The following function can be used to call the SpliceMap binaries.
We recommend to use the QuasR package instead of using
SpliceMap directly. QuasR provides a simpler interface than
SpliceMap and covers the whole analysis workflow of typical ultra-high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification.
A list containing named elements with SpliceMap parameters (see sQuoteDetails or SpliceMap documentation).
SpliceMap function performes the same steps as the
runSpliceMap binary from the SpliceMap software package,
R functions to improve compatibility on Windows.
While the original SpliceMap software package is able to call
different tools to find sub-read alignments, the
function from the
Rbowtie package works only with
contained in the package itself. Further modifications from the
original version include the reporting of unmapped reads at the end of
the output sam file, and the restriction to a single (pair) of input
cfg argument is a list with SpliceMap configuration
parameters that would normally be specified using the SpliceMap
configuration file. Here is a list of supported parameters extracted
from the sample config file that is distributed with SpliceMap:
genome_dir (single character value)
Directory of the chromosome files in FASTA format, or path to a
single FASTA file containing all chromosomes. If a directory, each chromosome
can be in a separate file or chromosomes can be concatenated, ie. chr1.fa, chr2.fa, ...
reads_list2 (single character values)
These are the two input sequence files.
reads_list2 can be
missing if reads are not paired-end. Note:
be the first pair, and pair-reads should be in the
read_format (single character value)
Format of the sequencer reads, also make sure reads are not split
over multiple lines. Choices are:
quality_format (single character value)
Format of the quality string if FASTQ is used. Choices are:
phred-33 Phred base 33 (same as Sanger format)
phred-64 Phred base 64 (same as Illumina 1.3+)
solexa Format used by solexa machines
outfile (single character value)
Name of the output file (spliced alignments in SAM format). If a
file with this name already exists,
SpliceMap will stop with
an exception. Note that unmapped reads will be appended to the end
of the output file (for paired-end experiments, only pairs without
alignments for any read are considered unmapped).
temp_path (single character value)
Directory name of the directory that stores temporary files. All
temporary files will be created in a subfolder of
temp_path and will be removed when
successfully or failed at an intermediate step.
max_intron (single integer value)
Maximum intron size, this is absolute 99th-percentile
maximum. Introns beyond this size will be ignored. If you don't set
this, we will assume a mamalian genome (400,000)
min_intron (single integer value)
25-th intron size, this is the lower 25th-percentile intron
size. This is not the smallest size that SpliceMap will search. That
is about ~25bp. If you don't set this, we will assume a mammalian
max_multi_hit (single integer value)
Maximum number of multi-hits. If a 25-mer seed has more than this
many multi-hits, it will be discarded. Default is 10.
full_read_length (single integer value)
Full read length. SpliceMap will only use the first
“full_read_length” bp for mapping. If the read is shorter
than “full_read_length”, the full read will be used before
head clip. If you don't set this parameter, SpliceMap will use as
many as possible. This is for the case where the reads might have
N's at the end. It is always desireable to cut off the N's
head_clip_length (single integer value)
Number of bases to clip off the head of the read. This clipping is
applied after “full_read_length”
seed_mismatch (single integer value)
Number of mismatches allowed in half-seeding. Choices are
0,1(default) or 2
read_mismatch (single integer value)
Maximum number of mismatches allowed in entire read. No limit on
value, however SpliceMap can only identify reads with a maximum of 2
mismatches per 25bp. Default is 2.
max_clip_allowed (single integer value)
Maximum number of bases allowed to be soft clipped from the ends of
reads during alignment. This is required as mismatches near
junctions could cause parts of a a read to not map. Default is 40.
num_chromosome_together (single integer value)
Number of chromosomes to process at once, to take advantage of
multi-core systems. The child processes are created using the
makeCluster function from the parallel
package. This is not threading, so it will take extra
memory. However, running 2 at a time should be fine on current
hardware. Default = 2
bowtie_base_dir (single character value)
Base of bowtie index, this should be the same genome as the
chromosome files eg. if you bowtie files are
“genome/hg18/genome.1.ewbt”, ... then your base dir is
num_threads (single integer values)
Number of threads to use for
bowtie mapping. Default value is 2
try_hard (single character value)
Try hard? Choices are “yes” or “no”. Default value is
“yes” (about 15% slower).
selectSingleHit (single logical value)
TRUE and multiple alignments are found for a read (pair),
only a single alignment is selected randomly and reported. This is a
new paramater only available in the
R version of
SpliceMap, but not in the original implementation that could
report several alignments per read (pair).
The following parameters are mandatory:
reads_list2 for paired-end experiments)
An invisible character vector of length one with the file name of the generated output SAM file.
An exception is thrown if a failure is detected at one of the many steps.
Au KF, Jiang H, Lin L, Xing Y, Wong WH. Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Research, 38(14):4570-8 (2010).
makeCluster from package parallel
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## Building a bowtie index refDir <- system.file(package="Rbowtie", "samples", "refs") indexDir <- file.path(tempdir(), "refsIndex") tmp <- bowtie_build(references=dir(refDir, full=TRUE), outdir=indexDir, prefix="index", force=TRUE) ## Alignments readsFiles <- system.file(package="Rbowtie", "samples", "reads", "reads.fastq") samFiles <- file.path(tempdir(), "splicedAlignments.sam") cfg <- list(genome_dir=refDir, reads_list1=readsFiles, read_format="FASTQ", quality_format="phred-33", outfile=samFiles, temp_path=tempdir(), max_intron=400000, min_intron=20000, max_multi_hit=10, seed_mismatch=1, read_mismatch=2, num_chromosome_together=2, bowtie_base_dir=file.path(indexDir, "index"), num_threads=4, try_hard="yes", selectSingleHit=TRUE) res <- SpliceMap(cfg)
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