* [Usage](#usage)
* [Example](#example)
* [Simulation](#simulation)
+* [Generate Transcript-to-Gene-Map from Trinity Output](#gen_trinity)
* [Acknowledgements](#acknowledgements)
* [License](#license)
* * *
-<h2 id="introduction">Introduction</h2>
+## <a name="introduction"></a> Introduction
RSEM is a software package for estimating gene and isoform expression
levels from RNA-Seq data. The new RSEM package (rsem-1.x) provides an
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
-estimates for expression levels.
+estimates for expression levels.
-<h2 id="compilation">Compilation & Installation</h2>
+## <a name="compilation"></a> Compilation & Installation
To compile RSEM, simply run
### Prerequisites
+C++ and Perl are required to be 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.
-## Usage <a name="usage"></a>
+If you want to plot model learned by RSEM, you should also install R.
+
+## <a name="usage"></a> Usage
### I. Preparing Reference Sequences
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.
+
### III. Visualization
RSEM contains a version of samtools in the 'sam' subdirectory. When
Refer to the [UCSC custom track help page](http://genome.ucsc.edu/goldenPath/help/customTrack.html).
-<h2 id="example">Example</h2>
+#### c) Visualize the model learned by RSEM
+
+RSEM provides an R script, 'rsem-plot-model', for visulazing the model learned.
+
+Usage:
+
+ rsem-plot-model sample_name outF
+
+sample_name: the name of the sample analyzed
+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
+error given a reference base and histogram of reads with different
+number of alignments.
+
+fragment length distribution and mate length distribution: x-axis is fragment/mate length, y axis is the probability of generating a fragment/mate with the associated length
+
+RSPD: Read Start Position Distribution. x-axis is bin number, y-axis is the probability of each bin. RSPD can be used as an indicator of 3' bias
+
+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
+
+Histogram of reads with different number of alignments: x-axis is the number of alignments a read has and y-axis is the number of such reads. The inf in x-axis means number of reads filtered due to too many alignments
+
+## <a name="example"></a> Example
Suppose we download the mouse genome from UCSC Genome Browser. We will
use a reference_name of 'mm9'. We have a FASTQ-formatted file,
rsem-calculate-expression --bowtie-path /sw/bowtie --phred64-quals --fragment-length-mean 150.0 --fragment-length-sd 35.0 -p 8 --out-bam --calc-ci --memory-allocate 1024 /data/mmliver.fq /ref/mm9 mmliver_single_quals
rsem-bam2wig mmliver_single_quals.sorted.bam mmliver_single_quals.sorted.wig mmliver_single_quals
-<h2 id="simulation">Simulation</h2>
+## <a name="simulation"></a> Simulation
### Usage:
rsem-simulate-reads reference_name estimated_model_file estimated_isoform_results theta0 N output_name [-q]
-estimated_model_file: File containing model parameters. Generated by
+estimated_model_file: file containing model parameters. Generated by
rsem-calculate-expression.
-estimated_isoform_results: File containing isoform expression levels.
+estimated_isoform_results: file containing isoform expression levels.
Generated by rsem-calculate-expression.
theta0: fraction of reads that are "noise" (not derived from a transcript).
N: number of reads to simulate.
output_name.sim.isoforms.results, output_name.sim.genes.results : Results estimated based on sample values.
-<h2 id="acknowledgements">Acknowledgements</h2>
+## <a name="gen_trinity"></a> Generate Transcript-to-Gene-Map from Trinity Output
+
+For Trinity users, RSEM provides a perl script to generate transcript-to-gene-map file from the fasta file produced by Trinity.
+
+### Usage:
+
+ extract-transcript-to-gene-map-from-trinity trinity_fasta_file map_file
+
+trinity_fasta_file: the fasta file produced by trinity, which contains all transcripts assembled.
+map_file: transcript-to-gene-map file's name.
+
+## <a name="acknowledgements"></a> Acknowledgements
-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
[samtools](http://samtools.sourceforge.net) libraries.
-<h2 id="license">License</h2>
+## <a name="license"></a> License
RSEM is licensed under the [GNU General Public License v3](http://www.gnu.org/licenses/gpl-3.0.html).
projects / rsem.git / blobdiff