Citation Guidelines¶

When publishing results from SeqNado, please cite:

SeqNado itself (citation pending - check GitHub releases for latest version)
Key tools used in your specific analysis (see References section below)
Snakemake workflow manager: Mölder F, Jablonski KP, Letcher B, et al. Sustainable data analysis with Snakemake. F1000Research. 2021;10:33.
Reference genomes used (e.g., hg38, mm10)

Example Acknowledgment¶

"Data analysis was performed using SeqNado v1.0.2 (Chahrour, C and Smith, AL, 2024), which incorporates Bowtie2 (Langmead & Salzberg, 2012) for alignment, MACS2 (Zhang et al., 2008) for peak calling, and deepTools (Ramírez et al., 2016) for coverage track generation. Workflows were managed with Snakemake (Mölder et al., 2021) within Apptainer containers."

Tools¶

Tools are organized by category, matching the structure of the seqnado tools CLI command. For more information about any tool, use seqnado tools <toolname>.

Download¶

SRA Toolkit (fasterq-dump)¶

Purpose: Fast extraction of sequences from SRA files
Version: 3.0.10
Usage: Download sequencing data from NCBI Sequence Read Archive
Reference: National Center for Biotechnology Information. SRA Toolkit: Sequence Read Archive tools and libraries. 2023. https://github.com/ncbi/sra-tools.

Quality Control¶

FastQ Screen¶

Purpose: Screen sequencing reads against a set of databases
Version: 0.16.0
Usage: Screen reads against multiple reference genomes
Reference: Steven W. Wingett and Simon Andrews. FastQ Screen: A tool for multi-genome mapping and quality control. F1000Research, 7(1338):1338, 2018. https://doi.org/10.12688/f1000research.15931.2

FastQC¶

Purpose: Quality control for high-throughput sequencing data
Version: 0.12.1
Usage: Generate quality metrics for sequencing data
Reference: Simon Andrews. FastQC. 2010. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.

Qualimap¶

Purpose: Quality assessment tool for next-generation sequencing data
Version: 2.3
Usage: Compute alignment metrics and coverage statistics
Reference: Konstantin Okonechnikov, Ana Conesa, and Fernando García-Alcalde. Qualimap 2: advanced multi-sample quality control for high-throughput sequencing data. Bioinformatics, 32(2):292–294, 2016. https://doi.org/10.1093/bioinformatics/btv566

Preprocessing¶

Cutadapt¶

Purpose: Remove adapter sequences from sequencing reads
Version: 5.1
Usage: Remove adapter sequences and trim low-quality bases
Reference: Marcel Martin. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal, 17(1):10–12, 2011. https://doi.org/10.14806/ej.17.1.200

FLASH¶

Purpose: Fast length adjustment of short reads (FLASH) to improve genome assemblies
Version: 1.2.11
Usage: Merge overlapping paired-end reads
Reference: Tanja Magoč and Steven L. Salzberg. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics, 27(21):2957–2963, 2011. https://doi.org/10.1093/bioinformatics/btr507

Trim Galore¶

Purpose: Wrapper around Cutadapt and FastQC for quality and adapter trimming
Version: 0.6.10
Usage: Combines Cutadapt with quality control
Reference: Felix Krueger. Trim galore. 2023. https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/.

Alignment¶

Bowtie2¶

Purpose: Fast and sensitive read mapping to large genomes
Version: 2.5.4
Usage: Align reads to reference genomes
Reference: Ben Langmead and Steven L. Salzberg. Fast gapped-read alignment with Bowtie 2. Nature Methods, 9(4):357–359, 2012. https://doi.org/10.1038/nmeth.1923

minimap2¶

Purpose: Fast pairwise sequence alignment tool
Version: 2.30
Usage: Fast alignment for long reads (PacBio/Nanopore)
Reference: Heng Li. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics, 34(18):3094–3100, 2018. https://doi.org/10.1093/bioinformatics/bty191

Picard¶

Purpose: Tools for manipulating high-throughput sequencing data and formats
Version: 3.4.0
Usage: Duplicate marking and BAM processing
Reference: Picard toolkit. 2019. https://broadinstitute.github.io/picard/.

SAMtools¶

Purpose: Tools for interacting with SAM/BAM format files
Version: 1.22.1
Usage: Sorting, indexing, filtering SAM/BAM files
Reference: Petr Danecek, James K Bonfield, Jennifer Liddle, John Marshall, Valeriu Ohan, Martin O Pollard, Andrew Whitwham, Thomas Keane, Shane A McCarthy, Robert M Davies, and Heng Li. Twelve years of SAMtools and BCFtools. GigaScience, 10(2):giab008, 2021. https://doi.org/10.1093/gigascience/giab008

STAR¶

Purpose: Ultrafast universal RNA-seq aligner
Version: 2.7.11b
Usage: High-speed splicing-aware RNA-seq alignment
Reference: Alexander Dobin, Carrie A. Davis, Felix Schlesinger, Jorg Drenkow, Chris Zaleski, Sonali Jha, Philippe Batut, Mark Chaisson, and Thomas R. Gingeras. STAR: ultrafast universal RNA-seq aligner. Bioinformatics, 29(1):15–21, 2013. https://doi.org/10.1093/bioinformatics/bts635

Analysis¶

BamNado¶

Purpose: SeqNado BAM file manipulation and analysis tool
Version: 0.4.4
Usage: Calculate scaling factors and spike-in normalization
Reference: Smith, Alastair L. BamNado: BAM file manipulation and analysis tool. 2024. https://pypi.org/project/bamnado/.

BCFtools¶

Purpose: Tools for BCF/VCF format variant files
Version: 1.22
Usage: Process VCF/BCF variant files
Reference: Petr Danecek, James K Bonfield, Jennifer Liddle, John Marshall, Valeriu Ohan, Martin O Pollard, Andrew Whitwham, Thomas Keane, Shane A McCarthy, Robert M Davies, and Heng Li. Twelve years of SAMtools and BCFtools. GigaScience, 10(2):giab008, 2021. https://doi.org/10.1093/gigascience/giab008

BEDTools¶

Purpose: Tools for genomic arithmetic and feature analysis
Version: 2.31.1
Usage: Genomic interval manipulation and analysis
Reference: Aaron R. Quinlan and Ira M. Hall. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics, 26(6):841–842, 2010. https://doi.org/10.1093/bioinformatics/btq033

Cooler¶

Purpose: Tools for high-resolution interactions and HiC contact matrices
Version: 0.10.4
Usage: Handle genomically-labeled arrays and Hi-C data
Reference: Nezar Abdennur and Leonid A. Mirny. Cooler: scalable storage for Hi-C data and other genomically labeled arrays. Bioinformatics, 36(1):311–316, 2020. https://doi.org/10.1093/bioinformatics/btz540

findPeaks (HOMER)¶

Purpose: Identify genomic peaks in ChIP-seq or ATAC-seq data (HOMER)
Version: 5.1
Usage: Identify genomic peaks in ChIP-seq or ATAC-seq data
Reference: Sven Heinz, Christopher Benner, Nathanael Spann, Eric Bertolino, Yin C. Lin, Peter Laslo, Jason X. Cheng, Cornelis Murre, Harinder Singh, and Christopher K. Glass. Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities. Molecular Cell, 38(4):576–589, 2010. https://doi.org/10.1016/j.molcel.2010.05.004

HOMER¶

Purpose: Tools for ChIP-seq, DNase-seq, and other genomic analysis
Version: 5.1
Usage: Peak calling, motif discovery, annotation
Reference: Sven Heinz, Christopher Benner, Nathanael Spann, Eric Bertolino, Yin C. Lin, Peter Laslo, Jason X. Cheng, Cornelis Murre, Harinder Singh, and Christopher K. Glass. Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities. Molecular Cell, 38(4):576–589, 2010. https://doi.org/10.1016/j.molcel.2010.05.004

LanceOtron¶

Purpose: Peak caller for high-resolution chromatin analysis
Version: 1.2.7
Usage: Machine learning-based peak calling
Reference: Lance D Hentges, Martin J Sergeant, Christopher B Cole, Damien J Downes, Jim R Hughes, and Stephen Taylor. LanceOtron: a deep learning peak caller for genome sequencing experiments. Bioinformatics, pages btac525, 2022. https://doi.org/10.1093/bioinformatics/btac525

MACS2¶

Purpose: Model-based analysis of ChIP-Seq data
Version: 2.2.9.1
Usage: Peak calling for ChIP-seq and ATAC-seq
Reference: Yong Zhang, Tao Liu, Clifford A Meyer, Jérôme Eeckhoute, David S Johnson, Bradley E Bernstein, Chad Nusbaum, Richard M Myers, Myles Brown, Wei Li, and X Shirley Liu. Model-based analysis of ChIP-seq (MACS). Genome Biology, 9(9):R137, 2008. https://doi.org/10.1186/gb-2008-9-9-r137

MAGeCK¶

Purpose: Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout data
Version: 0.5.9.5
Usage: CRISPR screen analysis for essential gene identification
Reference: Wei Li, Han Xu, Tengfei Xiao, Le Cong, Michael I Love, Feng Zhang, Rafael A Irizarry, Jun S Liu, Myles Brown, and X Shirley Liu. MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens. Genome Biology, 15(12):554, 2014. https://doi.org/10.1186/s13059-014-0554-4

makeTagDirectory (HOMER)¶

Purpose: Prepare and organize ChIP-seq tag directories (HOMER)
Version: 5.1
Usage: Prepare and organize ChIP-seq tag directories
Reference: Sven Heinz, Christopher Benner, Nathanael Spann, Eric Bertolino, Yin C. Lin, Peter Laslo, Jason X. Cheng, Cornelis Murre, Harinder Singh, and Christopher K. Glass. Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities. Molecular Cell, 38(4):576–589, 2010. https://doi.org/10.1016/j.molcel.2010.05.004

MCCNado¶

Purpose: Micro-Capture-C (MCC) sequencing data processing tool
Version: 0.1.6
Usage: Analyze chromatin 3D interactions (Micro-Capture-C)
Reference: Alastair L. Smith. MCCNado: Micro-Capture-C data processing tool. 2024. https://pypi.org/project/mccnado.

MEME Suite¶

Purpose: MEME Suite motif discovery and analysis tools
Version: 5.5.9
Usage: DNA motif discovery and analysis
Reference: T. L. Bailey, M. Boden, F. A. Buske, M. Frith, C. E. Grant, L. Clementi, J. Ren, W. W. Li, and W. S. Noble. Meme SUITE: tools for motif discovery and searching. Nucleic Acids Research, 37(Web Server):W202–W208, 2009. https://doi.org/10.1093/nar/gkp335

MethylDackel¶

Purpose: Tools for analyzing DNA methylation from bisulfite sequencing data
Version: 0.6.1
Usage: Extract methylation metrics from bisulfite-seq
Reference: Devon Ryan. MethylDackel. 2021. https://github.com/dpryan79/MethylDackel.

SEACR¶

Purpose: Sparse enrichment analysis for CUT&RUN
Version: 1.3
Usage: Peak calling optimized for CUT&Tag/CUT&RUN
Reference: Michael P. Meers, Dan Tenenbaum, and Steven Henikoff. Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling. Epigenetics & Chromatin, 12(1):42, 2019. https://doi.org/10.1186/s13072-019-0287-4

Visualization¶

deepTools¶

Purpose: Tools for processing and visualizing deep sequencing data
Version: 3.5.6
Usage: BigWig generation, heatmaps, and profile plots
Reference: Fidel Ramírez, Devon P Ryan, Björn Grüning, Vivek Bhardwaj, Fabian Kilpert, Andreas S Richter, Steffen Heyne, Friederike Dündar, and Thomas Manke. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Research, 44(W1):W160–W165, 2016. https://doi.org/10.1093/nar/gkw257

PlotNado¶

Purpose: SeqNado genome browser visualization and plotting tool
Version: 0.1.dev101
Usage: Publication-ready genomic region visualizations
Reference: Alastair L. Smith. PlotNado: genome browser visualization tool. 2023. https://github.com/alsmith151/plotnado.

trackhub¶

Purpose: Python library to work with track hubs
Version: 1.0
Usage: UCSC Genome Browser track hub library
Reference: Ryan K. Dale, Laura H. Matzat, and Elissa P. Lei. Trackhub: A Library for creating and remotely hosting UCSC Genome Browser track hubs. F1000Research, 10:121, 2021. https://doi.org/10.12688/f1000research.50107.2

TrackNado¶

Purpose: Track hub creation tool for UCSC Genome Browser
Version: ≥0.3.1
Usage: Create and host UCSC track hubs
Reference: Alastair L. Smith. TrackNado: a python library and cli tool to rapidly generate complex ucsc genome browser track hubs. 2024. https://pypi.org/project/tracknado.

Reporting¶

MultiQC¶

Purpose: Aggregate quality control reports from multiple QC tools
Version: 1.31
Usage: Aggregate QC reports across samples into interactive HTML
Reference: Philip Ewels, Måns Magnusson, Sverker Lundin, and Max Käller. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics, 32(19):3047–3048, 2016. https://doi.org/10.1093/bioinformatics/btw354

Quarto¶

Purpose: Scientific and technical publishing system for reports
Version: 1.8.25
Usage: Generate analysis reports with code and narrative
Reference: Posit Software, PBC. Quarto: An open-source scientific and technical publishing system. 2022. https://quarto.org/.

Quantification¶

featureCounts¶

Purpose: Count reads overlapping genomic features (genes/exons)
Version: 2.1.1
Usage: Gene-level read quantification for RNA-seq
Reference: Yang Liao, Gordon K. Smyth, and Wei Shi. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics, 30(7):923–930, 2014. https://doi.org/10.1093/bioinformatics/btt656

QuantNado¶

Purpose: SeqNado multiomics quantification and dataset creation tool
Version: 0.2.5
Usage: Generate quantified datasets for ML analysis
Reference: Catherine Chahrour and Alastair L. Smith. QuantNado: multiomics machine learning dataset generation tool. 2024. https://pypi.org/project/QuantNado.

Salmon¶

Purpose: Quantification of gene expression from RNA-seq data
Version: 1.10.3
Usage: Alignment-free transcript quantification
Reference: Rob Patro, Geet Duggal, Michael I. Love, Rafael A. Irizarry, and Carl Kingsford. Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods, 14(4):417–419, 2017. https://doi.org/10.1038/nmeth.4197

Subread¶

Purpose: High-performance read alignment, quantification and mutation discovery
Version: 2.1.1
Usage: High-performance read alignment and quantification
Reference: Yang Liao, Gordon K. Smyth, and Wei Shi. The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote. Nucleic Acids Research, 41(10):e108, 2013. https://doi.org/10.1093/nar/gkt214

Utilities¶

Apptainer¶

Purpose: Container runtime for running Singularity/Apptainer images on HPC clusters
Version: User-managed (see installation docs)
Usage: Run containerized tools in HPC environments
Reference: Apptainer Project Contributors. Apptainer. 2023. https://apptainer.org/.

bedToBigBed¶

Purpose: Convert BED format files to compressed BigBed format
Version: 482
Usage: Convert BED to BigBed format
Reference: W. James Kent, Charles W. Sugnet, Terrence S. Furey, Krishna M. Roskin, Tom H. Pringle, Alan M. Zahler, and David Haussler. The human genome browser at UCSC. Genome Research, 12(5):996–1006, 2002. https://doi.org/10.1101/gr.229102

pigz¶

Purpose: Parallel gzip compression utility
Version: 2.8
Usage: Fast parallel compression/decompression
Reference: Mark Adler. Pigz: Parallel Implementation of GZip. 2015. https://zlib.net/pigz/.

Snakemake¶

Purpose: Workflow management system for reproducible and scalable data analysis
Version: 9.14.5
Usage: Workflow management and execution
Reference: Felix Mölder, Kim Philipp Jablonski, Brice Letcher, Michael B. Hall, Christopher H. Tomkins-Tinch, Vanessa Sochat, Jan Forster, Soohyun Lee, Sven O. Twardziok, Alexander Kanitz, Andreas Wilm, Manuel Holtgrewe, Sven Rahmann, Sven Nahnsen, and Johannes Köster. Sustainable data analysis with Snakemake. F1000Research, 10:33, 2021. https://doi.org/10.12688/f1000research.29032.3

UCSC Tools¶

Purpose: UCSC genome browser command-line utilities
Version: 482
Usage: BigWig creation and genomic format conversion
Reference: W. James Kent, Charles W. Sugnet, Terrence S. Furey, Krishna M. Roskin, Tom H. Pringle, Alan M. Zahler, and David Haussler. The human genome browser at UCSC. Genome Research, 12(5):996–1006, 2002. https://doi.org/10.1101/gr.229102