Welcome to the ERGA Space!

Here we collect, curate and develop pipelines to assemble and annotation reference-quality genomes for all eukaryotic life.

For Genome Assembly pipelines head to our Assembly Team

For Genome Annotation pipelines head to our Annotation Team

Development, discussions and issue tracking takes place in the ERGA github repo

If you would like to join ...

HiC scaffolding pipeline

Snakemake pipeline for scaffolding of a genome using HiC reads using yahs.

Prerequisites

This pipeine has been tested using Snakemake v7.32.4 and requires conda for installation of required tools. To run the pipline use the command:

snakemake --use-conda --cores N

where N is number of cores to use. There are provided a set of configuration and running scripts for exectution on a slurm queueing system. After configuring the cluster.json file run:

./run_cluster ...

Purge dups

This snakemake pipeline is designed to be run using as input a contig-level genome and pacbio reads. This pipeline has been tested with snakemake v7.32.4. Raw long-read sequencing files and the input contig genome assembly must be given in the config.yaml file. To execute the workflow run:

snakemake --use-conda --cores N

Or configure the cluster.json and run using the ./run_cluster command

HiC contact map generation

Snakemake pipeline for the generation of .pretext and .mcool files for visualisation of HiC contact maps with the softwares PretextView and HiGlass, respectively.

Prerequisites

This pipeine has been tested using Snakemake v7.32.4 and requires conda for installation of required tools. To run the pipline use the command:

snakemake --use-conda

There are provided a set of configuration and running scripts for exectution on a slurm queueing system. After configuring ...

The workflow takes a paired-reads collection (like illumina WGS or HiC), runs FastQC and SeqKit, trims with Fastp, and creates a MultiQC report. The main outputs are a paired collection of trimmed reads, a report with raw and trimmed reads stats, and a table with raw reads stats.

The workflow takes raw ONT reads and trimmed Illumina WGS paired reads collections, the ONT raw stats table (calculated from WF1) and the estimated genome size (calculated from WF1) to run NextDenovo and subsequently polish the assembly with HyPo. It produces collapsed assemblies (unpolished and polished) and runs all the QC analyses (gfastats, BUSCO, and Merqury).

The workflow takes raw ONT reads and trimmed Illumina WGS paired reads collections, and the estimated genome size and Max depth (both calculated from WF1) to run Flye and subsequently polish the assembly with HyPo. It produces collapsed assemblies (unpolished and polished) and runs all the QC analyses (gfastats, BUSCO, and Merqury).

CLAWS (CNAG's Long-read Assembly Workflow in Snakemake)

Snakemake Pipeline used for de novo genome assembly @CNAG. It has been developed for Snakemake v6.0.5.

It accepts Oxford Nanopore Technologies (ONT) reads, PacBio HFi reads, illumina paired-end data, illumina 10X data and Hi-C reads. It does the preprocessing of the reads, assembly, polishing, purge_dups, scaffodling and different evaluation steps. By default it will preprocess the reads, run Flye + Hypo + purge_dups + yahs and evaluate ...

The workflow takes trimmed HiC forward and reverse reads, and one assembly (e.g.: Hap1 or Pri or Collapsed) to produce a scaffolded assembly using YaHS. It also runs all the QC analyses (gfastats, BUSCO, and Merqury).

The workflow takes a trimmed Illumina WGS paired-end reads collection, Collapsed contigs, and the values for transition parameter and max coverage depth (calculated from WF1) to run Purge_Dups. It produces purged Collapsed contigs assemblies, and runs all the QC analysis (gfastats, BUSCO, and Merqury).

The workflow takes a trimmed Illumina paired-end reads collection, runs Meryl to create a K-mer database, Genomescope2 to estimate genome properties and Smudgeplot to estimate ploidy. The main results are K-mer ddatabase and genome profiling plots, tables, and values useful for downstream analysis. Default K-mer length and ploidy for Genomescope are 21 and 2, respectively.

The workflow takes ONT reads collection, runs SeqKit and Nanoplot. The main outputs are a table and plots of raw reads stats.

The workflow takes a trimmed HiFi reads collection, Hap1/Hap2 contigs, and the values for transition parameter and max coverage depth (calculated from WF1) to run Purge_Dups. It produces purged Hap1 and Hap2 contigs assemblies, and runs all the QC analysis (gfastats, BUSCO, and Merqury).

The workflow takes trimmed HiC forward and reverse reads, and Hap1/Hap2 assemblies to produce Hap1 and Hap2 scaffolded assemblies using YaHS. It also runs all the QC analyses (gfastats, BUSCO, Merqury and Pretext).

The workflow takes a trimmed HiFi reads collection, Forward/Reverse HiC reads, and the max coverage depth (calculated from WF1) to run Hifiasm in HiC phasing mode. It produces both Pri/Alt and Hap1/Hap2 assemblies, and runs all the QC analysis (gfastats, BUSCO, and Merqury). The default Hifiasm purge level is Light (l1).

The workflow takes a trimmed HiFi reads collection, runs Meryl to create a K-mer database, Genomescope2 to estimate genome properties and Smudgeplot to estimate ploidy. The main results are K-mer database and genome profiling plots, tables, and values useful for downstream analysis. Default K-mer length and ploidy for Genomescope are 21 and 2, respectively.

The workflow takes a HiFi reads collection, runs FastQC and SeqKit, filters with Cutadapt, and creates a MultiQC report. The main outputs are a collection of filtred reads, a report with raw and filtered reads stats, and a table with raw reads stats.

Collection of workflows designed to assembled a set of PacBio HiFi and Illumina HiC reads into a chromosome-scale de-novo assembly.

Development versions of these pipelines can be found in the ERGA github and any questions or queries can be raised on the ERGA Discussions Channel

Want to find out more about the work done by ERGA? Become a member ...

Collection of de-novo genome assembly workflows written for implementation in Galaxy

Input data should be Oxford Nanopore raw reads plus Illumina WGS reads and Illumina 3-dimensional Chromatin Confirmation Capture (HiC) reads

Executing all workflows will output one scaffolded collapsed assembly and the complete QC analyses

Please run the workflows in order: WF0 (there are two, one for ONT, and another one for Illumina that can be used independently for the WGS and HiC reads), WF1, WF2, WF3, WF4

Collection of de-novo genome assembly workflows written for implementation in Galaxy

Input data should be Oxford Nanopore raw reads plus Illumina WGS reads and Illumina 3-dimensional Chromatin Confirmation Capture (HiC) reads

Executing all workflows will output one scaffolded collapsed assembly and the complete QC analyses

Please run the workflows in order: WF0 (there are two, one for ONT, and another one for Illumina that can be used independently for the WGS and HiC reads), WF1, WF2, WF3, WF4

Collection of de-novo genome assembly workflows written for implementation in Galaxy

Input data should be PacBio HiFi reads and Illumina 3-dimensional Chromatin Confirmation Capture (HiC) reads

Executing all workflows will output two scaffolded haplotype assemblies and the complete QC analyses

Please run the workflows in order: WF0 (there are two, one for HiFi and one for Illumina HiC), WF1, WF2, WF3, WF4