C++, Perl and R 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.
+To take advantage of RSEM's built-in support for the Bowtie/Bowtie 2
+alignment program, you must have
+[Bowtie](http://bowtie-bio.sourceforge.net) and/or [Bowtie
+2](http://bowtie-bio.sourceforge.net/bowtie2) installed.
## <a name="usage"></a> Usage
#### Using an alternative aligner
By default, RSEM automates the alignment of reads to reference
-transcripts using the Bowtie alignment program. To use an alternative
+transcripts using the Bowtie alignment program. Turn on '--bowtie2'
+for 'rsem-prepare-reference' and 'rsem-calculate-expression' will
+allow RSEM to use the Bowtie 2 alignment program instead. Please note
+that indel alignments, local alignments and discordant alignments are
+disallowed when RSEM uses Bowtie 2 since RSEM currently cannot handle
+them. See the description of '--bowtie2' option in
+'rsem-calculate-expression' for more details. To use an alternative
alignment program, align the input reads against the file
'reference_name.idx.fa' generated by 'rsem-prepare-reference', and
format the alignment output in SAM or BAM format. Then, instead of
__estimated_model_file:__ This file describes how the RNA-Seq reads will be sequenced given the expression levels. It determines what kind of reads will be simulated (single-end/paired-end, w/o quality score) and includes parameters for fragment length distribution, read start position distribution, sequencing error models, etc. Normally, this file should be learned from real data using 'rsem-calculate-expression'. The file can be found under the 'sample_name.stat' folder with the name of 'sample_name.model'. 'model_file_description.txt' provides the format and meanings of this file.
-__estimated_isoform_results:__ This file contains expression levels for all isoforms recorded in the reference. It can be learned using 'rsem-calculate-expression' from real data. The corresponding file users want to use is 'sample_name.isoforms.results'. If simulating from user-designed expression profile is desired, start from a learned 'sample_name.isoforms.results' file and only modify the 'TPM' column. The simulator only reads the TPM column. But keeping the file format the same is required.
+__estimated_isoform_results:__ This file contains expression levels for all isoforms recorded in the reference. It can be learned using 'rsem-calculate-expression' from real data. The corresponding file users want to use is 'sample_name.isoforms.results'. If simulating from user-designed expression profile is desired, start from a learned 'sample_name.isoforms.results' file and only modify the 'TPM' column. The simulator only reads the TPM column. But keeping the file format the same is required. If the RSEM references built are aware of allele-specific transcripts, 'sample_name.alleles.results' should be used instead.
__theta0:__ This parameter determines the fraction of reads that are coming from background "noise" (instead of from a transcript). It can also be estimated using 'rsem-calculate-expression' from real data. Users can find it as the first value of the third line of the file 'sample_name.stat/sample_name.theta'.
__output_name:__ Prefix for all output files.
+__--seed seed:__ Set seed for the random number generator used in simulation. The seed should be a 32-bit unsigned integer.
+
__-q:__ Set it will stop outputting intermediate information.
### Outputs:
output_name.sim.isoforms.results, output_name.sim.genes.results: Expression levels estimated by counting where each simulated read comes from.
+output_name.sim.alleles.results: Allele-specific expression levels estimated by counting where each simulated read comes from.
output_name.fa if single-end without quality score;
output_name.fq if single-end with quality score;
## <a name="authors"></a> Authors
-RSEM is developed by Bo Li, with substaintial technical input from Colin Dewey.
+The RSEM algorithm is developed by Bo Li and Colin Dewey. The RSEM software is mainly implemented by Bo Li.
## <a name="acknowledgements"></a> Acknowledgements
[EBSeq](http://www.biostat.wisc.edu/~ningleng/EBSeq_Package/) for
differential expression analysis.
-We thank earonesty for contributing patches.
+We thank earonesty and Dr. Samuel Arvidsson for contributing patches.
-We thank Han Lin for suggesting possible fixes.
+We thank Han Lin, j.miller, Joël Fillon, Dr. Samuel G. Younkin and Malcolm Cook for suggesting possible fixes.
## <a name="license"></a> License
projects / rsem.git / blobdiff