HTML Report

Concept

The output from this extract module, such as how many loci are recovered, in how many samples, and to what extent, would be the most direct indication of whether your analysis is successful or not, and thus would be of most interest to many users. However, collecting, summarizing, and visualizing such important information can be backbreaking, especially in a phylo"genomic" project which typically employs hundreds or even thousands of samples and loci.

Don’t worry, Captus automatically generates an informative report! Open captus-assembly_extract.report.html with your browser (internet connection required) to explore your extraction result at various scales, from the global level to the single sample or single locus level.

Tip

The entire report is based on data stored in captus-assembly_extract.stats.tsv.
All tables and plots in the report are interactive powered by Plotly.
Visit the following sites once to take full advantage of its interactivity:
- https://plotly.com/chart-studio-help/getting-to-know-the-plotly-modebar
- https://plotly.com/chart-studio-help/zoom-pan-hover-controls

Example

Here is a small example of the report you can play with!
The heatmap shows a extraction result of the Angiosperms353 (Johnson et al., 2019) loci from targeted-capture data of four plant species. The blue bars along with x- and y-axes indicate how many loci are recovered in each sample and how many samples each locus is recovered in, respectively.

Note

When your result contains more than one marker type, the report will include separate plots for each marker type.
For loci with more than one copy found in a sample, information on best hit (hit with the highest weighted score) will be shown.
Information on loci with no samples recovered and samples with no loci recovered will not be shown.

Features

1. Hover information

Hover mouse cursor over the heatmap to see detailed information about each single data point.

List of the information to be shown

Field	Description	Unit
Sample	Sample name	-
Marker type	Marker type (`NUC` = Nuclear proteins; `PTD` = Plastidial proteins; `MIT` = Mitochondrial proteins; `DNA` = Miscellaneous DNA markers; `CLR` = Cluster-derived DNA markers)	-
Locus	Locus name	-
Ref name	Reference sequence name selected	-
Ref coords	Matched coordinates with respect to the reference sequence (Consecutive coordinates separated by `,` indicate partial hits on the same contig; coordinates separated by `;` indicate hits on different contigs)	-
Ref type	Reference sequence format (`nucl` = nucleotides; `prot` = amino acids)	-
Ref len matched	Total length of `Ref coords`	aa/bp
Total hits (copies)	Number of hits found (Values greater than 1 imply the presence of paralogs)	-
Recovered length	Percentage of reference sequence length recovered, calcurated as (`Ref len matched` / Reference sequence length) * 100	%
Identity	Sequence identity of the recovered sequence to the reference sequence	%
Score	Score inspired by `Scipio`, calculated as (matches - mismatches) / reference sequence length	-
Weighted score	Weighted `score` to address multiple reference sequences per locus (for details, read Information included in the table)	-
Hit length	Length of sequence recovered	bp
CDS length	Total length of coding sequences (CDS) recovered (always `NA` when the `ref_type` is `nucl`)	bp
Intron length	Total length of introns recovered (always `NA` when the `ref_type` is `nucl`)	bp
Flanking length	Total length of flanking sequences recovered	bp
Number of frameshifts	Number of corrected frameshifts in the extracted sequence (always `0` when `ref_type` is `nucl`)	-
Position of frameshifts	Positions of corrected frameshifts in the extracted sequence (`NA` when no frameshift is detected or `ref_type` is `nucl`)	-
Contigs in best hit	Number of contigs used to assemble the best hit	-
Best hit L50	Least number of contigs in best hit that contain 50% of the best hit’s recovered length	-
Best hit L90	Least number of contigs in best hit that contain 90% of the best hit’s recovered length	-
Best hit LG50	Least number of contigs in best hit that contain 50% of the reference locus length	-
Best hit LG90	Least number of contigs in best hit that contain 90% of the reference locus length	-

* When your data is huge (number of samples * number of loci > 500k), only Sample, Locus, and the variable selected in the Variable dropdown will be shown.

2. `Variable` dropdown

Switch this dropdown to change the variable to be shown as a heatmap among the following options:

Variable	Description	Unit
Recovered Length	Percentage of reference sequence length recovered	%
Identity	Sequence identity of the recovered sequence to the reference sequence	%
Total Hits (Copies)	Number of hits found (Values greater than 1 imply the presence of paralogs)	-
Score	Score inspired by `Scipio`, calculated as (matches - mismatches) / reference sequence length	-
Weighted Score	Weighted `score` to address multiple reference sequences per locus (for details, read Information included in the table)	-
Number of Frameshifts	Number of corrected frameshifts in the extracted sequence (always `0` if the reference sequence is in nucleotide)	-
Contigs in Best Hit	Number of contigs used to assemble the best hit	-
Best Hit L50	Least number of contigs in best hit that contain 50% of the best hit’s recovered length	-
Best Hit L90	Least number of contigs in best hit that contain 90% of the best hit’s recovered length	-
Best Hit LG50	Least number of contigs in best hit that contain 50% of the reference locus length	-
Best Hit LG90	Least number of contigs in best hit that contain 90% of the reference locus length	-

3. `Sort by Value` dropdown

Switch this dropdown to change the sorting manner of each axis as follow:

Label	Locus (x-axis)	Sample (y-axis)
None	Sort by name	Sort by name
Mean X	Sort by mean value	Sort by name
Mean Y	Sort by name	Sort by mean value
Mean Both	Sort by mean value	Sort by mean value
Total X	Sort by total value	Sort by name
Total Y	Sort by name	Sort by total value
Total Both	Sort by total value	Sort by total value

Created by Gentaro Shigita (11.08.2021)
Last modified by Gentaro Shigita (16.09.2022)