This workflow constructs Metagenome-Assembled Genomes (MAGs) using SPAdes or MEGAHIT as assemblers, followed by binning with four different tools and refinement using Binette. The resulting MAGs are dereplicated across the entire input sample set, then annotated and evaluated for quality. You can provide pooled reads (for co-assembly/binning), individual read sets, or a combination of both. The input samples must consist of the original reads, which are used for abundance estimation. In all cases, ...

This workflows performs single end read mapping with bowtie2 followed by sensitive variant calling across a wide range of AFs with lofreq

This workflow takes as input a collection of paired fastqs. Remove adapters with cutadapt, map pairs with bowtie2. Keep MAPQ30 and concordant pairs. MACS2 for paired bam.

This workflow takes as input a collection of fastqs (single reads). Remove adapters with cutadapt, map with bowtie2. Keep MAPQ30. MACS2 for bam with fixed extension or model.

prepareChIPs

This is a simple snakemake workflow template for preparing single-end ChIP-Seq data. The steps implemented are:

1. Download raw fastq files from SRA
2. Trim and Filter raw fastq files using AdapterRemoval
3. Align to the supplied genome using bowtie2
4. Deduplicate Alignments using Picard MarkDuplicates
5. Call Macs2 Peaks using macs2

A pdf of the rulegraph is available here

Full details for each step are given below. Any additional ...

This workflow take as input a collection of paired fastq. Remove adapters with cutadapt, map pairs with bowtie2 allowing dovetail. Keep MAPQ30 and concordant pairs. BAM to BED. MACS2 with "ATAC" parameters.

This workflow take as input a collection of paired fastq. It will remove bad quality and adapters with cutadapt. Map with Bowtie2 end-to-end. Will remove reads on MT and unconcordant pairs and pairs with mapping quality below 30 and PCR duplicates. Will compute the pile-up on 5' +- 100bp. Will call peaks and count the number of reads falling in the 1kb region centered on the summit. Will plot the number of reads for each fragment length.

RNAseq workflow UMG: Here we introduce a scientific workflow implementing several open-source software executed by Galaxy parallel scripting language in an high-performance computing environment. We have applied the workflow to a single-cardiomyocyte RNA-seq data retrieved from Gene Expression Omnibus database. The workflow allows for the analysis (alignment, QC, sort and count reads, statistics generation) of raw RNA-seq data and seamless integration of differential expression results into a ...

ChIP-seq paired-end Workflow

Inputs dataset

• The workflow needs a single input which is a list of dataset pairs of fastqsanger.

Inputs values

• adapters sequences: this depends on the library preparation. If you don't know, use FastQC to determine if it is Truseq or Nextera.
• reference_genome: this field will be adapted to the genomes available for bowtie2.
• effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).

...

Objective. Biomarkers have become important for the prognosis and diagnosis of various diseases. High-throughput methods such as RNA-sequencing facilitate the detection of differentially expressed genes (DEGs), hence potential biomarker candidates. Individual studies suggest long lists of DEGs, hampering the identification of clinically relevant ones. Concerning preeclampsia, a major obstetric burden with high risk for adverse maternal and/or neonatal outcomes, limitations in diagnosis and ...