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diff --git a/Sequence_Quality_Control_and_Analysis.tex b/Sequence_Quality_Control_and_Analysis.tex
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...
controlled reads could be mapped back to our cluster seeds at a 97\% identity
cutoff for the 16S and 23S sequences, respectively.
\subsubsection{Alpha and Beta diversity analyses} Alpha diversity calculations
were made using PyCogent Python bioinformatics modules \citep{17708774}. Beta
diversity analyses were made using Phyloseq \citep{24699258} and its
dependencies \citep{vegan}. A sparsity threshold of 25\% was used for
ordination of both plastid 23S and bacterial 16S libraries. Additionally, we
discarded any OTUs from the 23S data that could not be annotated as belonging
in the
Eukaryota. Eukaryota or cyanobacteria. Cyanobacterial DNA sequences were
removed from 16S sequence collections. All DNA sequence based results were
visualized using GGPlot2 \citep{Wickham_2009}. Adonis tests and principal
coordinate ordinations were performed using the Bray-Curtis similarity measure
for pairwise library comparisons. Adonis tests employed the default value for
...
improve power and specificity when identifying differentially abundant OTUs
across sample classes in microbiome experiments \citet{24699258}.
The specific specific DESeq2 \citep{Love_2014} parameters we used were as
follows: All dispersion estimates from DESeq2 were calculated using a local fit
for mean-dispersion. Native DESeq2 independent filtering was disabled in favor
of explicit sparsity filtering. The sparsity thresholds that produced the
maximum number of OTUs with adjusted p-values for differential abundance below
a false discovery rate of 10\% were selected for biofilm versus planktonic
sequence 16S/plastid 23S library comparisons. The specific sparsity threshold
for plastid 23S and 16S libraries for biofilm versus plankton comparisons was
10\% (OTUs found in less than the sparsity threshold of samples were discarded
from the analysis). Cook's distance filtering was also disabled when
calculating p-values with DESeq2. We used the Benjamini-Hochberg method to
adjust p-values for multiple testing \citep{citeulike:1042553}. Identical
DESeq2 methods were used to assess enriched OTUs from relative abundances
grouped into high (C:P = 500) or low (C:P < 500 and control) categories.
IPython Notebooks with computational methods used to create all figures and
tables
as well as taking raw sequences through quality control preprocessing
are provided at the following url:
\url{http://nbviewer.ipython.org/github/chuckpr/BvP_manuscript_figures}.
diff --git a/table1.tex b/table1.tex
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--- a/table1.tex
+++ b/table1.tex
...
\textbf{\refstepcounter{table}\label{Tab:01} Table \arabic{table}.}{ Results for BLAST search against Living Tree Project (top 25 lifestyle enriched bacterial OTUs) }
{\tiny\begin{tabular}{llr>{\itshape}lrl} \begin{tabular}{llr>{\itshape}lrl}
\toprule
\\
\textbf{OTU ID} & \textbf{Phylum} &
$log_2(plank.:biof.)$ $log_2(plankton:biofilm)$ &
\textbf{Species} \textbf{Species Name} & \textbf{BLAST
\% ID} percent identity} & \textbf{accession} \\
\midrule
\multirow{1}{*}{OTU.103} & \multirow{1}{*}{Bacteroidetes} & \multirow{1}{*}{7.78} & Zunongwangia profunda & 89.66 &
\textbf{Accession} DQ855467 \\ \midrule
\multirow{1}{*}{OTU.105} & \multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{2.09} \multirow{1}{*}{8.09} & Microbulbifer yueqingensis & 90.14 & GQ262813 \\ \midrule
\multirow{1}{*}{OTU.11} & \multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{2.99} \multirow{1}{*}{9.59} & Methylobacillus glycogenes & 93.96 & FR733701 \\ \midrule
\multirow{2}{*}{OTU.123} & \multirow{2}{*}{Proteobacteria} &
\multirow{2}{*}{2.29} \multirow{2}{*}{8.96} & Flexibacter roseolus & 83.46 & AB078062 \\ & & & Flexibacter elegans & 83.46 & AB078048 \\ \midrule
\multirow{1}{*}{OTU.13} \multirow{2}{*}{OTU.165} &
\multirow{1}{*}{Proteobacteria} \multirow{2}{*}{Proteobacteria} &
\multirow{1}{*}{2.13} \multirow{2}{*}{-7.05} &
Vibrio fortis Kangiella spongicola &
100.0 92.05 &
AJ514916 GU339304 \\
\midrule
\multirow{1}{*}{OTU.14} &
\multirow{1}{*}{Lentisphaerae} &
\multirow{1}{*}{-2.25} &
Victivallis vadensis Kangiella marina &
86.57 92.05 &
AY049713 JN559388 \\ \midrule
\multirow{1}{*}{OTU.15} \multirow{1}{*}{OTU.166} & \multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{2.59} \multirow{1}{*}{-7.52} &
Neptunomonas naphthovorans Halomonas halocynthiae &
94.04 92.62 &
AF053734 AJ417388 \\ \midrule
\multirow{7}{*}{OTU.18} & \multirow{7}{*}{Proteobacteria} & \multirow{7}{*}{2.08} & Vibrio tasmaniensis & 100.0 & AJ316192 \\ & & & Vibrio pomeroyi & 100.0 & AJ491290 \\ & & & Vibrio gigantis & 100.0 & EF094888 \\ & & & Vibrio crassostreae & 100.0 & EF094887 \\ & & & Vibrio celticus & 100.0 & EF599162 \\ & & & Vibrio atlanticus & 100.0 & EF599163 \\ \multirow{1}{*}{OTU.19} &
\multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{9.31} &
Vibrio artabrorum Neptuniibacter caesariensis &
100.0 90.07 &
EF599164 AY136116 \\ \midrule
\multirow{1}{*}{OTU.19} \multirow{1}{*}{OTU.195} & \multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{3.05} \multirow{1}{*}{7.17} &
Neptuniibacter caesariensis Methylobacillus glycogenes &
90.07 94.63 &
AY136116 FR733701 \\ \midrule
\multirow{2}{*}{OTU.20} & \multirow{2}{*}{Proteobacteria} &
\multirow{2}{*}{2.94} \multirow{2}{*}{9.07} & Ruegeria halocynthiae & 96.15 & HQ852038 \\ & & & Phaeobacter daeponensis & 95.49 & DQ981486 \\ \midrule
\multirow{1}{*}{OTU.207} & \multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{2.45} \multirow{1}{*}{9.30} & Methylobacillus glycogenes & 91.28 & FR733701 \\ \midrule
\multirow{1}{*}{OTU.21} \multirow{5}{*}{OTU.223} &
\multirow{1}{*}{Proteobacteria} \multirow{5}{*}{Proteobacteria} &
\multirow{1}{*}{-2.62} \multirow{5}{*}{7.94} &
Pseudoruegeria aquimaris Methyloferula stellata &
94.07 87.02 &
DQ675021 FR686343 \\
\midrule
\multirow{1}{*}{OTU.24} &
\multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{-2.09} &
Sulfitobacter mediterraneus Methylocapsa aurea &
99.23 87.02 &
Y17387 FN433469 \\
\midrule
\multirow{1}{*}{OTU.25} &
\multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{2.02} &
Arcobacter nitrofigilis Beijerinckia indica subsp. lacticogenes &
90.13 87.02 &
L14627 AJ563931 \\
\midrule
\multirow{1}{*}{OTU.26} &
\multirow{1}{*}{Actinobacteria} &
\multirow{1}{*}{2.67} &
Corallomonas stylophorae Beijerinckia indica subsp. indica &
88.17 87.02 &
GU569894 CP001016 \\
\midrule
\multirow{2}{*}{OTU.3} &
\multirow{2}{*}{Proteobacteria} &
\multirow{2}{*}{2.70} &
Neptunomonas japonica Beijerinckia derxii subsp. venezuelae &
93.38 87.02 &
AB288092 AJ563934 \\
\midrule
\multirow{1}{*}{OTU.26} &
\multirow{1}{*}{Actinobacteria} &
\multirow{1}{*}{8.58} &
Neptunomonas antarctica Corallomonas stylophorae &
93.38 88.17 &
FJ713802 GU569894 \\ \midrule
\multirow{2}{*}{OTU.31} & \multirow{2}{*}{Bacteroidetes} &
\multirow{2}{*}{2.89} \multirow{2}{*}{9.63} & Sediminitomix flava & 91.33 & AB255370 \\ & & & Kordia algicida & 91.33 & AY195836 \\ \midrule
\multirow{1}{*}{OTU.32} & \multirow{1}{*}{Bacteroidetes} &
\multirow{1}{*}{2.63} \multirow{1}{*}{8.90} & Bizionia echini & 97.32 & FJ716799 \\ \midrule
\multirow{1}{*}{OTU.36} & \multirow{1}{*}{Actinobacteria} &
\multirow{1}{*}{2.64} \multirow{1}{*}{9.55} & Pseudoclavibacter soli & 95.95 & AB329630 \\ \midrule
\multirow{1}{*}{OTU.369} & \multirow{1}{*}{Actinobacteria} & \multirow{1}{*}{7.93} & Agrococcus terreus & 96.0 & FJ423764 \\ \midrule
\multirow{1}{*}{OTU.40} & \multirow{1}{*}{Bacteroidetes} &
\multirow{1}{*}{2.42} \multirow{1}{*}{7.68} & Aureitalea marina & 91.33 & AB602429 \\ \midrule
\multirow{3}{*}{OTU.44} & \multirow{3}{*}{Proteobacteria} &
\multirow{3}{*}{2.12} \multirow{3}{*}{8.92} & Glaciecola mesophila & 92.62 & AJ488501 \\ & & & Aestuariibacter salexigens & 92.67 & AY207502 \\ & & & Aestuariibacter halophilus & 92.67 & AY207503 \\ \midrule
\multirow{1}{*}{OTU.50} \multirow{2}{*}{OTU.48} &
\multirow{1}{*}{Proteobacteria} \multirow{2}{*}{Actinobacteria} &
\multirow{1}{*}{2.16} \multirow{2}{*}{7.28} &
Vibrio breoganii Microterricola viridarii &
100.0 97.33 &
EF599161 AB282862 \\ & & & Leifsonia pindariensis & 97.33 & AM900767 \\ \midrule
\multirow{1}{*}{OTU.69} \multirow{3}{*}{OTU.62} &
\multirow{1}{*}{Proteobacteria} \multirow{3}{*}{Proteobacteria} &
\multirow{1}{*}{2.27} \multirow{3}{*}{8.75} &
Sneathiella glossodoripedis Haliea rubra &
87.94 91.55 &
AB289439 EU161717 \\ & & & Congregibacter litoralis & 91.55 & AAOA01000004 \\ & & & Chromatocurvus halotolerans & 91.55 & AM691086 \\ \midrule
\multirow{1}{*}{OTU.7} \multirow{1}{*}{OTU.69} & \multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{-2.30} \multirow{1}{*}{9.34} &
Ruegeria mobilis Sneathiella glossodoripedis &
94.74 87.94 &
AB255401 AB289439 \\ \midrule
\multirow{1}{*}{OTU.71} & \multirow{1}{*}{Bacteroidetes} &
\multirow{1}{*}{2.24} \multirow{1}{*}{7.40} & Aequorivita sublithincola & 95.77 & AF170749 \\ \midrule
\multirow{1}{*}{OTU.8} \multirow{1}{*}{OTU.83} & \multirow{1}{*}{Actinobacteria} & \multirow{1}{*}{7.27} & Microbacterium invictum & 92.47 & AM949677 \\ \midrule
\multirow{2}{*}{OTU.84} & \multirow{2}{*}{Proteobacteria} & \multirow{2}{*}{-7.44} & Alcanivorax dieselolei & 93.29 & AY683537 \\ &
\multirow{1}{*}{Proteobacteria} &
\multirow{1}{*}{-2.04} &
Stakelama sediminis Alcanivorax balearicus &
91.54 93.29 &
EU099873 AY686709 \\ \midrule
\multirow{1}{*}{OTU.89} & \multirow{1}{*}{Actinobacteria} & \multirow{1}{*}{7.17} & Corallomonas stylophorae & 87.91 & GU569894 \\ \midrule
\bottomrule
\end{tabular}}{} \end{tabular}
\end{table}
