variable-length reads and RSPD estimation. It can also generate
genomic-coordinate BAM files and UCSC wiggle files for visualization. In
addition, it provides posterior mean and 95% credibility interval
variable-length reads and RSPD estimation. It can also generate
genomic-coordinate BAM files and UCSC wiggle files for visualization. In
addition, it provides posterior mean and 95% credibility interval
To take advantage of RSEM's built-in support for the Bowtie alignment
program, you must have [Bowtie](http://bowtie-bio.sourceforge.net) installed.
To take advantage of RSEM's built-in support for the Bowtie alignment
program, you must have [Bowtie](http://bowtie-bio.sourceforge.net) installed.
alternative aligner, you may also want to provide the --no-bowtie option
to rsem-prepare-reference so that the Bowtie indices are not built.
alternative aligner, you may also want to provide the --no-bowtie option
to rsem-prepare-reference so that the Bowtie indices are not built.
+However, please note that RSEM does ** not ** support gapped
+alignments. So make sure that your aligner does not produce alignments
+with intersions/deletions. Also, please make sure that you use
+'reference_name.idx.fa' , which is generated by RSEM, to build your
+aligner's indices.
+
outF: the file name for plots generated from the model. It is a pdf file
The plots generated depends on read type and user configuration. It
may include fragment length distribution, mate length distribution,
read start position distribution (RSPD), quality score vs observed
quality given a reference base, position vs percentage of sequencing
outF: the file name for plots generated from the model. It is a pdf file
The plots generated depends on read type and user configuration. It
may include fragment length distribution, mate length distribution,
read start position distribution (RSPD), quality score vs observed
quality given a reference base, position vs percentage of sequencing
Quality score vs. observed quality given a reference base: x-axis is Phred quality scores associated with data, y-axis is the "observed quality", Phred quality scores learned by RSEM from the data. Q = -10log_10(P), where Q is Phred quality score and P is the probability of sequencing error for a particular base
Position vs. percentage sequencing error given a reference base: x-axis is position and y-axis is percentage sequencing error
Quality score vs. observed quality given a reference base: x-axis is Phred quality scores associated with data, y-axis is the "observed quality", Phred quality scores learned by RSEM from the data. Q = -10log_10(P), where Q is Phred quality score and P is the probability of sequencing error for a particular base
Position vs. percentage sequencing error given a reference base: x-axis is position and y-axis is percentage sequencing error
-RSEM uses randomc.h and mersenne.cpp from
-<http://lxnt.info/rng/randomc.htm> for random number generation. RSEM
-also uses the [Boost C++](http://www.boost.org) and
+RSEM uses the [Boost C++](http://www.boost.org) and