nb_bars: Create stacked bar charts based on negative binomial model...
In tidyMicro: A Pipeline for Microbiome Analysis and Visualization
Description
Usage
Arguments
Value
Examples
Description
nb_bars takes the output from nb_mods and creates stacked bar charts of the estimated relative abundance for each taxa. The benefit of modeling each taxa before created stacked bar charts is the ability to control for potential confounders. The function will facet wrap interaction terms. Currently, only quant_style "discrete" can be used for an interaction between two quantitative variables
Usage
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Arguments
modsum
The output from nb_mods
...
The covariate you'd like to plot. Can be an interaction term or main effect, but must be in the models created by nb_mods
range
The range you'd like to plot over for a quantitative variable. Will default to the IQR
quant_style
"continuous" will plot over the entire range specified; "discrete" will plot only the endpoints of the range specified. "continuous" by default. This option is ignored without a quantitative variable
top_taxa
Only plot X taxa with the highest relative abundance. The rest will be aggregated into an "Other" category
RA
Only plot taxa with a relative abundance higher than X. The rest will be aggregated into an "Other" category
specific_taxa
Plot this specific taxa even if it doesn't meet the top_taxa or RA requirements
lines
Logical; Add outlines around the different taxa colors in the stacked bar charts
xaxis
Labels for the x-axis ticks. Most useful for categorical variables and defaults to the levels
main
Plot title
subtitle
Subtitle for the plot
xlab
x-axis label
ylab
y-axis label
facet_labels
Labels for the facets created for interaction terms
facet_layout
Rearrange the facets created for interaction terms
Value
Returns a ggplot that you can add geoms to if you'd like
Examples
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data(bpd_phy); data(bpd_cla); data(bpd_ord); data(bpd_fam); data(bpd_clin)
otu_tabs = list(Phylum = bpd_phy, Class = bpd_cla,
Order = bpd_ord, Family = bpd_fam)
set <- tidy_micro(otu_tabs = otu_tabs, clinical = bpd_clin) %>%
filter(day == 7) ## Only including the first week
## Creating negative binomial models on filtered tidy_micro set
nb_fam <- set %>%
otu_filter(ra_cutoff = 0.1, exclude_taxa = c("Unclassified", "Bacteria")) %>%
nb_mods(table = "Family", bpd1)
nb_fam %>%
nb_bars(bpd1, top_taxa = 9, xlab = "BPD Severity")
Example output
Loading required package: tidyverse
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
✔ ggplot2 3.3.2 ✔ purrr 0.3.4
✔ tibble 3.0.4 ✔ dplyr 1.0.2
✔ tidyr 1.1.2 ✔ stringr 1.4.0
✔ readr 1.4.0 ✔ forcats 0.5.0
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
Contains 74 libraries from OTU files.
Summary of sequencing depth:
Min. 1st Qu. Median Mean 3rd Qu. Max.
8851 24938 33314 36650 43590 97408
Filter for Class counts
Found 'Unclassified' category in input data.
Created new 'Other' category.
Found 'Bacteria' category in input data.
Found 34 OTUs.
Collapsed 2 OTUs into 'Other' in OTU table.
Converted 61662 counts to 'Other' otu category.
Remaining OTUs: 33 (Including 'Other').
Relative abundance cutoff: 0.1% (i.e., at least one library must have RA > 0.1% to keep OTU).
Found 33 OTUs.
Found 'Other' category in input data.
Collapsed 24 OTUs into 'Other' in OTU table.
Converted 337 counts to 'Other' otu category.
Remaining OTUs: 9 (Including 'Other').
Filter for Family counts
Found 'Unclassified' category in input data.
Created new 'Other' category.
Found 'Bacteria' category in input data.
Found 116 OTUs.
Collapsed 2 OTUs into 'Other' in OTU table.
Converted 61662 counts to 'Other' otu category.
Remaining OTUs: 115 (Including 'Other').
Relative abundance cutoff: 0.1% (i.e., at least one library must have RA > 0.1% to keep OTU).
Found 115 OTUs.
Found 'Other' category in input data.
Collapsed 95 OTUs into 'Other' in OTU table.
Converted 751 counts to 'Other' otu category.
Remaining OTUs: 20 (Including 'Other').
Filter for Order counts
Found 'Unclassified' category in input data.
Created new 'Other' category.
Found 'Bacteria' category in input data.
Found 62 OTUs.
Collapsed 2 OTUs into 'Other' in OTU table.
Converted 61662 counts to 'Other' otu category.
Remaining OTUs: 61 (Including 'Other').
Relative abundance cutoff: 0.1% (i.e., at least one library must have RA > 0.1% to keep OTU).
Found 61 OTUs.
Found 'Other' category in input data.
Collapsed 45 OTUs into 'Other' in OTU table.
Converted 525 counts to 'Other' otu category.
Remaining OTUs: 16 (Including 'Other').
Filter for Phylum counts
Found 'Unclassified' category in input data.
Created new 'Other' category.
Found 'Bacteria' category in input data.
Found 15 OTUs.
Collapsed 2 OTUs into 'Other' in OTU table.
Converted 61662 counts to 'Other' otu category.
Remaining OTUs: 14 (Including 'Other').
Relative abundance cutoff: 0.1% (i.e., at least one library must have RA > 0.1% to keep OTU).
Found 14 OTUs.
Found 'Other' category in input data.
Collapsed 7 OTUs into 'Other' in OTU table.
Converted 50 counts to 'Other' otu category.
Remaining OTUs: 7 (Including 'Other').
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
18 taxa converged.
2 taxa did not converge.
There were 50 or more warnings (use warnings() to see the first 50)
Warning messages:
1: Maximum column sum is 108 and will be rescaled to equal 100.
2: Minimum column sum is 86 and will be rescaled to equal 100.
tidyMicro documentation built on Jan. 13, 2021, 6:18 a.m.
R Package Documentation
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Description Usage Arguments Value Examples
Description
nb_bars takes the output from nb_mods and creates stacked bar charts of the estimated relative abundance for each taxa. The benefit of modeling each taxa before created stacked bar charts is the ability to control for potential confounders. The function will facet wrap interaction terms. Currently, only quant_style "discrete" can be used for an interaction between two quantitative variables
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 |
Arguments
modsum |
The output from nb_mods |
... |
The covariate you'd like to plot. Can be an interaction term or main effect, but must be in the models created by nb_mods |
range |
The range you'd like to plot over for a quantitative variable. Will default to the IQR |
quant_style |
"continuous" will plot over the entire range specified; "discrete" will plot only the endpoints of the range specified. "continuous" by default. This option is ignored without a quantitative variable |
top_taxa |
Only plot X taxa with the highest relative abundance. The rest will be aggregated into an "Other" category |
RA |
Only plot taxa with a relative abundance higher than X. The rest will be aggregated into an "Other" category |
specific_taxa |
Plot this specific taxa even if it doesn't meet the top_taxa or RA requirements |
lines |
Logical; Add outlines around the different taxa colors in the stacked bar charts |
xaxis |
Labels for the x-axis ticks. Most useful for categorical variables and defaults to the levels |
main |
Plot title |
subtitle |
Subtitle for the plot |
xlab |
x-axis label |
ylab |
y-axis label |
facet_labels |
Labels for the facets created for interaction terms |
facet_layout |
Rearrange the facets created for interaction terms |
Value
Returns a ggplot that you can add geoms to if you'd like
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | data(bpd_phy); data(bpd_cla); data(bpd_ord); data(bpd_fam); data(bpd_clin)
otu_tabs = list(Phylum = bpd_phy, Class = bpd_cla,
Order = bpd_ord, Family = bpd_fam)
set <- tidy_micro(otu_tabs = otu_tabs, clinical = bpd_clin) %>%
filter(day == 7) ## Only including the first week
## Creating negative binomial models on filtered tidy_micro set
nb_fam <- set %>%
otu_filter(ra_cutoff = 0.1, exclude_taxa = c("Unclassified", "Bacteria")) %>%
nb_mods(table = "Family", bpd1)
nb_fam %>%
nb_bars(bpd1, top_taxa = 9, xlab = "BPD Severity")
|
Example output
Loading required package: tidyverse
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
✔ ggplot2 3.3.2 ✔ purrr 0.3.4
✔ tibble 3.0.4 ✔ dplyr 1.0.2
✔ tidyr 1.1.2 ✔ stringr 1.4.0
✔ readr 1.4.0 ✔ forcats 0.5.0
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
Contains 74 libraries from OTU files.
Summary of sequencing depth:
Min. 1st Qu. Median Mean 3rd Qu. Max.
8851 24938 33314 36650 43590 97408
Filter for Class counts
Found 'Unclassified' category in input data.
Created new 'Other' category.
Found 'Bacteria' category in input data.
Found 34 OTUs.
Collapsed 2 OTUs into 'Other' in OTU table.
Converted 61662 counts to 'Other' otu category.
Remaining OTUs: 33 (Including 'Other').
Relative abundance cutoff: 0.1% (i.e., at least one library must have RA > 0.1% to keep OTU).
Found 33 OTUs.
Found 'Other' category in input data.
Collapsed 24 OTUs into 'Other' in OTU table.
Converted 337 counts to 'Other' otu category.
Remaining OTUs: 9 (Including 'Other').
Filter for Family counts
Found 'Unclassified' category in input data.
Created new 'Other' category.
Found 'Bacteria' category in input data.
Found 116 OTUs.
Collapsed 2 OTUs into 'Other' in OTU table.
Converted 61662 counts to 'Other' otu category.
Remaining OTUs: 115 (Including 'Other').
Relative abundance cutoff: 0.1% (i.e., at least one library must have RA > 0.1% to keep OTU).
Found 115 OTUs.
Found 'Other' category in input data.
Collapsed 95 OTUs into 'Other' in OTU table.
Converted 751 counts to 'Other' otu category.
Remaining OTUs: 20 (Including 'Other').
Filter for Order counts
Found 'Unclassified' category in input data.
Created new 'Other' category.
Found 'Bacteria' category in input data.
Found 62 OTUs.
Collapsed 2 OTUs into 'Other' in OTU table.
Converted 61662 counts to 'Other' otu category.
Remaining OTUs: 61 (Including 'Other').
Relative abundance cutoff: 0.1% (i.e., at least one library must have RA > 0.1% to keep OTU).
Found 61 OTUs.
Found 'Other' category in input data.
Collapsed 45 OTUs into 'Other' in OTU table.
Converted 525 counts to 'Other' otu category.
Remaining OTUs: 16 (Including 'Other').
Filter for Phylum counts
Found 'Unclassified' category in input data.
Created new 'Other' category.
Found 'Bacteria' category in input data.
Found 15 OTUs.
Collapsed 2 OTUs into 'Other' in OTU table.
Converted 61662 counts to 'Other' otu category.
Remaining OTUs: 14 (Including 'Other').
Relative abundance cutoff: 0.1% (i.e., at least one library must have RA > 0.1% to keep OTU).
Found 14 OTUs.
Found 'Other' category in input data.
Collapsed 7 OTUs into 'Other' in OTU table.
Converted 50 counts to 'Other' otu category.
Remaining OTUs: 7 (Including 'Other').
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
Waiting for profiling to be done...
18 taxa converged.
2 taxa did not converge.
There were 50 or more warnings (use warnings() to see the first 50)
Warning messages:
1: Maximum column sum is 108 and will be rescaled to equal 100.
2: Minimum column sum is 86 and will be rescaled to equal 100.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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