/diadema_ajmc2020

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16s_diadema_ajmc2020

This contains all of the data used in the study AJMC 2020. including qiime commands, etc.

File Tree Directory

 |-- diadema_ajmc2020
    |-- 16S
        |-- RawSequences
            |-- AllSamples
            |-- CategSize
        |-- qiimecommands.sh
    |-- CytoB
        |-- Geneious
            |-- de novo
                |-- Alignments
                    |-- Geneious
                    |-- Velvet
                |-- ConsensusSequences
                |-- Geneious de novo
                    |-- Edited
                    |-- Raw
                    |-- Tree
                |-- Velvet de novo
                    |-- Edited
                    |-- Raw
                    |-- Tree
                |-- Trees
            |-- Map To References
                |-- Alignments
                |-- alignref_Contigs
                |-- ConsensusSeq
            |-- Normalized_ErrorCorrected_RemovedDuplicates
            |-- Trees
        |-- RawSequences
        |-- ReferenceSequences
        |-- Trees
    |-- README.md
    |-- References Thesis.xlx

WORKFLOW

CytoB - Geneious & Mega X

Learn how to use Geneious: https://www.geneious.com/ | https://www.geneious.com/tutorials/ |

Tutorials used in this study: https://www.geneious.com/tutorials/de-novo-assembly/ | https://www.geneious.com/tutorials/map-to-reference/ |

Learn how to use Mega X: https://megasoftware.net/ |

References:

https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.3732/apps.1400062 |

  1. Download & Import sequences from diadema_ajmc2020\CytoB\RawSequences into Geneious.

  2. Merge Pair Ends, Trim, Normalize, Error Correct Sequences, Remove Duplicates. [Remove Chimeric Reads???]

 |-- diadema_ajmc2020
    |-- CytoB
        |-- Geneious
            |-- Normalized_ErrorCorrected_RemovedDuplicates
  1. Velvet de novo Assembly of each of the samples
 |-- diadema_ajmc2020
    |-- CytoB
        |-- Geneious
            |-- de novo
                |-- Velvet de novo
                    |-- Raw
  1. Edits: The contigs generated by the de novo were edited to only contain sequences which corresponded close to the length of the gene
 |-- diadema_ajmc2020
    |-- CytoB
        |-- Geneious
            |-- de novo
                |-- Velvet de novo
                    |-- Edited
  1. Alignments: The edited Contigs were aligned within each sample using Geneious Alignment: Global 51
 |-- diadema_ajmc2020
    |-- CytoB
        |-- Geneious
            |-- de novo
                |-- Alignments
                    |-- Velvet
  1. Consensus Sequences: A Consensus Sequence was generated using 0 Majority
 |-- diadema_ajmc2020
    |-- CytoB
        |-- Geneious
            |-- de novo
                |-- ConsensusSequences
  1. Consensus Trees A tree was generated with all the samples.
 |-- diadema_ajmc2020
    |-- CytoB
        |-- Geneious
            |-- de novo
                |-- Velvet de novo
                    |-- Tree

16S rRNA - Qiime2

Tutorial used:

https://docs.qiime2.org/2020.6/ |

https://docs.qiime2.org/2020.6/tutorials/moving-pictures/ |

https://s3-us-west-2.amazonaws.com/qiime2-data/distro/core/virtualbox-images.txt |

To view Qiime files (artifacts (.qza files) and visualizations (.qzv files)) without downloading qiime use: https://view.qiime2.org/

References:

  1. Bolyen, Evan, et al. “Reproducible, Interactive, Scalable and Extensible Microbiome Data Science Using QIIME 2.” Nature Biotechnology, vol. 37, no. 8, 2019, pp. 852–857., doi:10.1038/s41587-019-0209-9.

  2. Estaki, Mehrbod, et al. “QIIME 2 Enables Comprehensive End‐to‐End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data.” Current Protocols in Bioinformatics, vol. 70, no. 1, 2020, doi:10.1002/cpbi.100.

  3. Hall, Michael, and Robert G. Beiko. “16S RRNA Gene Analysis with QIIME2.” Methods in Molecular Biology Microbiome Analysis, 2018, pp. 113–129., doi:10.1007/978-1-4939-8728-3_8.

Workflow:

QIIME2 Commands used can be found in diadema_ajmc2020\16S\qiimecommands.sh

  1. Import Data

  2. Visualize Data Files Generated

allsamplesimport.qzv
  1. Filter
allsamplesimportdemux-filtered.qza
allsamplesimportdemux-filter-stats.qza
  1. Deblur & Generate Feature Table
allsamplesimportrep-seqs-deblur.qza
allsamplesimporttable-deblur.qza
allsamplesimportdeblur-stats.qza
  1. Summary Stats
allsamplesimportdemux-filter-stats.qzv
allsamplesimportdeblur-stats.qzv
  1. Summary Feature Table $ Feature Sequence Data
seaurchinfeaturetableallsamples.qzv
sequences.qzv
  1. Generate a Phylogenetic Tree
aligned-rep-seqs.qza
masked-aligned-rep-seqs.qza
unrooted-tree.qza
rooted-tree.qza
  1. Alpha & Beta Diversity
core-metrics-results (FOLDER)
  1. Exploring Microbial Composition with Metadata
core-metrics-results/faith-pd-group-significance.qzv
core-metrics-results/evenness-group-significance.qzv
  1. Permanova
core-metrics-results/unweighted-unifrac-reefhabitat-significance.qzv
core-metrics-results/unweighted-unifrac-location-significance.qzv
  1. Emperor Plots by Metadata
core-metrics-results/unweighted-unifrac-emperor-size.qzv
core-metrics-results/bray-curtis-emperor-size.qzv
  1. Alpha Rarefaction Plotting
alpha-rarefaction.qzv
  1. Taxonomic Analysis
taxonomy.qza
taxonomy.qzv
taxa-bar-plots.qzv
  1. Group by Metadata
locationseaurchintable.qza
  1. Merge by Metadata.
grouped-taxa-bar-plots.qzv