Package 'PICB'

Title: piRNA Cluster Builder
Description: piRNAs (short for PIWI-interacting RNAs) and their PIWI protein partners play a key role in fertility and maintaining genome integrity by restricting mobile genetic elements (transposons) in germ cells. piRNAs originate from genomic regions known as piRNA clusters. The piRNA Cluster Builder (PICB) is a versatile toolkit designed to identify genomic regions with a high density of piRNAs. It constructs piRNA clusters through a stepwise integration of unique and multimapping piRNAs and offers wide-ranging parameter settings, supported by an optimization function that allows users to test different parameter combinations to tailor the analysis to their specific piRNA system. The output includes extensive metadata columns, enabling researchers to rank clusters and extract cluster characteristics.
Authors: Pavol Genzor [aut], Aleksandr Friman [aut], Daniel Stoyko [aut], Parthena Konstantinidou [aut], Franziska Ahrend [aut, cre] , Zuzana Loubalova [aut], Yuejun Wang [aut], Hernan Lorenzi [aut], Astrid D Haase [aut]
Maintainer: Franziska Ahrend <[email protected]>
License: CC0
Version: 0.99.15
Built: 2025-02-07 03:27:20 UTC
Source: https://github.com/bioc/PICB

Help Index

Annotate GRanges according to a piRNA library

Description

Annotate GRanges according to a piRNA library

Usage

PICBannotate(
  INPUT.GRANGES,
  ALIGNMENTS,
  REFERENCE.GENOME = NULL,
  REPLICATE.NAME = NULL,
  LIBRARY.SIZE = length(ALIGNMENTS$unique) + length(ALIGNMENTS$multi.primary),
  PROVIDE.NON.NORMALIZED = FALSE,
  SEQ.LEVELS.STYLE = "UCSC",
  COMPUTE.1U.10A.FRACTIONS = FALSE
)

Arguments

INPUT.GRANGES

GRanges (seeds/cores/clusters) to annotate
ALIGNMENTS

list of alignments from PICBload
REFERENCE.GENOME

name of genome. For example "BSgenome.Dmelanogaster.UCSC.dm6"
REPLICATE.NAME

name of the replicate. NULL by default.
LIBRARY.SIZE

number of reads in the library. By default computed as number of unique mapping alignments + number of primary multimapping alignments.
PROVIDE.NON.NORMALIZED

provide annotations in non-normalized format. False by default.
SEQ.LEVELS.STYLE

naming of chromosomes style. "UCSC" by default.
COMPUTE.1U.10A.FRACTIONS

for each locus and each alignments type (unique mapping, primary multimapping, secodnary multimapping) compute fraction 1U and 10A containing reads overlapping the locus. Default FALSE.

Value

GRanges object with extra annotation columns

Author(s)

Aleksandr Friman

Examples

library(BSgenome.Dmelanogaster.UCSC.dm6)
myGenome <- "BSgenome.Dmelanogaster.UCSC.dm6"
myAlignmentsFromPICBload <- PICBload(
    BAMFILE = system.file("extdata", "Fly_Ov1_chr2L_20To21mb_filtered.bam", package = "PICB"),
    REFERENCE.GENOME = myGenome,
    VERBOSE = FALSE
)
myRangesFromPICBbuild <- PICBbuild(
    IN.ALIGNMENTS = myAlignmentsFromPICBload,
    REFERENCE.GENOME = myGenome,
    VERBOSITY = 0
)

myClustersFromPICBbuildAnnotationsRemoved <- GenomicRanges::granges(myRangesFromPICBbuild$clusters)

PICBannotate(
    INPUT.GRANGES = myClustersFromPICBbuildAnnotationsRemoved,
    ALIGNMENTS = myAlignmentsFromPICBload,
    REFERENCE.GENOME = myGenome,
    PROVIDE.NON.NORMALIZED = TRUE
)

Build piRNA seeds/cores/clusters from alignments

Description

Build piRNA seeds/cores/clusters from alignments

Usage

PICBbuild(
  IN.ALIGNMENTS,
  REFERENCE.GENOME,
  UNIQUEMAPPERS.SLIDING.WINDOW.WIDTH = 350,
  UNIQUEMAPPERS.SLIDING.WINDOW.STEP = round(UNIQUEMAPPERS.SLIDING.WINDOW.WIDTH/10, 0),
  PRIMARY.MULTIMAPPERS.SLIDING.WINDOW.WIDTH = 350,
  PRIMARY.MULTIMAPPERS.SLIDING.WINDOW.STEP =
    round(PRIMARY.MULTIMAPPERS.SLIDING.WINDOW.WIDTH/10, 0),
  SECONDARY.MULTIMAPPERS.SLIDING.WINDOW.WIDTH = 1000,
  SECONDARY.MULTIMAPPERS.SLIDING.WINDOW.STEP =
    round(SECONDARY.MULTIMAPPERS.SLIDING.WINDOW.WIDTH/10, 0),
  LIBRARY.SIZE = length(IN.ALIGNMENTS$unique) + length(IN.ALIGNMENTS$multi.primary),
  MIN.UNIQUE.ALIGNMENTS.PER.WINDOW = 2 * (UNIQUEMAPPERS.SLIDING.WINDOW.WIDTH/1000) *
    (LIBRARY.SIZE/1e+06),
  MIN.UNIQUE.SEQUENCES.PER.WINDOW = min(MIN.UNIQUE.ALIGNMENTS.PER.WINDOW,
    round(UNIQUEMAPPERS.SLIDING.WINDOW.WIDTH/50, 0)),
  MIN.PRIMARY.MULTIMAPPING.ALIGNMENTS.PER.WINDOW = 4 *
    (PRIMARY.MULTIMAPPERS.SLIDING.WINDOW.WIDTH/1000) * (LIBRARY.SIZE/1e+06),
  MIN.SECONDARY.MULTIMAPPING.ALIGNMENTS.PER.WINDOW = 0.2 *
    (SECONDARY.MULTIMAPPERS.SLIDING.WINDOW.WIDTH/1000) * (LIBRARY.SIZE/1e+06),
  MIN.SEED.LENGTH = 2 * UNIQUEMAPPERS.SLIDING.WINDOW.WIDTH + 100,
  MIN.COVERED.SEED.LENGTH = 0,
  THRESHOLD.SEEDS.GAP = 0,
  THRESHOLD.CORES.GAP = 0,
  THRESHOLD.CLUSTERS.GAP = 0,
  SEQ.LEVELS.STYLE = "UCSC",
  MIN.OVERLAP = 5,
  PROVIDE.NON.NORMALIZED = FALSE,
  COMPUTE.1U.10A.FRACTIONS = FALSE,
  VERBOSITY = 2
)

Arguments

IN.ALIGNMENTS

list of alignments from PICBload
REFERENCE.GENOME

name of genome. For example "BSgenome.Dmelanogaster.UCSC.dm6"
UNIQUEMAPPERS.SLIDING.WINDOW.WIDTH

width of sliding window for unique mappers. 350 nt by default
UNIQUEMAPPERS.SLIDING.WINDOW.STEP

step of sliding windows for unique mappers. width/10 by default
PRIMARY.MULTIMAPPERS.SLIDING.WINDOW.WIDTH

width of sliding window for primary multimapping alignments. 350 nt by default
PRIMARY.MULTIMAPPERS.SLIDING.WINDOW.STEP

step of sliding windows for primary multimapping alignments. width/10 by default
SECONDARY.MULTIMAPPERS.SLIDING.WINDOW.WIDTH

width of sliding window for secondary multimapping alignments. 1000 nt by default
SECONDARY.MULTIMAPPERS.SLIDING.WINDOW.STEP

step of sliding windows for secondary multimapping alignments. width/10 by default
LIBRARY.SIZE

number of reads in the library. By default computed as number of unique mapping alignments + number of primary multimapping alignments.
MIN.UNIQUE.ALIGNMENTS.PER.WINDOW

absolute number of unique mapping alignments per window to call it. By default computed as 2 FPKM.
MIN.UNIQUE.SEQUENCES.PER.WINDOW

absolute number of unique mapping sequences per window to call it. By default computed as width/50.
MIN.PRIMARY.MULTIMAPPING.ALIGNMENTS.PER.WINDOW

absolute number of primary multimapping alignments per window to call it. By default computed as 4 FPKM.
MIN.SECONDARY.MULTIMAPPING.ALIGNMENTS.PER.WINDOW

absolute number of secondary multimapping alignments per window to call it. By default computed as 0.2 FPKM.
MIN.SEED.LENGTH

minimum length of a seed. By default computed as 2x unique mapper window size + 100.
MIN.COVERED.SEED.LENGTH

minimum number of seed nucleotides covered by unique mappers. 0 by default.
THRESHOLD.SEEDS.GAP

minimum gap between seeds to not merge them. 0 by default.
THRESHOLD.CORES.GAP

minimum gap between cores to not merge them. 0 by default.
THRESHOLD.CLUSTERS.GAP

minimum gap between clusters to not merge them. 0 by default.
SEQ.LEVELS.STYLE

naming of chromosomes style. "UCSC" by default.
MIN.OVERLAP

minimum overlap between seeds and cores, as well as between cores and clusters 5 nt by default.
PROVIDE.NON.NORMALIZED

include non-normalized to the library size statistics in the output annotations
COMPUTE.1U.10A.FRACTIONS

for each locus and each alignments type (unique mapping, primary multimapping, secodnary multimapping) compute fraction 1U and 10A containing reads overlapping the locus. Default FALSE.
VERBOSITY

verbosity level 0/1/2/3. 2 by default.

Value

list of annotated GRanges objects named "seeds" for seeds, "cores" for cores, "clusters" for clusters

Author(s)

Pavol Genzor

Daniel Stoyko

Aleksandr Friman

Franziska Ahrend

Examples

library(BSgenome.Dmelanogaster.UCSC.dm6)
myAlignmentsFromPICBload <- PICBload(
    BAMFILE = system.file("extdata", "Fly_Ov1_chr2L_20To21mb_filtered.bam", package = "PICB"),
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    VERBOSE = FALSE
)

outputOfPICBbuild <- PICBbuild(
    IN.ALIGNMENTS = myAlignmentsFromPICBload,
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    VERBOSITY = 0
)

Export cluster object into an Excel file

Description

Export cluster object into an Excel file

Usage

PICBexporttoexcel(IN.RANGES = NULL, EXCEL.FILE.NAME = NULL)

Arguments

IN.RANGES

clustering object to export
EXCEL.FILE.NAME

file name to save

Value

no values returned

Author(s)

Aleksandr Friman

Franziska Ahrend

Examples

library(BSgenome.Dmelanogaster.UCSC.dm6)
myAlignmentsFromPICBload <- PICBload(
    BAMFILE = system.file("extdata", "Fly_Ov1_chr2L_20To21mb_filtered.bam", package = "PICB"),
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    VERBOSE = FALSE
)

outputOfPICBbuild <- PICBbuild(
    IN.ALIGNMENTS = myAlignmentsFromPICBload,
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    LIBRARY.SIZE = 12799826, #usually not necessary
    VERBOSITY = 0
)
PICBexporttoexcel(
    IN.RANGES = outputOfPICBbuild,
    EXCEL.FILE.NAME = "inst/extdata/myClusters_demonstration.xlsx"
)

Get SeqInfo object from standard non-circular chromosome names from your genome

Description

Get SeqInfo object from standard non-circular chromosome names from your genome

Usage

PICBgetchromosomes(REFERENCE.GENOME, SEQ.LEVELS.STYLE = "UCSC")

Arguments

REFERENCE.GENOME

name of genome. For example "BSgenome.Dmelanogaster.UCSC.dm6", or directly a SeqInfo object.
SEQ.LEVELS.STYLE

naming of chromosomes style. "UCSC" by default.

Value

SeqInfo object with standard non-circular chromosome names

Author(s)

Aleksandr Friman

Franziska Ahrend

Examples

library(BSgenome.Dmelanogaster.UCSC.dm6)
mySI <- PICBgetchromosomes("BSgenome.Dmelanogaster.UCSC.dm6", "UCSC")

Import cluster object from an Excel file

Description

Import cluster object from an Excel file

Usage

PICBimportfromexcel(EXCEL.FILE.NAME = NULL)

Arguments

EXCEL.FILE.NAME

file name to import from

Value

list of annotated GRanges objects named "seeds" for seeds, "cores" for cores, "clusters" for clusters

Author(s)

Aleksandr Friman

Examples

importedClusters <- PICBimportfromexcel(
    EXCEL.FILE.NAME = system.file("extdata", "myClusters_demonstration.xlsx", package = "PICB")
)

Load and preprocess BAM files containing piRNA alignments

Description

Load and preprocess BAM files containing piRNA alignments

Usage

PICBload(
  BAMFILE = NULL,
  REFERENCE.GENOME = NULL,
  SIMPLE.CIGAR = TRUE,
  IS.SECONDARY.ALIGNMENT = NA,
  STANDARD.CONTIGS.ONLY = TRUE,
  PERFECT.MATCH.ONLY = FALSE,
  FILTER.BY.FLAG = TRUE,
  SELECT.FLAG = c(0, 16, 272, 256),
  USE.SIZE.FILTER = TRUE,
  READ.SIZE.RANGE = c(18, 50),
  TAGS = c("NH", "NM"),
  WHAT = c("flag"),
  SEQ.LEVELS.STYLE = "UCSC",
  GET.ORIGINAL.SEQUENCE = FALSE,
  VERBOSE = TRUE
)

Arguments

BAMFILE

name of the bam file to load. Should be sorted and indexed.
REFERENCE.GENOME

name of genome. For example "BSgenome.Dmelanogaster.UCSC.dm6"
SIMPLE.CIGAR

simpleCigar parameter of Rsamtools::ScanBamParam
IS.SECONDARY.ALIGNMENT

defines loading of primary/secondary alignments. Default value NA loads both primary and secondary.
STANDARD.CONTIGS.ONLY

use only standard chromosomes
PERFECT.MATCH.ONLY

load only alignments without mismatches
FILTER.BY.FLAG

enables filtering by flag. TRUE by default.
SELECT.FLAG

vector of flags to use. Default value c(0,16, 272, 256).
USE.SIZE.FILTER

enables filter by alignment size. True by default.
READ.SIZE.RANGE

allowed alignment sizes. c(18,50) by default.
TAGS

tags to import from bam file. c("NH","NM") by default.
WHAT

"what" parameter of Rsamtools::ScanBamParam. c("flag") by default.
SEQ.LEVELS.STYLE

naming of chromosomes style. "UCSC" by default.
GET.ORIGINAL.SEQUENCE

adds "seq" to WHAT. False by default.
VERBOSE

enables progress output. True by default.

Value

list of GRanges objects named "unique" for unique mapping alignments, "multi.primary" for primary multimapping alignments, "multi.secondary" for secondary multimapping alignments

Author(s)

Pavol Genzor

Daniel Stoyko

Aleksandr Friman

Franziska Ahrend

Examples

library(BSgenome.Dmelanogaster.UCSC.dm6)
PICBload(
    BAMFILE = system.file("extdata", "Fly_Ov1_chr2L_20To21mb_filtered.bam", package = "PICB"),
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    VERBOSE = FALSE
)

Get SeqInfo object from a fasta file

Description

Get SeqInfo object from a fasta file

Usage

PICBloadfasta(FASTA.NAME = NULL)

Arguments

FASTA.NAME

path to the fasta file

Value

SeqInfo object with all chromosome names and lengths from the fasta file

Author(s)

Aleksandr Friman

Examples

library(BSgenome.Dmelanogaster.UCSC.dm6)

# create temporary fasta file
chr2L_seq <- BSgenome.Dmelanogaster.UCSC.dm6[["chr2L"]]
chr2L_seq_set <- DNAStringSet(chr2L_seq)
names(chr2L_seq_set) <- "chr2L"
temp_fasta <- tempfile(fileext = ".fasta")
writeXStringSet(chr2L_seq_set, temp_fasta)

myGenome <- PICBloadfasta(FASTA.NAME = temp_fasta)
unlink(temp_fasta)

Runs PICBbuild multiple times with provided parameters and returns optimization data frame.

Description

Runs PICBbuild multiple times with provided parameters and returns optimization data frame.

Usage

PICBoptimize(
  IN.ALIGNMENTS,
  REFERENCE.GENOME,
  LIBRARY.SIZE = length(IN.ALIGNMENTS$unique) + length(IN.ALIGNMENTS$multi.primary),
  VERBOSITY = 2,
  PROVIDE.INFO.SEEDS.AND.CORES = FALSE,
  SEQ.LEVELS.STYLE = "UCSC",
  ...
)

Arguments

IN.ALIGNMENTS

list of alignments from PICBload
REFERENCE.GENOME

name of genome. For example "BSgenome.Dmelanogaster.UCSC.dm6"
LIBRARY.SIZE

number of reads in the library. By default computed as number of unique mapping alignments + number of primary multimapping alignments.
VERBOSITY

verbosity level 0/1/2/3. 2 by default.
PROVIDE.INFO.SEEDS.AND.CORES

FALSE by default.
SEQ.LEVELS.STYLE

naming of chromosomes style. "UCSC" by default.
...

rest of the parameters used by PICBbuild and provided as iteratable vectors

Value

Optimization values dataframe

Author(s)

Aleksandr Friman

Examples

library(BSgenome.Dmelanogaster.UCSC.dm6)
myAlignmentsFromPICBload <- PICBload(
    BAMFILE = system.file("extdata", "Fly_Ov1_chr2L_20To21mb_filtered.bam", package = "PICB"),
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    VERBOSE = FALSE
)

PICBoptimize(
    IN.ALIGNMENTS = myAlignmentsFromPICBload,
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    MIN.UNIQUE.ALIGNMENTS.PER.WINDOW = c(1, 2, 3, 4, 5)
)

Add sense/antisense ratio of unique piRNAs per piRNA cluster

Description

Add sense/antisense ratio of unique piRNAs per piRNA cluster

Usage

PICBstrandanalysis(IN.ALIGNMENTS, IN.RANGES, VERBOSE = TRUE)

Arguments

IN.ALIGNMENTS

list of alignments from PICBload
IN.RANGES

single GRanges object (seeds, cores or clusters from PICBbuild)
VERBOSE

enables progress output. True by default.

Value

GRanges object with an additional annotation column

Author(s)

Parthena Konstantinidou

Zuzana Loubalova

Franziska Ahrend

Examples

library(BSgenome.Dmelanogaster.UCSC.dm6)
myAlignmentsFromPICBload <- PICBload(
    BAMFILE = system.file("extdata", "Fly_Ov1_chr2L_20To21mb_filtered.bam", package = "PICB"),
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    VERBOSE = FALSE
)

outputOfPICBbuild <- PICBbuild(
    IN.ALIGNMENTS = myAlignmentsFromPICBload,
    REFERENCE.GENOME = "BSgenome.Dmelanogaster.UCSC.dm6",
    VERBOSITY = 0
)

outputOfPICBbuild$clusters <- PICBstrandanalysis(
    IN.ALIGNMENTS = myAlignmentsFromPICBload,
    IN.RANGES = outputOfPICBbuild$clusters
)