The NCBI Datasets datasets command line tools are datasets and dataformat .

Use datasets to download biological sequence data across all domains of life from NCBI.

Use dataformat to convert metadata from JSON Lines format to other formats.

Conda download:

https://anaconda.org/conda-forge/ncbi-datasets-cli

Buld Download

 https://www.ncbi.nlm.nih.gov/datasets/builder/?tax_id=29979

Address of the bookmark: https://www.ncbi.nlm.nih.gov/datasets/docs/v1/quickstarts/command-line-tools/

https://www.readcube.com/articles/10.3390%2Fv9040072

Address of the bookmark: https://pubmed.ncbi.nlm.nih.gov/28387730/

• hist: Create an histogram of k-mer occurrences from a sequence file. Adds metadata in output for easy plotting.
• gcp: K-mer GC Processor. Creates a matrix of the number of K-mers found given a GC count and a K-mer count.
• comp: K-mer comparison tool. Creates a matrix of shared K-mers between two (or three) sequence files or hashes.
• sect: SEquence Coverage estimator Tool. Estimates the coverage of each sequence in a file using K-mers from another sequence file.
• blob: Given, reads and an assembly, calculates both the read and assembly K-mer coverage along with GC% for each sequence in the assembly.SEquence Coverage estimator Tool.
• filter: Filtering tools. Contains tools for filtering k-mer hashes and FastQ/A files:
  • kmer: Produces a k-mer hash containing only k-mers within specified coverage and GC tolerances.
  • seq: Filters a sequence file based on whether or not the sequences contain k-mers within a provided hash.
• plot: Plotting tools. Contains several plotting tools to visualise K-mer and compare distributions. The following plot tools are available:
  • density: Creates a density plot from a matrix created with the "comp" tool. Typically this is used to compare two K-mer hashes produced by different NGS reads.
  • profile: Creates a K-mer coverage plot for a single sequence. Takes in fasta coverage output coverage from the "sect" tool
  • spectra-cn: Creates a stacked histogram using a matrix created with the "comp" tool. Typically this is used to compare a jellyfish hash produced from a read set to a jellyfish hash produced from an assembly. The plot shows the amount of distinct K-mers absent, as well as the copy number variation present within the assembly.
  • spectra-hist: Creates a K-mer spectra plot for a set of K-mer histograms produced either by jellyfish-histo or kat-histo.
  • spectra-mx: Creates a K-mer spectra plot for a set of K-mer histograms that are derived from selected rows or columns in a matrix produced by the "comp".

In addition, KAT contains a python script for analysing the mathematical distributions present in the K-mer spectra in order to determine how much content is present in each peak.

This README only contains some brief details of how to install and use KAT. For more extensive documentation please visit: https://kat.readthedocs.org/en/latest/

https://academic.oup.com/bioinformatics/article/33/4/574/2664339 

Address of the bookmark: https://github.com/TGAC/KAT

Sequence Analysis and General Bioinformatics

• BLAST, Ian Korf, Mark Yandell, Joseph Bedell, 2003, O'Reilly
• Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases, Scott Markel, Darryl Leon, 2003, O'Reilly
• Bioinformatics for Geneticists, Michael Barnes, Ian C Gray (Editors), 2003, John Wiley & Sons
• Bioinformatics for Dummies, Jean-Michel Claverie, Cedric Notredame, 2003, John Wiley & Sons
• Mathematics of Genome Analysis, Jerome K. Percus, 2002, Cambridge Univ Press
• Bioinformatics Computing, Bryan P. Bergeron, 2002, Prentice Hall
• Evolutionary Computation in Bioinformatics, Gary B. Fogel, David W. Corne (Editors), 2002, Morgan Kaufmann
• Introduction to Bioinformatics, Arthur M. Lesk, 2002, Oxford University Press
• Instant Notes in Bioinformatics, D.R. Westhead, J. H. Parish, R.M. Twyman, 2002, Bios Scientific Pub
• Fundamental Concepts of Bioinformatics, Dan E. Krane, Michael L. Raymer, Michaeel L. Raymer, Elaine Nicpon Marieb, 2002, Benjamin/Cummings
• Essentials of Genomics and Bioinformatics, C. W. Sensen (Editor), 2002, John Wiley & Sons
• Current Topics in Computational Molecular Biology (Computational Molecular Biology), Tao Jiang, Ying Xu, Michael Zhang (Editors), 2002, MIT Press
• Hidden Markov Models for Bioinformatics, Timo Koski, Timo Koskinen, 2001, Kluwer Academic Publishers
• Bioinformatics: From Genomes to Drugs, Thomas Lengauer (Editor), 2001, John Wiley & Sons
• Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health), Warren Ewens, Gregory Grant, 2001, Springer Verlag
• Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, Second Edition, Andreas D. Baxevanis, B. F. Francis Ouellette, 2001, Wiley-Interscience
• Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning), Pierre Baldi, Soren Brunak, Sren Brunak, 2001, MIT Press
• Introduction to Bioinformatics, T eresa Attwood, David Parry-Smith, 2001, Prentice Hall
• Bioinformatics: A Primer, Charles Staben, 2001, Jones & Bartlett Pub
• Data Analysis and Classification for Bioinformatics, Arun Jagota, 2000, AKJ Academics
• Bioinformatics: Sequence and Genome Analysis, David W. Mount, 2001, Cold Spring Harbor Laboratory Press
• Bioinformatics: A Biologist's Guide to Biocomputing and the Internet, Stuart M. Brown, 2000, Eaton Pub Co
• Bioinformatics: Sequence, Structure and Databanks: A Practical Approach (The Practical Approach Series, 236), Des Higgins (Editor), Willie Taylor (Editor), 2000, Oxford Univ Press
• Neural Networks and Genome Informatics, Cathy H. Wu, Jerry W. McLarty, 2000, Elsevier Science
• Computational Molecular Biology: An Introduction (Wiley Series in Mathematical and Computational Biology), Peter Clote and Rolf Backofen, 2000, John Wiley & Sons
• Computational Molecular Biology: An Algorithmic Approach, Pavel A. Pevzner, 2000, MIT Press
• Post-Genome Informatics, Minoru Kanehisa, 2000, Oxford Univ Press
• Mathematical and Computational Biology: Computational Morphogenesis, Hierarchical Complexity, and Digital Evolution, Chrystopher L. Nehaniv, 1999, American Mathematical Society
• Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications, Jason T. L. Wang, Bruce A. Shapiro, Dennis Elliott Shasha (Editors), 1999, Oxford Univ Press
• Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison, David Sankoff and Joseph Kruskal (Editors), 1999, Cambridge University Press
• Bioinformatics Basics: Applications in Biological Science and Medicine, Hooman Rashidi, 1999, CRC Press
• Bioinformatics: Methods and Protocols (Methods in Molecular Biology, Vol 132), Stephen Misener and Stephen A. Krawetz (Editors),1999, Humana Press
• Bioinformatics: Databases and Systems, Stanley Letovsky (Editor),1999, Kluwer Academic Publishers
• Computational Molecular Biology, P. Green, 1998, Blackwell Science Inc.
• Computational Methods in Molecular Biology (New Comprehensive Biochemistry, V. 32), Steven L. Salzberg, David B. Searls, Simon Kasif (Editors), 1998, Elsevier Science Ltd.
• Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Richard Durbin, S. Eddy, A. Krogh, G. Mitchison, 1998, Cambridge University Press
• Guide to Human Genome Computing, M. J. Bishop (Editor), 1998, Academic Press
• Introduction to Computational Molecular Biology, Joao Meidanis, Joao C. Setabal, 1997, PWS Pub. Co.
• Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology, Dan Gusfield, 1997, Cambridge University Press
• Sequence Data Analysis Guidebook, Simon R. Swindell (Editor), 1997, Humana Press
• High Performance Computational Methods for Biological Sequence Analysis, Tieng K. Yap, Ophir Frieder, Robert L. Martino, 1996, Kluwer Academic Pub.
• Computer Methods for Macromolecular Sequence Analysis, Methods in Enzymology, volume 266, Russell F. Doolittle (Editor), 1996, Academic Press
• DNA and Protein Sequence Analysis: A Practical Approach (Practical Approach Series , No 171), 1996, M. J. Bishop and C. J. Rawlings (Editors), 1996, IRL Press
• Molecular Bioinformatics: Algorithms and Applications, Steffen Schulze-Kremer, 1995, Walter De Gruyter
• Introduction to Computational Biology - Maps, sequences and genomes, Michael S. Waterman, 1995, Chapman & Hall
• Computer Analysis of Sequence Data, Annette M. Griffin and Hugh G. Griffin (Editors), 1994, Humana Press
• Artificial Intelligence and Molecular Biology, Lawrence Hunter (Editor), 1993, AAAI Press
• Sequence Analysis Primer, Michael Gribskov and John Devereux (Editors), 1992, Oxford University Press
• Mathematical Methods of Analysis of Biopolymer Sequences (Dimacs Series in Discrete Mathematics and Theoretical Computer Science ; Volume 8), S. G. Gindikin, 1992, American Mathematical Society
• Mathematical Methods for DNA Sequences, Michael S. Waterman (Editor), 1989, CRC Press

Programming Books for Bioinformatics

• Mastering Perl for Bioinformatics, James D. Tisdall, 2003, O'Reilly
• Genomic Perl: From Bioinformatics Basics to Working Code, Rex A. Dwyer, 2002, Cambridge University Press
• Beginning Perl for Bioinformatics, James Tisdall, 2001, O'Reilly
• Developing Bioinformatics Computer Skills, Cynthia Gibas, Per Jambeck, 2001, O'Reilly

General Genomics

• Functional Microbial Genomics (Volume 33), Brendan Wren, Nick Dorrell, 2003, Academic Press
• Discovering Genomics, Proteomics, and Bioinformatics, A. Malcolm Campbell, Laurie J. Heyer, 2002, Benjamin/Cummings
• Genomes, Terence A. Brown, 2002, John Wiley & Sons
• Essentials of Medical Genomics, Stuart M. Brown , 2002, John Wiley & Sons
• A Primer of Genome Science, Greg Gibson, Spencer V. Muse, 2002, Sinauer Associates
• Pathogen Genomics: Impact on Human Health, Karen Joy, Phd Shaw (Editors), 2002, Humana Press
• Genomics, John E. Antonopoulos, 2000, Xlibris Corporation
• Genomics and Proteomics: Functional and Computational Aspects, Sandor Suhai (Editor), 2000, Plenum Pub Corp
• Functional Genomics: A Practical Approach (The Practical Approach Series, 235), S. Hunt and F. Livesey (Editors), 2000, Oxford Univ Press
• Human Molecular Genetics, Andrew P. Read, Tom Strachan 1999, BIOS Scientific Publishers Ltd.
• Genomics: The Science and Technology Behind the Human Genome Project, Charles R. Cantor and Cassandra L. Smith, 1999, John Wiley & Sons
• Cells: A Laboratory Manual, 3 volumes, David L. Spector, Robert D. Goldman, Leslie A. Leinwand, 1998, Cold Spring Harbor Laboratory Press
• Genome Analysis: A Laboratory Manual, 4 volumes, Bruce Birren, et al. (Editors), 1997, Cold Spring Harbor Laboratory Press
• The Human Genome Project, N. G. Cooper (Editor), 1994, University Science Books

Comparative Genomics

• Handbook of Comparative Genomics: Principles and Methodology, Cecilia Saccone, Graziano Pesole, 2003, Wiley-Liss
• Sequence - Evolution - Function: Computational Approaches in Comparative Genomics, Eugene V. Koonin, Michael Y. Galperin, 2002, Kluwer Academic Publishers
• Comparative Genomics - Empirical and Analytical Approaches to Gene Order Dynamics, Map Alignment and the Evolution of Gene Families, David Sankoff and Joseph H. Nadeau, 2000, Kluwer Academic Pub
• Comparative Genomics, Melody Clark (Editor), 2000, Kluwer Academic Pub

Proteomics

• Proteins and Proteomics: A Laboratory Manual, Richard J. Simpson (Editor), Cold Spring Harbor Laboratory
• Proteomics in Practice: A Laboratory Manual of Proteome Analysis , Reiner Westermeier, Tom Naven, 2002, John Wiley & Sons
• Posttranslational Modifications of Proteins: Tools for Functional Proteomics (Methods in Molecular Biology, Vol 194) , Christoph Kannicht (Editor), 2002, Humana Press
• Peptide Arrays on Membrane Supports: Synthesis and Applications (Springer Lab Manual), Joachim Koch, Michael Mahler (Editors), 2002, Springer Verlag
• Proteomics , Timothy Palzkill, 2002, Kluwer Academic Publishers
• Introduction to Proteomics: Tools for the New Biology , Daniel C. Liebler (Editor), 2001, Humana Press
• Proteome Research: Mass Spectrometry (Principles and Practice) , P. James (Editor), 2001, Springer Verlag
• Interpreting Protein Mass Spectra: A Comprehensive Resource , A. Peter Snyder, 2000, American Chemical Society
• Protein Sequencing and Identification Using Tandem Mass Spectrometry , Michael Kinter, Nicholas E. Sherman, 2000, Wiley-Interscience
• From Genome to Proteome: Advances in the Practice and Application of Proteomics, Michael J. Dunn (Editor), 2000, Vch Verlagsgesellschaft Mbh
• Proteomics: From Protein Sequence to Function, S. Pennington (Editor), M. Dunn (Editor), 2000, Springer Verlag
• Proteome Research: Two-Dimensional Gel Electrophoresis and Detection Methods (Principles and Practice), T. Rabilloud (Editor), 2000, Springer Verlag
• Proteome and Protein Analysis, R. M. Kamp, D. Kyriakidis, th Choli-Papadopoulou (Editor), 1999, Springer Verlag
• Proteome Research: New Frontiers in Functional Genomics, M. R. Wilkins, et al. (Editors), 1997, Springer Verlag

Protein Structure

• Structural Bioinformatics, Philip E. Bourne, Helge Weissig (Editors), 2003, John Wiley & Sons
• Protein Structure Prediction: Bioinfomatic Approach, I.F. Tsigelny, 2002, International University Line
• Introduction to Protein Architecture: The Structural Biology of Proteins, Arthur M. Lesk, 2001, Oxford University Press
• Protein Structure Prediction: Methods and Protocols, David M. Webster (Editor), 2000, Humana Press
• Introduction to Protein Structure, Carl-Ivar Branden, John Tooze, 1999, Garland Publishing
• Structure and Mechanism in Protein Science: A Guide to Enzyme Catalysis and Protein Folding, Alan Fersht, 1999, Freeman

Pharmacogenomics

• Pharmacogenomics: Social, Ethical, and Clinical Dimensions, Mark A. Rothstein (Editor), 2003, Wiley-Liss
• Pharmacogenomics: The Search for Individualized Therapies, Julio Licinio, Ma-Li Wong (Editors), 2002, John Wiley & Sons
• Pharmacogenomics, Werner Kalow, Urs A. Meyer, Rachel Tyndale (Editors), 2001, Marcel Dekker
• Pharmacogenetics and Pharmcogenomics: Recent Conceptual and Technical Advances (Pharmacology, Volume 61, Number 3, 2000), Elliot S. Vesell (Editor), 2000, S. Karger Publishing
• Pharmacogenetics, Wendell Weber, 1997, Oxford University Press

DNA Microarrays

• Statistical Analysis of Gene Expression Microarray Data, T. P. Speed (Editor), 2003, CRC Press
• Microarray Gene Expression Data Analysis: A Beginner's Guide, Helen C. Causton, John Quackenbush, Alvis Brazma, 2003, Blackwell Publishers
• The Analysis of Gene Expression Data (Statistics for Biology and Health), G. Parmigiani, E. S. Garrett, R. A. Irizarry, S. Zeger , Graeme Clark (Editors), 2003, Springer Verlag
• A Practical Approach to Microarray Data Analysis, Daniel P. Berrar, Werner Dubitzky, Martin Granzow (Editors), 2002, Kluwer Academic Publishers
• DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling, Pierre Baldi, G. Wesley Hatfield, 2002, Cambridge University Press
• DNA Microarrays: A Molecular Cloning Manual, David Bowtell, Joseph Sambrook (Editors), 2002, Cold Spring Harbor Laboratory
• DNA Array Image Analysis: Nuts & Bolts, Gerda Kamberova, Shishir Shah, 2002, DNA Press
• Microarray Analysis, Mark Schena, 2002, John Wiley & Sons
• A Biologist's Guide to Analysis of DNA Microarray Data, Steen Knudsen, 2002, John Wiley & Sons
• Microarrays for an Integrative Genomics (Computational Molecular Biology), Isaac S. Kohane, Alvin Kho, Atul J. Butte, 2002, MIT Press
• Microarrays for the Neurosciences: An Essential Guide (Cellular and Molecular Neuroscience), Daniel H. Geschwind, Jeffrey P. Gregg (Editors), 2002, MIT Press
• DNA Microarrays: Gene Expression Applications, Bertrand Jordan (Editor), 2001, Springer Verlag
• DNA Arrays: Methods and Protocols (Methods in Molecular Biology, Volume 170), Jang B. Rampal (Editor), 2001, Humana Press
• DNA Arrays: Technologies and Experimental Strategies, Elena V. Grigorenko (Editor), 2001, CRC Press
• Microarray Biochip Technology, Mark Schena (Editor), 2000, Eaton Pub
• Expression Genetics: Accelerated and High-Throughput Methods (Biotechniques Update Series), Michael McClelland (Editor), Arthur B. Pardee (Editor), 1999, Eaton Pub
• DNA Microarrays: A Practical Approach (Practical Approach Series 205), Mark Schena (Editor), 1999, Oxford Univ Press
• cDNA Preparation and Characterization (Methods in Enzymology Volume 303), S.M. Weissman (Editor), 1999, Academic Press

Systems Biology, Genetic and Biochemical Network

• Handbook of Graphs and Networks : From the Genome to the Internet, Stefan Bornholdt, Heinz Georg Schuster (Editors), 2003, Vch Verlagsgesellschaft Mbh
• Computational Cell Biology, Christopher Fall, Eric Marland, John Wagner, John Tyson (Editors), 2002, Springer Verlag
• Gene Regulation and Metabolism: Post-Genomic Computational Approaches (Computational Molecular Biology), Julio Collado-Vides, Ralf Hofestadt (Editors), 2002, MIT Press
• Foundations of Systems Biology, Hiroaki Kitano (Editor), 2001, MIT Press
• Genomic Regulatory Systems: Development and Evolution, Eric H. Davidson , 2001, Academic Press
• Genes & Signals, Mark Ptashne, Alexander Gann, 2001, Cold Spring Harbor Laboratory
• Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology), James M. Bower and Hamid Bolouri (Editors), 2001, MIT Press
• Protein-Protein Interactions: A Molecular Cloning Manual, Erica Golemis (Editor), 2001, Cold Spring Harbor Laboratory
• Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists, Eberhard O. Voit, 2000, Cambridge University Press
• Mathematical Physiology, James P. Keener, James Sneyd, 1998, Springer Verlag

DNA Sequencing

• DNA Sequencing: From Experimental Methods to Bioinformatics (Introduction to Biotechniques Series), Luke Alphey, 1997, Springer Verlag
• Automated DNA sequencing and analysis, Adams M.D., Fields C., Venter J.C. (Editors), 1994, Academic Press

Apart from above mentioned books, you can also find some useful books links at following mentioned URLs:

http://www.amazon.com/Biological-Sequence-Analysis-Probabilistic-Proteins/dp/0521629713

http://www.amazon.com/Bioinformatics-Genes-Proteins-Computers-Advanced/dp/1859960545

http://www.amazon.com/Introduction-Bioinformatics-Algorithms-Computational-Molecular/dp/0262101068

http://books.google.no/books?id=pxSM7R1sdeQC&dq=Pierre+baldi+%2B+bioinformatics&printsec=frontcover&source=bn&hl=en&ei=IoGRS6uCIJT-NYLA8Z0N&sa=X&oi=book_result&ct=result&redir_esc=y#v=onepage&q&f=false

http://www.amazon.com/Statistical-Methods-Bioinformatics-Introduction-Statistics/dp/0387400826

If you think your favourite books are not listed then please write it down in comment section for the benefits of other users. Feel free to add many more books in comment section. 

tax_id:
the unique identifier provided by NCBI Taxonomy
for the species or strain/isolate

GeneID:
the unique identifier for a gene
ASN1: geneid

Symbol:
the default symbol for the gene
ASN1: gene->locus

LocusTag:
the LocusTag value
ASN1: gene->locus-tag

Synonyms:
bar-delimited set of unofficial symbols for the gene

dbXrefs:
bar-delimited set of identifiers in other databases
for this gene. The unit of the set is database:value.
Note that HGNC and MGI include 'HGNC' and 'MGI', respectively,
in the value part of their identifier. Consequently,
dbXrefs for these databases will appear like:
HGNC:HGNC:1100
This would be interpreted as database='HGNC', value='HGNC:1100'
Example for MGI:
MGI:MGI:104537
This would be interpreted as database='MGI', value='MGI:104537'

chromosome:
the chromosome on which this gene is placed.
for mitochondrial genomes, the value 'MT' is used.

map location:
the map location for this gene

description:
a descriptive name for this gene

type of gene:
the type assigned to the gene according to the list of options
provided in https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/lxr/source/src/objects/entrezgene/entrezgene.asn

Symbol from nomenclature authority:
when not '-', indicates that this symbol is from a
a nomenclature authority

Full name from nomenclature authority:
when not '-', indicates that this full name is from a
a nomenclature authority

Nomenclature status:
when not '-', indicates the status of the name from the
nomenclature authority (O for official, I for interim)

Other designations:
pipe-delimited set of some alternate descriptions that
have been assigned to a GeneID
'-' indicates none is being reported.

Modification date:
the last date a gene record was updated, in YYYYMMDD format

Feature type:
pipe-delimited set of annotated features and their classes or
controlled vocabularies, displayed as feature_type:feature_class
or feature_type:controlled_vocabulary, when appropriate; derived
from select feature annotations on RefSeq(s) associated with the
GeneID

Address of the bookmark: ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/

Address of the bookmark: https://github.com/wtmatlock/flanker

Address of the bookmark: https://bioconductor.org/packages/release/bioc/html/doubletrouble.html

The new visrus are about one micron—a thousandth of a millimeter—in length, the newfound genus Pandoravirus dwarfs other viruses, which range in size from about 50 nanometers up to 100 nanometers. A genus is a taxonomic ranking between species and family.

Find  more at @ http://www.nature.com/scitable/blog/viruses101/newly_found_pandoraviruses_hint_at

http://news.nationalgeographic.co.uk/news/2013/07/130718-viruses-pandoraviruses-science-biology-evolution/

https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html

Targeted bait capture is a technique for sequencing many loci simultaneously based on bait sequences. HybPiper pipeline starts with high-throughput sequencing reads (for example from Illumina MiSeq), and assigns them to target genes using BLASTx or BWA. The reads are distributed to separate directories, where they are assembled separately using SPAdes. The main output is a FASTA file of the (in frame) CDS portion of the sample for each target region, and a separate file with the translated protein sequence.

HybPiper also includes post-processing scripts, run after the main pipeline, to also extract the intronic regions flanking each exon, investigate putative paralogs, and calculate sequencing depth. For more information, please see our wiki.

HybPiper is run separately for each sample (single or paired-end sequence reads). When HybPiper generates sequence files from the reads, it does so in a standardized directory hierarchy. Many of the post-processing scripts rely on this directory hierarchy, so do not modify it after running the initial pipeline. It is a good idea to run the pipeline for each sample from the same directory. You will end up with one directory per run of HybPiper, and some of the later scripts take advantage of this predictable directory structure.

Address of the bookmark: https://github.com/mossmatters/HybPiper