Manual

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Package
February 13, 2019
Type Package
Title Analyze and comapre ONT MinION and GridION X5 1D Sequencing Data
Version 1.0
Author Davide Bolognini, BS, PhD Fellow [aut, cre]
Maintainer Davide Bolognini 
Depends R (>= 3.1.3)
Imports parallel,
ggplot2 (>= 2.2.1),
seqinr,
reshape2,
scales,
RColorBrewer,
grid,
gridExtra,
rhdf5(>= 2.14),
ShortRead (>= 1.24.0)
Encoding UTF-8
LazyData true
RoxygenNote 6.0.1

R topics documented:
FastqFilterG . .
NanoCompare .
NanoFastqG . .
NanoFastqM .
NanoPrepareG .
NanoPrepareM
NanoStatsG . .
NanoStatsM . .
NanoTableG . .
NanoTableM .

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2
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1

2

FastqFilterG

FastqFilterG

Filter your GridION X5 .fastq files

Description
Use this function if you have .fastq and sequencing summary files and you want to filter your .fastq
files in order to obtain only the high-quality ones. FastqFilterG can optionally return a .fasta file
for the high-quality sequences. FastqFilterG can optionally return a total .fastq file (equivalent to a
’cat’ shell command) and translate into .fasta
Usage
FastqFilterG(Data, DataOut, FASTQTOT = FALSE, FASTA = FALSE, Cores = 1,
Label)
Arguments
Data

Path to .fastq and sequencing summary files returned from GridION X5 (can
find .fastq and sequencing summary files recursively)

DataOut

Where the .fastq (and, optionally, .fasta) file will be saved

FASTQTOT

Logical. If TRUE, combine all the .fastq together and store in the DataOut
folder. Default to FALSE

FASTA

Logical. If FALSE, return only .fastq file else, if TRUE, return both .fastq and
.fasta files. Default to FALSE

Cores

Number of cores to use to accelerate sequencing summary files reading. Default
to 1

Label

Llabel to use, together with the Flow Cell identifier, to identify the experiment

Value
High-quality .fastq file and, optionally, high quality .fasta file, total .fastq file and total .fasta file. If
one or more .fastq file is "ill-formatted", FastqFilterG stops and prints the number of the "guilty"
.fastq file.
Examples
#do not run
DataPath<-"/data/basecalled/ExperimentName/FlowCellId"
FastqFilterG(Data=DataPath, DataOut="Path/To/DataOut",FASTQTOT=FALSE,FASTA=FALSE)

NanoCompare

NanoCompare

3

Compare ONT experiments

Description
NanoCompare plots comparison statistics for MinION and GridION X5 experiments analyzed with
the other functions from this package
Usage
NanoCompare(DataIn, DataOut, Labels, GCC = TRUE)
Arguments
DataIn

Character vector containing paths to folders contaning analyzed MinION and/or
GridION X5 experiments

DataOut

Where to save NanoCompare results

Labels

Character vector containing ordered labels used to identify experiments in DataIn

Value
Plots:
- Violins.pdf;
- Histograms.pdf;
Examples
#do not run
DataIn<-c("Path/To/AnalyzedFolder1","Path/To/AnalyzedFolder2",...)
Labels<-c("Label1","Label2","Label3") #labels used
NanoCompare(DataIn=DataIn,DataOut="Path/To/DataOut",Labels=Labels,GCC=TRUE) #compare

NanoFastqG

Extracts .fastq informations from your GridION X5 basecalled passed
.fast5 files

Description
NanoFastqG returns a .fastq file (and, optionally, a .fasta file) for your high-quality reads
Usage
NanoFastqG(DataPass, DataOut, Label, Cores = 1, FASTA = FALSE)

4

NanoFastqM

Arguments
DataPass
DataOut
Label
Cores
FASTA

Path to passed .fast5 files folder
Where .fastq (and, optionally, .fasta) file will be saved
Label used, together with the Flow Cell identifier extracted from the inputted
data, to identify .fastq (and, optionally, .fasta) file
Number of cores to be used: 1 by default
Logical. If FALSE, return only .fastq file else, if TRUE, return both .fastq and
.fasta files. Default to FALSE

Value
.fastq file and, optionally, .fasta file for passed .fast5 files
Examples
#do not run
NanoFastqG(DataPass="Path/To/DataPass", DataOut="/Path/To/DataOutExp", Cores=6, FASTA=FALSE)
NanoFastqG(DataPass="Path/To/DataPass", DataOut="/Path/To/DataOutExp", Cores=6, FASTA=TRUE)

NanoFastqM

Extracts .fastq informations from your MinION passed .fast5 files

Description
NanoFastqM returns a .fastq file (and, optionally, a .fasta file) for your high-quality reads
Usage
NanoFastqM(DataPass, DataOut, Label, Cores = 1, FASTA = FALSE)
Arguments
DataPass
DataOut
Label
Cores
FASTA

Path to passed .fast5 files folder
Where .fastq (and, optionally, .fasta) file will be saved
Label used to identify .fastq (and, optionally, .fasta) file
Number of cores to be used: 1 by default
Logical. If FALSE, return only .fastq file else, if TRUE, return both .fastq and
.fasta files. Default to FALSE

Value
.fastq file and, optionally, .fasta file for passed .fast5 files
Examples
#do not run
NanoFastqM(DataPass="Path/To/DataPass", DataOut="/Path/To/DataOutExp", Cores=6, FASTA=FALSE)
NanoFastqM(DataPass="Path/To/DataPass", DataOut="/Path/To/DataOutExp", Cores=6, FASTA=TRUE)

NanoPrepareG

NanoPrepareG

5

Prepares GridION X5 data for your analyses with NanoR

Description
NanoPrepareG generates an object of class list that contains informations required by other functions from NanoR when analyzing GridION X5 data.
Usage
NanoPrepareG(BasecalledFast5 = FALSE, Data, DataFail = NA, DataSkip = NA,
Cores = 1, Label)
Arguments
BasecalledFast5
Logical. TRUE if dealing with basecalled .fast5 files. Defaulto to FALSE
Data

Path to GridION X5 folder containing .fastq and sequencing summary files (if
BasecalledFast5 = FALSE) or to basecalled .fast5 files (if BasecalledFast5 =
TRUE)

DataFail

Path to failed .fast5 files folder

DataSkip

Path to skipped .fast5 files folder

Cores

Number of cores to be used to accelerate sequencing summary files reading
(useful only if BasecalledFast5 = FALSE)

Label

Label used, together with the Flow Cell identifier extracted from the inputted
data, to identify your experiment: do not use underscore characters ("_").

Details
NanoPrepareg can find desired inputs recursively. DataSkip and DataFail can be omitted.
Value
Object of class list containing informations required by NanoTableG and NanoStatsG functions.
Examples
#do not run
#when working with sequencing summary files and .fastq files
Data<-"/data/basecalled/ExperimentName/FlowCellId"
NanoGList<-NanoPrepareG(BasecalledFast5=FALSE, Data=Data, Label="Ex", Cores=3)
#when working with basecalled .fast5 files
Pass<-"Path/to/workspace/pass"
Fail<-"Path/to/workspace/fail"
NanoGList<-NanoPrepareG(BasecalledFast5=TRUE, Data=Pass, DataFail=Fail, Label="Ex")

6

NanoPrepareM

NanoPrepareM

Prepares MinION data for your analyses with NanoR

Description
NanoPrepareM generates an object of class list that contains informations required by other functions from NanoR when analyzing MinION data

Usage
NanoPrepareM(DataPass, DataFail = NA, DataSkip = NA, Label)

Arguments
DataPass

Path to MinION passed .fast5 files folder

DataFail

Path to MinION failes .fast5 files folder

DataSkip

Path to MinION skipped .fast5 files folder

Label

Label to identify your MinION experiment

Details
NanoPreareM can find .fast5 files recursivel. DataFail and DataSkip can be omitted (MinKNOW
generates passed, failes and skipped .fast5 files folders but failed and skipped .fast5 files are taken
into account only for calculating their number and percentage)

Value
Object of class list

Examples
#do not run
PathPass<-"/Path/To/PassFast5"
Lab<-"Exp"
NanoMList<-NanoPrepareM(DataPass=PathPass, Label=Lab)

NanoStatsG

NanoStatsG

7

Plots statistics for your GridION X5 .fast5 files

Description
NanoStatsG plots statistics for passed .fast5 files and returns 4 tables used by NanoCompare
Usage
NanoStatsG(NanoPrepareGList, NanoGTable, DataOut)
Arguments
NanoPrepareGList
Object of class list returned by NanoPrepareG
NanoGTable

Table returned by NanoTableG

DataOut

Where NanoStatsG results will be saved. Use the same directory specified for
NanoTableG function and be sure that it doesn’t already contain NanoStatsM
(or NanoStatsG) results

Value
Plots:
- Cumulative_Reads_&_Cumulative_Basepairs.pdf;
- Reads_Basepairs_Length_Quality.pdf;
- Length_versus_Quality.pdf;
- Pass_Fail_Skip_and_GC_Content.pdf or Pass_Fail_Skip_NO_GC_Content.pdf;
- Channels_Activity.pdf or Channels_and_Muxes_Activity.pdf. Not-working channels and muxes
are grey-colored.
Examples
#do not run
#knows how to deal with different inputs type autonomously
NanoStatsG(NanoPrepareGList=NanoGList, NanoGTable=NanoGTable, DataOut="/Path/To/DataOutEx")

NanoStatsM

Plots statistics for your MinION .fast5 files

Description
NanoStatsM plots statistics for passed .fast5 files and returns 4 tables used by NanoCompare
Usage
NanoStatsM(NanoPrepareMList, NanoMTable, DataOut)

8

NanoTableG

Arguments
NanoPrepareMList
Object of class list returned by NanoPrepareM
NanoMTable

Table returned by NanoTableM

DataOut

Where NanoStatsM results will be saved. Use the same directory specified for
NanoTableM function and be sure that it doesn’t already contain NanoStatsM
(or NanoStatsG) results

Value
Plots:
- Cumulative_Reads_&_Cumulative_Basepairs.pdf;
- Reads_Basepairs_Length_Quality.pdf;
- Length_versus_Quality.pdf;
- Pass_Fail_Skip_and_GC_Content.pdf or Pass_Fail_Skip_NO_GC_Content.pdf;
- Channels_and_Muxes_Activity.pdf. Inactive channels and muxes are grey-colored
Examples
#do not run
NanoStatsM(NanoPrepareMList=NanoMList, NanoMTable=NanoMTable, DataOut="/Path/To/DataOutExp")

NanoTableG

Generates an information table for your GridION X5 .fast5 files

Description
NanoTableG generates a table that contains useful informations for each read identified by NanoPrepareG function. When analyzing GridION X5 basecalled .fast5 files, metadata extraction can be accelerated using multiple cores. Sometimes .fastq files returned by GridION X5 can be ill-formatted:
in this case, NanoTableG will stop and you can run this function again after set GCC to FALSE.
This problem can be avoided if basecalled .fast5 files are used.
Usage
NanoTableG(NanoPrepareGList, DataOut, Cores = 1, GCC = TRUE)
Arguments
NanoPrepareGList
Object of class list returned by NanoPrepareG function
DataOut

Where the table will be saved. Do not use a directory that already contains a
NanoTableM (or NanoTableG) result

Cores

Number of cores to be used: 1 by default. Does not affect time when dealing
with .fastq and sequencing summary files.

GCC

Logical. If TRUE, NanoTableM computes GC content for each read. Default to
TRUE

NanoTableM

9

Value
Table with 7 columns
Examples
#do not run
DataOut <- "/Path/To/DataOutEx"
#when working with sequencing summary files and .fastq files
NanoGTable<-NanoTableG(NanoPrepareGList=NanoGList, DataOut=DataOut) #set GCC to "FALSE" on error
#when working with basecalled .fast5 files
NanoGTable<-NanoTableG(NanoPrepareGList=NanoGList, DataOut=DataOut, GCC=TRUE, Cores=6)

Generates a metadata table for your MinION .fast5 files

NanoTableM

Description
NanoTableM generates a table that contains useful informations for each read of the "pass" .fast5
files folder given to NanoPrepareM function. As NanoTableM can take some time (it depends on
the number of reads it has to deal with), this function can be accelerated using multiple cores
Usage
NanoTableM(NanoPrepareMList, DataOut, Cores = 1, GCC = TRUE)
Arguments
NanoPrepareMList
Object of class list returned by NanoPrepareM
DataOut

Where the table will be saved. Do not use a directory that already contains a
NanoTableM (or NanoTableG) result

Cores

Number of cores to be used: 1 by default

GCC

Logical. If TRUE, NanoTableM computes GC content for each read. Default to
TRUE

Value
Table with 7 columns
Examples
#do not run
NanoMTable<-NanoTableM(NanoPrepareMList=NanoMList, DataOut="/Path/To/DataOutExp",Cores=6,GCC=TRUE)

Index
FastqFilterG, 2
NanoCompare, 3
NanoFastqG, 3
NanoFastqM, 4
NanoPrepareG, 5
NanoPrepareM, 6
NanoStatsG, 7
NanoStatsM, 7
NanoTableG, 8
NanoTableM, 9

10



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