(default: use empirical base frequencies) Nevertheless, we observed in practice that for the case the actual overlap sizes are relatively small, test 2 can correctly assemble more reads with only slightly higher false-positive rate.ĭisable empirical base frequencies. Therefore, this is not a valid statistical test and the 'p-value' is in fact the maximal probability for accepting the assembly. However, it assumes that the minimal overlap is the observed overlap with the highest OES, instead of the one specified by -v. This test methods computes the same probability as test method 1. Use the acceptance probability (m.a.p).For example, setting the cut-off to 0.05 using this test, the assembled reads might have an actual p-value of 0.02. Note that due to its discrete nature, this test usually yields a lower p-value for the assembled read than the cut-off (specified by -p). Given the minimum allowed overlap, test using the highest OES.The other extreme setting is 1 which causes PEAR to process all reads independent on the number of uncalled bases. Setting this value to 0 will cause PEAR to discard all reads containing uncalled bases. Specify the maximal proportion of uncalled bases in a read. If the quality scores of two consecutive bases are strictly less than the specified threshold, the rest of the read will be trimmed. Specify the quality score threshold for trimming the low quality part of a read. Specify the minimum length of reads after trimming the low quality part (see option -q). Setting this value to 0 disables the restriction and assembled sequences may be arbitrary short. Specify the minimum possible length of the assembled sequences. Setting this value to 0 disables the restriction and assembled sequences may be arbitrary long. Specify the maximum possible length of the assembled sequences. However, further restricting the minimum overlap size to a proper value may reduce false-positive assembles. The minimum overlap may be set to 1 when the statistical test is used. If the computed p-value of a possible assembly exceeds the specified p-value then the paired-end read will not be assembled. Specify a p-value for the statistical test. , and a file containing the discarded reads with a discarded.fastq extension. reverse, unassembled reads with extensions, resp. A file containing the assembled reads with a assembled.fastq extension, two files containing the forward, resp. Specify the name to be used as base for the output files. Specify the name of file that contains the reverse paired-end reads. Specify the name of file that contains the forward paired-end reads. The optional arguments affect the process of assemblying. PEAR runs in console-mode and takes a number of mandatory and optional arguments which are explained in the following sections. The above sequence of commands will install PEAR in a the directory $HOME/pear.Ĭurrently, there is no graphical user interface (GUI) for PEAR. Ubuntu), you can install all dependencies by running: If you are using a Debian based Linux distribution (e.g. You will need to install GNU Autotools and GNU Libtool for compiling the source code. If you intend to compile PEAR from source, make sure to get the source package. Binaries are available for Intel based architectures (i386 and x86_64) running Linux. PEAR sources and binaries are available on the official website. PEAR is available as source-code and also in the form of precompiled binaries. PEAR is distributed under the Creative Commons license, and it runs on the command-line under Linux and UNIX based operating systems. It is fully parallelized and can run with as low as just a few kilobytes of memory. PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger.
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