Paul Nemer

11 April 2019

Lab 12 Moving Picture Tutorial

Objective: The objective of the lab is learn how to create a figure representing the biodiversity of the samples collected. In the future we plan on incorporating the figure representing our eDNA sample. The figure was created according to the number of allowed sequence bases.

Procedure for Moving Pictures:

1. Using terminal session, create a new directory.
   1. Input: mkdir qiime2-moving-pictures-tutorial
   2. Input: cd qiime2-moving-pictures-tutorial
2. Open the Search bar and allow to show side bars. Click the link at the bottom to show your ID. This allows us to monitor progress.
3. Download the sample metadata by inserting
   1. Type: wget \-O “sample-metadata.tsv” \
   2. “https://data.qiime2.org/2019.1/tutorials/moving-pictures/sample_metadata.tsv”

4. Download the sequence reads by inputing the single end sequences.
   1. Type: mkdir emp-single-end-sequences
   2. Type: wget \-O “emp-single-end-sequences/barcodes.fastq.gz” \
   3. “https://data.qiime2.org/2019.1/tutorials/moving-pictures/emp-single-end-sequences/barcodes.fastq.gz
   4. Type: wget \-O “emp-single-end-sequences/sequences.fastq.gz” \
   5. https://data.qiime2.org/2019.1/tutorials/moving-pictures/emp-single-end-sequences/sequences.fastq.gz

5. Import Sequence Data.
   1. Type: qiime tools import \
   2. Type: EMPSingleEndSequences \
   3. input-path emp-single-end-sequences \
   4. output-path emp-single-end-sequences.qza
6. Demultiplexing is processing where one would use the barcode information in order to know which sequence came from which sample. In order to demultiplex the sequences:
   1. Type: qiime demux emp-single \–i-seqs emp-single-end-sequences.qza \–m-barcodes-file sample-metadata.tsv \–m-barcodes-column BarcodeSequence \–o-per-sample-sequences demux.qza
   2. Type: qiime demux summarize \–i-data demux.qza \–o-visualization demux.qzv

7. In order to view the qzv files, open QIIME2 and drag the newly created qzv files into the drop on the QIIME2 View website box located at the top of the website.
   2. https://view.qiime2.org/
8. Denoise the sequence by using the DADA2 protocol and input into terminal:
   2. qiime dada2 denoise-single \–i-demultiplexed-seqs demux.qza \–p-trim-left 0 \–p-trunc-len 120 \–o-representative-sequences rep-seqs-dada2.qza \–o-table table-dada2.qza \–o-denoising-stats stats-dada2.qza
   3. qiime metadata tabulate \ –m-input-file stats-dada2.qza \ –o-visualization stats-dada2.qzvmv rep-seqs-dada2.qza rep-seqs.qzamv table-dada2.qza table.qza
9. Repeat step 6 to view stats-dada2.qzv
10. To generate the feature table, repeat step 6 by adding into the drop box.
    1. qiime feature-table summarize \–i-table table.qza \–o-visualization table.qzv \–m-sample-metadata-file sample-metadata.tsvqiime feature-table tabulate-seqs \–i-data rep-seqs.qza \–o-visualization rep-seqs.qzv
11. Following the Taxonomic Analysis procedure: insert
    2. wget \ -O “gg-13-8-99-515-806-nb-classifier.qza” \ “https://data.qiime2.org/2019.1/common/gg-13-8-99-515-806-nb-classifier.qza”qiime feature-classifier classify-sklearn \ –i-classifier gg-13-8-99-515-806-nb-classifier.qza \ –i-reads rep-seqs.qza \ –o-classification taxonomy.qza qiime metadata tabulate \ –m-input-file taxonomy.qza \ –o-visualization taxonomy.qzv
12. Repeat step 6 in order to view the taxonomy.qzv
    1. qiime taxa barplot \ –i-table table.qza \ –i-taxonomy taxonomy.qza \ –m-metadata-file sample-metadata.tsv \ –o-visualization taxa-bar-plots.qzv
13. Repeat step 6, to view taxa-barplots.qzv
    1. Type: qiime taxa barplot \–i-table table.qza \–i-taxonomy taxonomy.qza \–m-metadata-file sample-metadata.tsv \–o-visualization taxa-bar-plots.qzv

Bar Plot using Mac computer:

Conclusion: By analyzing and creating visual figures regarding our data, we can better represent the specificity of the biodiversity within our eDNA sample. During analysis of the sample, we are able to see the best quality and reliable of scores. As the sequence of bases progressed, the quality and reliability decreased. Furthermore, we learned the points at which sequences can be cut. We were able to match them to already existing taxa located in the NCBI database.

Future Goals: By learning the basics of moving as well as the procedure, we can continue analyzing our eDNA sample in the future. I hope that these procedures will increase my directional skills as well as my coding skills. The biggest problem that we face as a whole is technology. I personally do not have a Mac therefore I struggle in certain uses of it. Furthermore, complications with technology came up for both my group and other groups.  In regards to the project, since we cannot acquire data about this year’s sequence due to time constraints, we plan on analyzing last year’s data.