4 [Bo Li](http://pages.cs.wisc.edu/~bli) \(bli at cs dot wisc dot edu\)
11 * [Introduction](#introduction)
12 * [Compilation & Installation](#compilation)
15 * [Simulation](#simulation)
16 * [Acknowledgements](#acknowledgements)
21 ## <a name="introduction"></a> Introduction
23 RSEM is a software package for estimating gene and isoform expression
24 levels from RNA-Seq data. The new RSEM package (rsem-1.x) provides an
25 user-friendly interface, supports threads for parallel computation of
26 the EM algorithm, single-end and paired-end read data, quality scores,
27 variable-length reads and RSPD estimation. It can also generate
28 genomic-coordinate BAM files and UCSC wiggle files for visualization. In
29 addition, it provides posterior mean and 95% credibility interval
30 estimates for expression levels.
32 ## <a name="compilation"></a> Compilation & Installation
34 To compile RSEM, simply run
38 To install, simply put the rsem directory in your environment's PATH
43 C++ and Perl are required to be installed.
45 To take advantage of RSEM's built-in support for the Bowtie alignment
46 program, you must have [Bowtie](http://bowtie-bio.sourceforge.net) installed.
48 If you want to plot model learned by RSEM, you should also install R.
50 ## <a name="usage"></a> Usage
52 ### I. Preparing Reference Sequences
54 RSEM can extract reference transcripts from a genome if you provide it
55 with gene annotations in a GTF file. Alternatively, you can provide
56 RSEM with transcript sequences directly.
58 Please note that GTF files generated from the UCSC Table Browser do not
59 contain isoform-gene relationship information. However, if you use the
60 UCSC Genes annotation track, this information can be recovered by
61 downloading the knownIsoforms.txt file for the appropriate genome.
63 To prepare the reference sequences, you should run the
64 'rsem-prepare-reference' program. Run
66 rsem-prepare-reference --help
68 to get usage information or visit the [rsem-prepare-reference
69 documentation page](http://deweylab.biostat.wisc.edu/rsem/rsem-prepare-reference.html).
71 ### II. Calculating Expression Values
73 To calculate expression values, you should run the
74 'rsem-calculate-expression' program. Run
76 rsem-calculate-expression --help
78 to get usage information or visit the [rsem-calculate-expression
79 documentation page](http://deweylab.biostat.wisc.edu/rsem/rsem-calculate-expression.html).
81 #### Calculating expression values from single-end data
83 For single-end models, users have the option of providing a fragment
84 length distribution via the --fragment-length-mean and
85 --fragment-length-sd options. The specification of an accurate fragment
86 length distribution is important for the accuracy of expression level
87 estimates from single-end data. If the fragment length mean and sd are
88 not provided, RSEM will not take a fragment length distribution into
91 #### Using an alternative aligner
93 By default, RSEM automates the alignment of reads to reference
94 transcripts using the Bowtie alignment program. To use an alternative
95 alignment program, align the input reads against the file
96 'reference_name.idx.fa' generated by rsem-prepare-reference, and format
97 the alignment output in SAM or BAM format. Then, instead of providing
98 reads to rsem-calculate-expression, specify the --sam or --bam option
99 and provide the SAM or BAM file as an argument. When using an
100 alternative aligner, you may also want to provide the --no-bowtie option
101 to rsem-prepare-reference so that the Bowtie indices are not built.
103 However, please note that RSEM does ** not ** support gapped
104 alignments. So make sure that your aligner does not produce alignments
105 with intersions/deletions. Also, please make sure that you use
106 'reference_name.idx.fa' , which is generated by RSEM, to build your
109 ### III. Visualization
111 RSEM contains a version of samtools in the 'sam' subdirectory. When
112 users specify the --out-bam option RSEM will produce three files:
113 'sample_name.bam', the unsorted BAM file, 'sample_name.sorted.bam' and
114 'sample_name.sorted.bam.bai' the sorted BAM file and indices generated
115 by the samtools included.
117 #### a) Generating a UCSC Wiggle file
119 A wiggle plot representing the expected number of reads overlapping
120 each position in the genome can be generated from the sorted BAM file
121 output. To generate the wiggle plot, run the 'rsem-bam2wig' program on
122 the 'sample_name.sorted.bam' file.
126 rsem-bam2wig bam_input wig_output wiggle_name
128 bam_input: sorted bam file
129 wig_output: output file name, e.g. output.wig
130 wiggle_name: the name the user wants to use for this wiggle plot
132 #### b) Loading a BAM and/or Wiggle file into the UCSC Genome Browser
134 Refer to the [UCSC custom track help page](http://genome.ucsc.edu/goldenPath/help/customTrack.html).
136 #### c) Visualize the model learned by RSEM
138 RSEM provides an R script, 'rsem-plot-model', for visulazing the model learned.
142 rsem-plot-model sample_name outF
144 sample_name: the name of the sample analyzed
145 outF: the file name for plots generated from the model. It is a pdf file
147 The plots generated depends on read type and user configuration. It
148 may include fragment length distribution, mate length distribution,
149 read start position distribution (RSPD), quality score vs observed
150 quality given a reference base, position vs percentage of sequencing
151 error given a reference base and histogram of reads with different
152 number of alignments.
154 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
156 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
158 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
160 Position vs. percentage sequencing error given a reference base: x-axis is position and y-axis is percentage sequencing error
162 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
164 ## <a name="example"></a> Example
166 Suppose we download the mouse genome from UCSC Genome Browser. We will
167 use a reference_name of 'mm9'. We have a FASTQ-formatted file,
168 'mmliver.fq', containing single-end reads from one sample, which we call
169 'mmliver_single_quals'. We want to estimate expression values by using
170 the single-end model with a fragment length distribution. We know that
171 the fragment length distribution is approximated by a normal
172 distribution with a mean of 150 and a standard deviation of 35. We wish
173 to generate 95% credibility intervals in addition to maximum likelihood
174 estimates. RSEM will be allowed 1G of memory for the credibility
175 interval calculation. We will visualize the probabilistic read mappings
178 The commands for this scenario are as follows:
180 rsem-prepare-reference --gtf mm9.gtf --mapping knownIsoforms.txt --bowtie-path /sw/bowtie /data/mm9 /ref/mm9
181 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
182 rsem-bam2wig mmliver_single_quals.sorted.bam mmliver_single_quals.sorted.wig mmliver_single_quals
184 ## <a name="simulation"></a> Simulation
188 rsem-simulate-reads reference_name estimated_model_file estimated_isoform_results theta0 N output_name [-q]
190 estimated_model_file: File containing model parameters. Generated by
191 rsem-calculate-expression.
192 estimated_isoform_results: File containing isoform expression levels.
193 Generated by rsem-calculate-expression.
194 theta0: fraction of reads that are "noise" (not derived from a transcript).
195 N: number of reads to simulate.
196 output_name: prefix for all output files.
197 [-q] : set it will stop outputting intermediate information.
201 output_name.fa if single-end without quality score;
202 output_name.fq if single-end with quality score;
203 output_name_1.fa & output_name_2.fa if paired-end without quality
205 output_name_1.fq & output_name_2.fq if paired-end with quality score.
207 output_name.sim.isoforms.results, output_name.sim.genes.results : Results estimated based on sample values.
209 ## <a name="acknowledgements"></a> Acknowledgements
211 RSEM uses the [Boost C++](http://www.boost.org) and
212 [samtools](http://samtools.sourceforge.net) libraries.
214 ## <a name="license"></a> License
216 RSEM is licensed under the [GNU General Public License v3](http://www.gnu.org/licenses/gpl-3.0.html).