BAM (-b)	BAM cleanup
Step 6: FastQC Short read data from your current history Output dataset 'fastq_out_paired' from step 4 Contaminant list select at runtime Submodule and Limit specifing file select at runtime
Step 7: StringTie Input mapped reads Output dataset 'output1' from step 5 Specify strand information Reverse (RF) Use a reference file to guide assembly? Do not use reference GTF/GFF3 Advanced Options: Output gene abundance estimation file? True Do not assemble any transcripts on these reference sequence(s) Empty. Name prefix for output transcripts Empty. Minimum isoform fraction 0.15 Minimum assembled transcript length 200 Minimum anchor length for junctions 10 Minimum junction coverage 1 Minimum bundle reads per bp coverage to consider for assembly 2 Gap between read mappings triggering a new bundle 50 Fraction of bundle allowed to be covered by multi-hit reads 0.95 Disable trimming of predicted transcripts based on coverage True Disable multi-mapping correction False Job Resource Parameters Use default job resource parameters	choose strand correctly Input the read name Prefix according to sample group if desired To make custom GFF
Step 8: StringTie merge Transcripts Output dataset 'output_gtf' from step 7 Reference annotation to include in the merging Output dataset 'output' from step 3 Minimum input transcript length to include in the merge 50 Minimum input transcript coverage to include in the merge 0 Minimum input transcript FPKM to include in the merge 1.0 Minimum input transcript TPM to include in the merge 1.0 Minimum isoform fraction 0.01 Gap between transcripts to merge together 250 Keep merged transcripts with retained introns False Job Resource Parameters Use default job resource parameters	But in order to distinguish between novel and existing transcripts we will need provide Stringtie merge with a list of known annotated transcripts. For mouse genome version used in this tutorial (mm10) such a list can be downloaded from a Galaxy Library as was described above. Now we can finally run Stringtie merge
Step 9: featureCounts Alignment file Output dataset 'output1' from step 5 Specify strand information Stranded (Reverse) Gene annotation file in your history Gene annotation file Output dataset 'out_gtf' from step 8 Output format Gene-ID "\t" read-count (MultiQC/DESeq2/edgeR/limma-voom compatible) Create gene-length file True Options for paired-end reads: Count fragments instead of reads Disabled; all reads/mates will be counted individually Only allow fragments with both reads aligned False Exclude chimeric fragments True Advanced options: GFF feature type filter exon GFF gene identifier transcript_id On feature level False Allow read to contribute to multiple features False Count multi-mapping reads/fragments Disabled; multi-mapping reads are excluded (default) Minimum mapping quality per read 12 Exon-exon junctions False Long reads False Count reads by read group False Largest overlap False Minimum bases of overlap 1 Minimum fraction (of read) overlapping a feature 0 Minimum fraction (of feature) overlapping a read 0 Read 5' extension 0 Read 3' extension 0 Reduce read to single position Leave the read as it is Only count primary alignments False Ignore reads marked as duplicate False Annotates the alignment file with 'XS:Z:'-tags to described per read or read-pair the corresponding assigned feature(s). False Ignore unspliced alignments False Job Resource Parameters Use default job resource parameters

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lho-w

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