,
Jorden Rabasco [aut, ctb] ,
Craig Gin [aut] ,
Benjamin Callahan [aut] ,
Manuel Kleiner [aut, ths] | Title: | TrIdent - Transduction Identification |
|---|---|
| Description: | The `TrIdent` R package automates the analysis of transductomics data by detecting, classifying, and characterizing read coverage patterns associated with potential transduction events. Transductomics is a DNA sequencing-based method for the detection and characterization of transduction events in pure cultures and complex communities. Transductomics relies on mapping sequencing reads from a viral-like particle (VLP)-fraction of a sample to contigs assembled from the metagenome (whole-community) of the same sample. Reads from bacterial DNA carried by VLPs will map back to the bacterial contigs of origin creating read coverage patterns indicative of ongoing transduction. |
| Authors: | Jessie Maier [aut, cre] ,
Jorden Rabasco [aut, ctb] ,
Craig Gin [aut] ,
Benjamin Callahan [aut] ,
Manuel Kleiner [aut, ths] |
| Maintainer: | Jessie Maier <[email protected]> |
| License: | GPL-2 |
| Version: | 0.99.3 |
| Built: | 2025-02-15 02:54:56 UTC |
| Source: | https://github.com/bioc/TrIdent |
Plot the read coverages of a contig and its associated pattern-match for Prophage-like, Sloping and HighCovNoPattern classifications. Returns a list of ggplot objects.
plotTrIdentResults( VLPpileup, WCpileup, TrIdentResults, matchScoreFilter, saveFilesTo )plotTrIdentResults( VLPpileup, WCpileup, TrIdentResults, matchScoreFilter, saveFilesTo )
VLPpileup |
VLP-fraction pileup file generated by mapping sequencing reads from a sample's ultra-purified VLP-fraction mapped to the sample's whole-community metagenome assembly. The pileup file MUST have the following format: * V1: Contig accession * V2: Mapped read coverage values averaged over 100 bp windows * V3: Starting position (bp) of each 100 bp window. Restarts from 0 at the start of each new contig. * V4: Starting position (bp) of each 100 bp window. Does NOT restart at the start of each new contig. |
WCpileup |
A whole-community pileup file generated by mapping sequencing reads from a sample's whole-community mapped to the sample's whole-community metagenome assembly. The pileup file MUST have the following format: * V1: Contig accession * V2: Mapped read coverage values averaged over 100 bp windows * V3: Starting position (bp) of each 100 bp window. Restarts from 0 at the start of each new contig. * V4: Starting position (bp) of each 100 bp window. Does NOT restart at the start of each new contig. |
TrIdentResults |
Output from 'TrIdentClassifier()'. |
matchScoreFilter |
Optional, Filter plots using the normalized pattern match-scores. A suggested filtering threshold is provided by 'TrIdentClassifier()' if 'suggFiltThresh=TRUE'. |
saveFilesTo |
Optional, Provide a path to the directory you wish to save output to. A folder will be made within the provided directory to store results. |
Large list containing ggplot objects
data("VLPFractionSamplePileup") data("WholeCommunitySamplePileup") data("TrIdentSampleOutput") patternMatches <- plotTrIdentResults( VLPpileup = VLPFractionSamplePileup, WCpileup = WholeCommunitySamplePileup, TrIdentResults = TrIdentSampleOutput )data("VLPFractionSamplePileup") data("WholeCommunitySamplePileup") data("TrIdentSampleOutput") patternMatches <- plotTrIdentResults( VLPpileup = VLPFractionSamplePileup, WCpileup = WholeCommunitySamplePileup, TrIdentResults = TrIdentSampleOutput )
Search contigs classified as Prophage-like for dense read coverage outside of the pattern-match borders that may indicate specialized transduction. Returns a list with the first object containing a summary table and the second object containing a list of plots of with associated specialzied transduction search results. If the plot is green, it has been identified as having potential specialized transduction.
specializedTransductionID( VLPpileup, TrIdentResults, specificContig, noReadCov = 500, specTransLength = 2000, matchScoreFilter, logScale = FALSE, verbose = TRUE, SaveFilesTo )specializedTransductionID( VLPpileup, TrIdentResults, specificContig, noReadCov = 500, specTransLength = 2000, matchScoreFilter, logScale = FALSE, verbose = TRUE, SaveFilesTo )
VLPpileup |
VLP-fraction pileup file generated by mapping sequencing reads from a sample's ultra-purified VLP-fraction mapped to the sample's whole-community metagenome assembly. The pileup file MUST have the following format: * V1: Contig accession * V2: Mapped read coverage values averaged over 100 bp windows * V3: Starting position (bp) of each 100 bp window. Restarts from 0 at the start of each new contig. * V4: Starting position (bp) of each 100 bp window. Does NOT restart at the start of each new contig. |
TrIdentResults |
Output from 'TrIdentClassifier()' |
specificContig |
Optional, Search a specific contig classified as Prophage-like ("NODE_1"). |
noReadCov |
Number of basepairs of zero read coverage encountered before specialized transduction searching stops. Default is 500. Must be at least 100. |
specTransLength |
Number of basepairs of non-zero read coverage needed for specialized transduction to be considered. Default is 2000. Must be at least 100. |
matchScoreFilter |
Optional, Filter plots using the normalized pattern match-scores. A suggested filtering threshold is provided by 'TrIdentClassifier()' if 'suggFiltThresh=TRUE'. |
logScale |
TRUE or FALSE, display VLP-fraction read coverage in log10 scale. Default is FALSE. |
verbose |
TRUE or FALSE. Print progress messages to console. Default is TRUE. |
SaveFilesTo |
Provide a path to the directory you wish to save output to. 'specializedTransductionID()' will make a folder within the provided directory to store results. |
Large list containing two objects
data("VLPFractionSamplePileup") data("TrIdentSampleOutput") specTransduction <- specializedTransductionID( VLPpileup = VLPFractionSamplePileup, TrIdentResults = TrIdentSampleOutput ) specTransductionNODE62 <- specializedTransductionID( VLPpileup = VLPFractionSamplePileup, TrIdentResults = TrIdentSampleOutput, specificContig = "NODE_62" )data("VLPFractionSamplePileup") data("TrIdentSampleOutput") specTransduction <- specializedTransductionID( VLPpileup = VLPFractionSamplePileup, TrIdentResults = TrIdentSampleOutput ) specTransductionNODE62 <- specializedTransductionID( VLPpileup = VLPFractionSamplePileup, TrIdentResults = TrIdentSampleOutput, specificContig = "NODE_62" )
Performs all the pattern-matching and summarizes the results into a list. The first item in the list is a table consisting of the summary information of all the contigs that passed through pattern-matching (i.e were not filtered out). The second item in the list is a table consisting of the summary information of all contigs that were classified via pattern-matching. The third item in the list contains the pattern-match information associated with each contig in the previous table. The fourth object in the list is a table containing the contigs that were filtered out prior to pattern-matching. The fifth item is the windowSize used for the search.
TrIdentClassifier( VLPpileup, WCpileup, windowSize = 1000, minBlockSize = 10000, maxBlockSize = Inf, minContigLength = 30000, minSlope = 0.001, suggFiltThresh = FALSE, verbose = TRUE, SaveFilesTo )TrIdentClassifier( VLPpileup, WCpileup, windowSize = 1000, minBlockSize = 10000, maxBlockSize = Inf, minContigLength = 30000, minSlope = 0.001, suggFiltThresh = FALSE, verbose = TRUE, SaveFilesTo )
VLPpileup |
VLP-fraction pileup file generated by mapping sequencing reads from a sample's ultra-purified VLP-fraction mapped to the sample's whole-community metagenome assembly. The pileup file MUST have the following format: * V1: Contig accession * V2: Mapped read coverage values averaged over 100 bp windows * V3: Starting position (bp) of each 100 bp window. Restarts from 0 at the start of each new contig. * V4: Starting position (bp) of each 100 bp window. Does NOT restart at the start of each new contig. |
WCpileup |
A whole-community pileup file generated by mapping sequencing reads from a sample's whole-community mapped to the sample's whole-community metagenome assembly. The pileup file MUST have the following format: * V1: Contig accession * V2: Mapped read coverage values averaged over 100 bp windows * V3: Starting position (bp) of each 100 bp window. Restarts from 0 at the start of each new contig. * V4: Starting position (bp) of each 100 bp window. Does NOT restart at the start of each new contig. |
windowSize |
The number of basepairs to average read coverage values over. Options are 100, 200, 500, 1000 ONLY. Default is 1000. |
minBlockSize |
The minimum size (in bp) of the Prophage-like block pattern. Default is 10000. Must be at least 1000. |
maxBlockSize |
The maximum size (in bp) of the Prophage-like block pattern. Default is NA (no maximum). |
minContigLength |
The minimum contig size (in bp) to perform pattern-matching on. Must be at least 25000. Default is 30000. |
minSlope |
The minimum slope value to test for sloping patterns. Default is 0.001 (i.e minimum change of 10x read coverage over 100,000 bp). |
suggFiltThresh |
TRUE or FALSE, Suggest a filtering threshold for TrIdent classifications based on the normalized pattern-match scores. Default is FALSE. |
verbose |
TRUE or FALSE. Print progress messages to console. Default is TRUE. |
SaveFilesTo |
Optional, Provide a path to the directory you wish to save output to. A folder will be made within the provided directory to store results. |
Large list containing 5 objects
data("VLPFractionSamplePileup") data("WholeCommunitySamplePileup") TrIdent_results <- TrIdentClassifier( VLPpileup = VLPFractionSamplePileup, WCpileup = WholeCommunitySamplePileup )data("VLPFractionSamplePileup") data("WholeCommunitySamplePileup") TrIdent_results <- TrIdentClassifier( VLPpileup = VLPFractionSamplePileup, WCpileup = WholeCommunitySamplePileup )