http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#Head http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8 http://www.nanopub.org/nschema#hasAssertion http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#assertion http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8 http://www.nanopub.org/nschema#hasProvenance http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#provenance http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8 http://www.nanopub.org/nschema#hasPublicationInfo http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#pubinfo http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#assertion http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#config-1 http://purl.org/dc/terms/identifier config.yml http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#config-1 https://schema.org/text ## General Workflow Parameters: # sample information and experimental design samples: samples.csv ## Workflow-specific Parameters: # Define reference genome/transcriptome ref: species: "Drosophila melanogaster" # Local reference data # Genome file path (supported extensions: .fa, .fna, .fasta, case-insensitive) # may be a path or left empty, if download using an accession number is preferred genome: "" # Annotation file (supported extensions: .gff, .gtf, case-insensitive) # may be a path or left empty, if download using an accession number is preferred annotation: "" # Remote reference data # NCBI accession number of the reference data set; can be left empty if both reference files are available locally" #accession: "GCF_000001215.2" accession: "GCF_000001215.4" ensembl_species: "" # e.g., "homo_sapiens" build: "" # e.g., "GRCh38" release: "" # e.g., "105" read_filter: # Minimum read length; set 0 to keep all reads. min_length: 200 # minimap2 alignment parameters minimap2: # Minimap2 indexing options index_opts: "" # Minimap2 mapping options opts: "" # Maximum secondary alignments maximum_secondary: 100 # Secondary score ratio (-p for minimap2) secondary_score_ratio: 1.0 # samtools processing parameters samtools: # Samtools view opts, "-b" creates BAM from SAM. samtobam_opts: "-b" # Samtools sort opts, bamsort_opts: "" # Samtools index opts, bamindex_opts: "" # Samtools stats opts bamstats_opts: "" # salmon quantification parameters quant: # Salmon library type (Default: U) salmon_libtype: "U" # This section defines the pyDESeq2 plot and data handling parameters deseq2: # normalization fit type, must be 'parametric' or 'mean' fit_type: "" # the "design factors" are the confounding variables to be adjusted for # during normalization. They must be given in the configuration (samples.csv). design_factors: - "condition" # # the "continuous factors" are non-categorial factors to be considered #continuous_factors: # - # # The (log2) log fold change under the null hypothesis. (default: 0). lfc_null: 1.0 # # The alternative hypothesis for computing wald p-values. By default, # the normal Wald test assesses deviation of the estimated log fold # change from the null hypothesis, as given by lfc_null. # One of ["greaterAbs", "lessAbs", "greater", "less"] or None. # The alternative hypothesis corresponds to what the user wants to # find rather than the null hypothesis. (default: None). alt_hypothesis: "greaterAbs" # # The marker size in points**2 (typographic points are 1/72 in.). # Default is rcParams['lines.markersize'] ** 2.# minimum count to # be considered for subsequent analysis point_width: 20 # # we disregard loci with count number lower 'mincount' mincount: 10 # # Type I error cutoff value: alpha: 0.05 # # in addition to the full heatmap, plot the top number of different # values, ranked by the top ratio between the two traits threshold_plot: 10 # # the heatmap color map # see https://seaborn.pydata.org/tutorial/color_palettes.htm for an overview colormap: "Blues" #plot figure type figtype: "png" batch_effect: - "" # ## Differential Isoform Analysis # The FLAIR splice-isoform analysis pipeline includes resource-intensive computations and only works with additional constraints. # 1. In 'samples.csv: The 'condition' column must contain exactly two distinct values. For example 'control' and 'treated'. # 2. In 'samples.csv: Refrain from using underscores when naming samples. The 'sample' column may contain underscores, but be aware that underscores will be removed from the name for isoform quantification steps. # 3. In this file: the variable 'FLAIR' below must be:'true'. This is a check to determine if users are aware of the constraints and wish to proceed. isoform_analysis: # Enables FLAIR Isoform Analysis if 'true' FLAIR: true # Minimum MAPQ of read assignment to an isoform (default: 1). qscore: 1 # min read count expression threshold. Isoforms which contain fewer than 'exp_thresh' (Default=10) reads in both conditions are filtered out. exp_thresh: 10 # 'flair_collapse' options # '--annotation-reliant' makes FLAIR align reads to the annotation before identifying novel transcripts for the remaining reads # '--generate-map' to generate a txt file of read-isoform assignments # '--stringent' for full-length supporting reads (>=80% coverage) col_opts: "--annotation_reliant generate --generate_map --stringent" # Query genes to identify similar proteins using "lambda" protein_annotation: # Enables lambda sequence alignment if 'true' lambda: false # Pre-formatted UniProt Reference Cluster database (default: UniRef50) uniref: "https://ftp.imp.fu-berlin.de/pub/lambda/index/lambda3/gen_0/uniref50_20230713.lba.gz" # maximum number of protein matches returned per sequence (default: 3) num_matches: 3 # Enrichment Analysis Parameters #enrichment: # # Enable enrichment analysis if 'true' # perform_enrichment: true # # minimum number of genes to consider per pathway (default: 3) # min_genes: 3 http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#dataset http://www.w3.org/1999/02/22-rdf-syntax-ns#type https://schema.org/Dataset http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#dataset https://w3id.org/np/snakemake/describesWorkflow RAjHDlPDghZzc9ZvQ3uJQNJ9Jd_KAYzZt7dk5PXKgjRyE http://purl.org/np/RAG04Vs_yQL0sVxWgBd5JQ3sF0F-RPRFN3W7VT4tv5AT8#dataset https://w3id.org/np/snakemake/description This workflow performs differential expression analysis of RNA-seq data obtained from Oxford Nanopore long-read sequencing technology. First a transcriptome FASTA is constructed using gffread. Reads are then mapped to the transcriptome with the long-read optimized alignment tool minimap2. Next quantification is performed using salmon before normalization and differential expression analysis are conducted by PyDESeq2. The workflow can optionally analyze splice-isoforms through integrating the FLAIR workflow. 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