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 <h2 id="introduction">Introduction</h2>
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 <h2 id="compilation">Compilation & Installation</h2>
34 To compile RSEM, simply run
38 To install, simply put the rsem directory in your environment's PATH
43 To take advantage of RSEM's built-in support for the Bowtie alignment
44 program, you must have [Bowtie](http://bowtie-bio.sourceforge.net) installed.
46 <h2 id="usage">Usage</h2>
48 ### I. Preparing Reference Sequences
50 RSEM can extract reference transcripts from a genome if you provide it
51 with gene annotations in a GTF file. Alternatively, you can provide
52 RSEM with transcript sequences directly.
54 Please note that GTF files generated from the UCSC Table Browser do not
55 contain isoform-gene relationship information. However, if you use the
56 UCSC Genes annotation track, this information can be recovered by
57 downloading the knownIsoforms.txt file for the appropriate genome.
59 To prepare the reference sequences, you should run the
60 'rsem-prepare-reference' program. Run
62 rsem-prepare-reference --help
64 to get usage information or visit the [rsem-prepare-reference
65 documentation page](rsem-prepare-reference.html).
67 ### II. Calculating Expression Values
69 To prepare the reference sequences, you should run the
70 'rsem-calculate-expression' program. Run
72 rsem-calculate-expression --help
74 to get usage information or visit the [rsem-calculate-expression
75 documentation page](rsem-calculate-expression.html).
77 Note: RSEM no longer provides nu values. Instead, RSEM provides
78 nrf(normalized read fraction), which is a normalized version of theta
79 vector excluding theta_0.
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 ### III. Visualization
105 RSEM contains a version of samtools in the 'sam' subdirectory. When
106 users specify the --out-bam option RSEM will produce three files:
107 'sample_name.bam', the unsorted BAM file, 'sample_name.sorted.bam' and
108 'sample_name.sorted.bam.bai' the sorted BAM file and indices generated
109 by the samtools included.
111 #### a) Generating a UCSC Wiggle file
113 A wiggle plot representing the expected number of reads overlapping
114 each position in the genome can be generated from the sorted BAM file
115 output. To generate the wiggle plot, run the 'rsem-bam2wig' program on
116 the 'sample_name.sorted.bam' file.
120 rsem-bam2wig bam_input wig_output wiggle_name
122 bam_input: sorted bam file
123 wig_output: output file name, e.g. output.wig
124 wiggle_name: the name the user wants to use for this wiggle plot
126 #### b) Loading a BAM and/or Wiggle file into the UCSC Genome Browser
128 Refer to the [UCSC custom track help page](http://genome.ucsc.edu/goldenPath/help/customTrack.html).
130 <h2 id="example">Example</h2>
132 Suppose we download the mouse genome from UCSC Genome Browser. We will
133 use a reference_name of 'mm9'. We have a FASTQ-formatted file,
134 'mmliver.fq', containing single-end reads from one sample, which we call
135 'mmliver_single_quals'. We want to estimate expression values by using
136 the single-end model with a fragment length distribution. We know that
137 the fragment length distribution is approximated by a normal
138 distribution with a mean of 150 and a standard deviation of 35. We wish
139 to generate 95% credibility intervals in addition to maximum likelihood
140 estimates. RSEM will be allowed 1G of memory for the credibility
141 interval calculation. We will visualize the probabilistic read mappings
144 The commands for this scenario are as follows:
146 rsem-prepare-reference --gtf mm9.gtf --mapping knownIsoforms.txt --bowtie-path /sw/bowtie /data/mm9 /ref/mm9
147 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
148 rsem-bam2wig mmliver_single_quals.sorted.bam mmliver_single_quals.sorted.wig mmliver_single_quals
150 <h2 id="simulation">Simulation</h2>
154 rsem-simulate-reads reference_name estimated_model_file estimated_isoform_results theta0 N output_name [-q]
156 estimated_model_file: File containing model parameters. Generated by
157 rsem-calculate-expression.
158 estimated_isoform_results: File containing isoform expression levels.
159 Generated by rsem-calculate-expression.
160 theta0: fraction of reads that are "noise" (not derived from a transcript).
161 N: number of reads to simulate.
162 output_name: prefix for all output files.
163 [-q] : set it will stop outputting intermediate information.
167 output_name.fa if single-end without quality score;
168 output_name.fq if single-end with quality score;
169 output_name_1.fa & output_name_2.fa if paired-end without quality
171 output_name_1.fq & output_name_2.fq if paired-end with quality score.
173 output_name.sim.isoforms.results, output_name.sim.genes.results : Results estimated based on sample values.
175 <h2 id="acknowledgements">Acknowledgements</h2>
177 RSEM uses randomc.h and mersenne.cpp from
178 <http://lxnt.info/rng/randomc.htm> for random number generation. RSEM
179 also uses the [Boost C++](http://www.boost.org) and
180 [samtools](http://samtools.sourceforge.net) libraries.
182 <h2 id="license">License</h2>
184 RSEM is licensed under the [GNU General Public License v3](http://www.gnu.org/licenses/gpl-3.0.html).