Computational methods used by the Shasta assembler include:

• Using a run-length representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.
• Using in some phases of the computation a representation of the read sequence based on markers, a fixed subset of short k-mers (k ≈ 10).

More at https://chanzuckerberg.github.io/shasta/index.html

Address of the bookmark: https://github.com/chanzuckerberg/shasta

Address of the bookmark: https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&selected=%23BRIG&tag=Comparative

For knowledge about Linux and their importance amongst bioinformatician plesae read this article "An introduction to Linux for bioinformatics" by Paul Stothard.

Linux cheat sheet at http://bioinformaticsonline.com/file/view/87/linux-cheat-sheet

Please browse for futher useful linux pages on right hand side ...

'du' – Check the size of a directory

$ du
This command ( du) gives you a list of directories that exist in the current working directory along with their sizes in kilobytes (default). The last line of the output gives you the total size of the current directory including its subdirectories.

$ du /home/jin1
The above command would give you the directory size of the directory /home/david

$ du -h
The same “du”command with some flag gives you a better output than the default one. The option '-h' stands for human readable format. Therefore, in order to print the sizes of the files / directories in your desire notation use this time suffixed with a 'k' if its kilobytes and 'M' if its Megabytes and 'G' if its Gigabytes.

$ du -ah
If you are interested in checking everything present in a folder use above mentioned command. It gives us not only the directories but also all the files that are present in the current directory. The “-a” flag displays the filenames along with the directory names in the output.

$ du -c
This gives you a grand total as the last line of the output. So if your directory occupies 30MB the last 2 lines of the output would be 30M.

$ du -s
Use this command to displays a summary of the directory size. It is the simplest way to know the total size of the current directory.

$ du -S
This would display the size of the current directory excluding the size of the subdirectories that exist within that directory. So it basically shows you the total size of all the files that exist in the current directory.

$ du --exculde=mp3
Several times it required to exclude some directory in our size calculation. In such cases the above command would display the size of the current directory along with all its subdirectories, but it would exclude all the files having the given pattern present in their filenames.

'df' - finding the disk free space / disk usage

$ df
Hmmm … now “df” command is really useful, and I guess you are going to use it over time. Typing the above command, outputs a table consisting of 6 columns. All the columns are very easy to understand. Remember that the 'Size', 'Used' and 'Avail' columns use kilobytes as the unit. The 'Use%' column shows the usage as a percentage which is also very useful.

$ df -h
Displays the same output as the previous command but the '-h' indicates human readable format. Hence instead of kilobytes as the unit the output would have 'M' for Megabytes and 'G' for Gigabytes.

Example: Linux installed on /dev/hda1
$ df -h | grep /dev/hda1

All right, this is not the only option to check the sizes and free spaces but there are a few more options that can be used with 'du' and 'df' . I will discuss it later.

ALF
A Simulation Framework for Genome Evolution
http://www.cbrg.ethz.ch/alf

Bayesian Serial SimCoal
Bayesian Serial SimCoal, (BayeSSC) is a modification of SIMCOAL 1.0, a program written by Laurent Excoffier, John Novembre, and Stefan Schneider.
http://www.stanford.edu/group/hadlylab/ssc/index.html

BEERS
BEERS was designed to benchmark RNA-Seq alignment algorithms and also algorithms that aim to reconstruct different isoforms and alternate splicing from RNA-Seq data
http://cbil.upenn.edu/beers/

BOTTLENECK
Bottleneck is a program for detecting recent effective population size reductions from allele data frequencies
http://www.ensam.inra.fr/urlb/bottleneck/bottleneck.html

BottleSim
BottleSim is a computer simulation program for simulating the process of population bottlenecks
http://chkuo.name/software/bottlesim.html

CASS
Protein Sequence Simulation
http://www.wyomingbioinformatics.org/liberlesgroup/cass/

CDPOP
CDPOP is a landscape genetics tool for simulating the emergence of spatial genetic structure in populations resulting from specified landscape processes governing organism movement behavior.
http://cel.dbs.umt.edu/cdpop

CoalFace
CoalFace is a simulation of the coalescent process with the visual display of gene genealogies.
http://web.up.ac.za/default.asp?ipkcategoryid=3283

CoaSim
CoaSim is a tool for simulating the coalescent process with recombination and geneconversion under various demographic models.
http://users-birc.au.dk/mailund/coasim/index.html

cosi
The cosi package is written in C and is available as a tar file.
http://www.broadinstitute.org/~sfs/cosi/

CS-PSeq-Gen
A program to simulate the evolution of protein sequences under the constraints of the information of a particular reconstructed phylogeny
http://bioserv.rpbs.univ-paris-diderot.fr/software/cs-pseq-gen.html

DAWG
An application designed to simulate the evolution of recombinant DNA sequences in continuous time
http://scit.us/projects/dawg

Easypop
EASYPOP is an individual based model intended to simulate datasets under a very broad range of conditions
http://www.unil.ch/dee/page36926_fr.html

EggLib
EggLib is a C++/Python library and program package for evolutionary genetics and genomics.
http://egglib.sourceforge.net/

EvolSimulator
A simulation test bed for hypotheses of genome evolution
http://acb.qfab.org/acb/evolsim/

EvolveAGene
A realistic coding sequence simulation program that separates mutation from selection and allows the user to set selection conditions
http://bellinghamresearchinstitute.com/software/index.html

fastsimcoal
A continuous-¬‐time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios
http://cmpg.unibe.ch/software/fastsimcoal/

FastSLINK
Simulation of Marker and Phenotype Data in Pedigrees
http://watson.hgen.pitt.edu/

FFPopSim
C++/Python library for population genetics.
http://webdav.tuebingen.mpg.de/ffpopsim/

FLUX SIMULATOR
The Flux Simulator aims at providing a deterministic in silico reproduction of the experimental pipelines for RNA-Seq, employing a minimal set of parameters.
http://flux.sammeth.net/simulator.html

ForSim
ForSim: A Forward Evolutionary Computer Simulation
http://www.anthro.psu.edu/weiss_lab/research.shtml

ForwSim
The program given below is based on the algorithm described in Padhukasahasram et al. 2008 to simulate genetic drift in a standard Wright-Fisher process.
http://badri-populationgeneticsimulators.blogspot.com/

FPG
Forward Population Genetic simulation
http://genfaculty.rutgers.edu/hey/software#fpg

FREGENE
FREGENE is a C++ program that simulates sequence-like data over large genomic regions in large diploid populations.
http://www.ebi.ac.uk/projects/bargen/download/fregen/documentation_html.html

GAMETES
Genetic Architecture Model Emulator for Testing and Evaluating Software: Simulates complex SNP models with pure, strict epistatic interactions with n-loci.
http://sourceforge.net/projects/gametes/?source=navbar

GASP
Genometric Analysis Simulation Program. A software tool for testing and investigating methods in statistical genetics by generating samples of family data based on user specified models.
http://research.nhgri.nih.gov/gasp/

GemSIM
Next generation sequencing read simulator
http://sourceforge.net/projects/gemsim/

GeneArtisan
Simulation of Markers in Case-Control Study Designs
http://www.rannala.org/?page_id=241

GENOME
A rapid coalescent-based whole genome simulator
http://www.sph.umich.edu/csg/liang/genome/

GenomePop2
GenomePop2 is a specialization of the program GenomePop just to manage SNPs under more flexible and useful settings. If you need models with more than 2 alleles please use the GenomePop program version.
http://webs.uvigo.es/acraaj/genomepop2.htm

GenomeSimla
GenomeSIMLA is currently under development- however, we have a beta release that we are asking to be tested
http://chgr.mc.vanderbilt.edu/genomesimla/

GENS2
Simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions.
https://sourceforge.net/projects/gensim/

GWAsimulator
A rapid whole genome simulation program
http://biostat.mc.vanderbilt.edu/wiki/main/gwasimulator

HAP-SAMPLE
An association simulator for candidate regions or genome scans
http://www.hapsample.org/

HAPGEN
A simulator for the simulation of case control datasets at SNP markers
https://mathgen.stats.ox.ac.uk/genetics_software/hapgen/hapgen2.html

HapSim
A simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients
http://cran.r-project.org/web/packages/hapsim/index.html

HAPSIMU
A program that simulates heterogeneous populations with various known and controllable structures under the continuous migration model or the discrete model
http://l.web.umkc.edu/liujian/

IBDsim
IBDSim is a computer package for the simulation of genotypic data under general isolation by distance models.
http://raphael.leblois.free.fr/

indel-Seq-Gen
A biological sequence simulation program that simulates highly divergent DNA sequences and protein superfamilies
http://bioinfolab.unl.edu/~cstrope/isg/

Indelible
A powerful and flexible simulator of biological evolution
http://abacus.gene.ucl.ac.uk/software/indelible/

invertFREGENE
InvertFREGENE is a forward-in-time simulator of inversions in population genetic data
http://www.ebi.ac.uk/projects/bargen/

kernalPop
A spatially explicit population genetic simulation engine
http://cran.r-project.org/src/contrib/archive/kernelpop/

MaCS
Markovian Coalescent Simulator
http://www-hsc.usc.edu/~garykche/

Mason
A package for the simulation of nucleotide data.
http://www.seqan.de/projects/mason/

mbs
modifying Hudson's ms software to generate samples of DNA sequences with a biallelic site under selection
http://www.sendou.soken.ac.jp/esb/innan/innanlab/software.html

Mendel's Accountant
Mendel's Accountant (MENDEL) is an advanced numerical simulation program for modeling genetic change over time and was developed collaboratively by Sanford, Baumgardner, Brewer, Gibson and ReMine
http://mendelsaccount.sourceforge.net/

MetaSim
A tool to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets
http://ab.inf.uni-tuebingen.de/software/metasim/

mlcoalsim
Multilocus Coalescent Simulations
http://code.google.com/p/mlcoalsim-v1/

ms
The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets.
http://home.uchicago.edu/~rhudson1/source/mksamples.html

msHOT
The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets.
http://home.uchicago.edu/~rhudson1/

msms
A coalescent Simlation tool with selection.
http://www.mabs.at/ewing/msms/index.shtml

MySSP
A program for the simulation of DNA sequence evolution across a phylogenetic tree
http://www.rosenberglab.net/software.php

Nemo
A forward-time, individual-based, genetically explicit, and stochastic simulation program designed to study the evolution of genetic markers, life history traits, and phenotypic traits in a flexible (meta-)population framework.
http://nemo2.sourceforge.net/

NetRecodon
Coalescent simulation of coding DNA sequences with recombination (inter and intracodon), migration and demography
http://code.google.com/p/netrecodon/

PEDAGOG
Software for simulating eco-evolutionary population dynamics
https://bcrc.bio.umass.edu/pedigreesoftware/node/5

phenosim
A tool to add phenotypes to simulated genotypes
http://evoplant.uni-hohenheim.de/doku.php?id=software:software

PhyloSim
An R package for the Monte Carlo simulation of sequence evolution
http://bit.ly/rlsim-git

pIRS
Profile-based Illumina pair-end reads simulator
https://code.google.com/p/pirs/

ProteinEvolver
Simulation of protein evolution along phylogenies under structure-based substitution models
http://code.google.com/p/proteinevolver/

QMSim
QTL and Marker Simulator
http://www.aps.uoguelph.ca/~msargol/qmsim/

quantiNEMO
An individual-based program for the analysis of quantitative traits with explicit genetic architecture potentially under selection in a structured population
http://www2.unil.ch/popgen/softwares/quantinemo/

RECOAL
Simulates new haplotype data from a reference population of haplotypes.
ftp://popgen.usc.edu/

Recodon
Coalescent simulation of coding DNA sequences with recombination, migration and demography
http://code.google.com/p/recodon/

rlsim
A package for simulating RNA-seq library preparation with parameter estimation
http://bit.ly/rlsim-git

Rmetasim
Rmetasim is a front-end for the metasim engine that is implemented as a package that runs in the statistical computing environment R
http://linum.cofc.edu/software.html#metasim

RNA Seq Simulator
RSS takes SAM alignment files from RNA-Seq data and simulates over dispersed, multiple replica, differential, non-stranded RNA-Seq datasets.
http://useq.sourceforge.net/cmdlnmenus.html#rnaseqsimulator

Rose
Random model of sequence evolution
http://bibiserv.techfak.uni-bielefeld.de/rose/

SelSim
SelSim is a program for Monte Carlo simulation of DNA polymorphism data for a recom- bining region within which a single bi-allelic site has experienced natural selection
http://www.well.ox.ac.uk/~spencer/selsim/

Seq-Gen
An application for the Monte Carlo simulation of molecular sequence evolution along phylogenetic trees.
http://tree.bio.ed.ac.uk/software/seqgen/

SEQPower
Statistical power analysis for sequence-based association studies
http://bioinformatics.org/spower/

SeqSIMLA
SeqSIMLA can simulate sequence data with user-specified disease and quantitative trait models. Family or unrelated case-control data can be simulated.
http://seqsimla.sourceforge.net/

Serial NetEvolve
A flexible utility for generating serially-sampled sequences along a tree or recombinant network
http://biorg.cis.fiu.edu/sne/

SFS_CODE
SFS_CODE can perform forward population genetic simulations under a general Wright-Fisher model with arbitrary migration, demographic, selective, and mutational effects.
http://sfscode.sourceforge.net/sfs_code/index/index.html

SIBSIM
Quantitative phenotype simulation in extended pedigrees
http://sourceforge.net/projects/sibsim/

SIMCOAL2
A coalescent program for the simulation of complex recombination patterns over large genomic regions under various demographic models
http://cmpg.unibe.ch/software/simcoal2/

SimCopy
An R package simulating the evolution of copy number profiles along a tree.
http://bit.ly/simcopy

SIMLA
SIMLA is a SIMuLAtion program that generates data sets of families for use in Linkage and Association studies.
http://www.chg.duke.edu/research/simla.html

SimPed
A Simulation Program to Generate Haplotype and Genotype Data for Pedigree Structures
http://www.hgsc.bcm.tmc.edu/content/simped

Simprot
A program to simulate protein evolution by substitution, insertion and deletion
http://www.uhnresearch.ca/labs/tillier/software.htm#3

SimRare
Rare variant simulation and analysis tool
http://code.google.com/p/simrare/

simuGWAS
A forward-time simulator that simulates realistic samples for genome-wide association studies.
http://simupop.sourceforge.net/cookbook/simucomplexdisease

simuPOP
simuPOP is a general-purpose individual-based forward-time population genetics simulation environment.
http://simupop.sourceforge.net/

SISSI
A software tool to generate data of related sequences along a given phylogeny, taking into account user defined system of neighbourhoods and instantaneous rate matrices.
http://www.cibiv.at/software/sissi/

SNPsim
Coalescent simulation of hotspot recombination
http://code.google.com/p/phylosoftware/

SPIP
SPIP simulates the transmission of genes from parents to offspring in a population having demographic structure defined by the user
http://swfsc.noaa.gov/textblock.aspx?division=fed&id=3434

Splatche
Spatial and Temporal Coalescences in Heterogeneous Environment
http://www.splatche.com/

srv
Simulator of Rare Varaints (srv) is a simulator for the simulation of the introduction and evolution of (rare) genetic variants.
http://simupop.sourceforge.net/cookbook/simurarevariants

SUP
SLINK/FastSLINK utility program
http://mlemire.freeshell.org/software.html

TreesimJ
A flexible, forward-time population genetic simulator
http://code.google.com/p/treesimj/

Vortex
VORTEX is an individual-based simulation model for population viability analysis (PVA).
http://www.vortex9.org/vortex.html

References:

Image www.evolution-of-life.com

www.cancer.gov

Again, running spades.py will show you the options:

spades.py

This produces:

SPAdes genome assembler v3.10.1

Usage: /usr/local/SPAdes-3.10.1-Linux/bin/spades.py [options] -o <output_dir>

Basic options:
-o      <output_dir>    directory to store all the resulting files (required)
--sc                    this flag is required for MDA (single-cell) data
--meta                  this flag is required for metagenomic sample data
--rna                   this flag is required for RNA-Seq data
--plasmid               runs plasmidSPAdes pipeline for plasmid detection
--iontorrent            this flag is required for IonTorrent data
--test                  runs SPAdes on toy dataset
-h/--help               prints this usage message
-v/--version            prints version

Input data:
--12    <filename>      file with interlaced forward and reverse paired-end reads
-1      <filename>      file with forward paired-end reads
-2      <filename>      file with reverse paired-end reads
-s      <filename>      file with unpaired reads
--pe<#>-12      <filename>      file with interlaced reads for paired-end library number <#> (<#> = 1,2,..,9)
--pe<#>-1       <filename>      file with forward reads for paired-end library number <#> (<#> = 1,2,..,9)
--pe<#>-2       <filename>      file with reverse reads for paired-end library number <#> (<#> = 1,2,..,9)
--pe<#>-s       <filename>      file with unpaired reads for paired-end library number <#> (<#> = 1,2,..,9)
--pe<#>-<or>    orientation of reads for paired-end library number <#> (<#> = 1,2,..,9; <or> = fr, rf, ff)
--s<#>          <filename>      file with unpaired reads for single reads library number <#> (<#> = 1,2,..,9)
--mp<#>-12      <filename>      file with interlaced reads for mate-pair library number <#> (<#> = 1,2,..,9)
--mp<#>-1       <filename>      file with forward reads for mate-pair library number <#> (<#> = 1,2,..,9)
--mp<#>-2       <filename>      file with reverse reads for mate-pair library number <#> (<#> = 1,2,..,9)
--mp<#>-s       <filename>      file with unpaired reads for mate-pair library number <#> (<#> = 1,2,..,9)
--mp<#>-<or>    orientation of reads for mate-pair library number <#> (<#> = 1,2,..,9; <or> = fr, rf, ff)
--hqmp<#>-12    <filename>      file with interlaced reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9)
--hqmp<#>-1     <filename>      file with forward reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9)
--hqmp<#>-2     <filename>      file with reverse reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9)
--hqmp<#>-s     <filename>      file with unpaired reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9)
--hqmp<#>-<or>  orientation of reads for high-quality mate-pair library number <#> (<#> = 1,2,..,9; <or> = fr, rf, ff)
--nxmate<#>-1   <filename>      file with forward reads for Lucigen NxMate library number <#> (<#> = 1,2,..,9)
--nxmate<#>-2   <filename>      file with reverse reads for Lucigen NxMate library number <#> (<#> = 1,2,..,9)
--sanger        <filename>      file with Sanger reads
--pacbio        <filename>      file with PacBio reads
--nanopore      <filename>      file with Nanopore reads
--tslr  <filename>      file with TSLR-contigs
--trusted-contigs       <filename>      file with trusted contigs
--untrusted-contigs     <filename>      file with untrusted contigs

Pipeline options:
--only-error-correction runs only read error correction (without assembling)
--only-assembler        runs only assembling (without read error correction)
--careful               tries to reduce number of mismatches and short indels
--continue              continue run from the last available check-point
--restart-from  <cp>    restart run with updated options and from the specified check-point ('ec', 'as', 'k<int>', 'mc')
--disable-gzip-output   forces error correction not to compress the corrected reads
--disable-rr            disables repeat resolution stage of assembling

Advanced options:
--dataset       <filename>      file with dataset description in YAML format
-t/--threads    <int>           number of threads
                                [default: 16]
-m/--memory     <int>           RAM limit for SPAdes in Gb (terminates if exceeded)
                                [default: 250]
--tmp-dir       <dirname>       directory for temporary files
                                [default: <output_dir>/tmp]
-k              <int,int,...>   comma-separated list of k-mer sizes (must be odd and
                                less than 128) [default: 'auto']
--cov-cutoff    <float>         coverage cutoff value (a positive float number, or 'auto', or 'off') [default: 'off']
--phred-offset  <33 or 64>      PHRED quality offset in the input reads (33 or 64)
                                [default: auto-detect]

As you can see this is also a “pipeline” of tools that can be switched on or off. SPAdes takes quite a long time, so for the purposes of this practical, something like this may suffice:

spades.py -t 4 \
          -m 32 \
          -k 31,51,71 \
          --only-assembler \
          -1 miseq.1.fastq -2 miseq.2.fastq \
          --nanopore minion.fastq \
          -o hybrid_assembly

In turn, these parameters mean

• use 4 threads
• max memory is 32Gb
• use 3 kmer values to build the de bruijn graph(s) - 31, 51 and 71
• only run the assembler, not the correction algorithm (for speed)
• read 1 and read 2 of the MiSeq data
• the nanopore data
• put the output in folder “hybrid_assembly”

Following are the genome assembly tools based on string graph:

1.SGA (String Graph Assembler) https://github.com/jts/sga

Assembles large genomes from high coverage short read data. SGA is designed as a modular set of programs, which are used to form an assembly pipeline. SGA implements a set of assembly algorithms based on the FM-index. As the FM-index is a compressed data structure, the algorithms are very memory efficient. The SGA assembly has three distinct phases. The first phase corrects base calling errors in the reads. The second phase assembles contigs from the corrected reads. The third phase uses paired end and/or mate pair data to build scaffolds from the contigs. The output of this software is a PDF report that allows the properties of the genome and data quality to be visually explored. By providing more information to the user at the start of an assembly project, this software will help increase awareness of the factors that make a given assembly easy or difficult, assist in the selection of software and parameters and help to troubleshoot an assembly if it runs into problems.

2. SAGE: String-overlap Assembly of GEnomes https://github.com/lucian-ilie/SAGE2

SAGE, for de novo genome assembly. As opposed to most assemblers, which are de Bruijn graph based, SAGE uses the string-overlap graph. SAGE builds upon great existing work on string-overlap graph and maximum likelihood assembly, bringing an important number of new ideas, such as the efficient computation of the transitive reduction of the string overlap graph, the use of (generalized) edge multiplicity statistics for more accurate estimation of read copy counts, and the improved use of mate pairs and min-cost flow for supporting edge merging. The assemblies produced by SAGE for several short and medium-size genomes compared favourably with those of existing leading assemblers.

3. FSG: Fast String Graph

The new integrated assembler has been assessed on a standard benchmark, showing that fast string graph (FSG) is significantly faster than SGA while maintaining a moderate use of main memory, and showing practical advantages in running FSG on multiple threads. Moreover, we have studied the effect of coverage rates on the running times.

4.  BASE https://github.com/dhlbh/BASE

It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs. BASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.

5. Fermi https://github.com/lh3/fermi/

Fermi is a de novo assembler with a particular focus on assembling Illumina short sequence reads from a mammal-sized genome. In addition to the role of a typical assembler, fermi also aims to preserve heterozygotes which are often collapsed by other assemblers. Its ultimate goal is to find a minimal set of unitigs to represent all the information in raw reads.

If you want to learn about String Graph assembler, please read the following papers -

i) The Fragment Assembly String Graph - E. W. Myers

This paper describes the String Graph concept.

ii) Efficient construction of an assembly string graph using the FM-index - Jared T. Simpson and Richard Durbin

This earlier paper from Simpson and Durbin

iii) Efficient de novo assembly of large genomes using compressed data structures - Jared T. Simpson and Richard Durbin

y a number of metrics, including:

• Overall assembly length
• Number of scaffolds/contigs
• Length of longest scaffold/contig
• Scaffold/contig N50 and N90Assembly base composition, in particular percentage GC and percentage Ns
• CEGMA completeness
• Scaffold/contig length/count distribution

assembly-stats supports two widely used presentations of these values, tabular and cumulative length plots, and introduces an additional circular plot that summarises most commonly used assembly metrics in a single visualisation. Each of these presentations is generated using javascript from a common (JSON) data structure, allowing toggling between alternative views, and each can be applied to a single or multiple assemblies to allow direct comparison of alternate assemblies.

Tabular presentation allows direct comparison of exact values between assemblies, the limitations of this approach lie in the necessary omission of distributions and the challenge of interpreting ratios of values that may vary by several orders of magnitude.

Address of the bookmark: https://github.com/rjchallis/assembly-stats