rsem-calculate-expression - Estimate gene and isoform expression
from RNA-Seq data.
rsem-calculate-expression [options] upstream_read_file(s) reference_name sample_name
rsem-calculate-expression [options] --paired-end upstream_read_file(s) downstream_read_file(s) reference_name sample_name
rsem-calculate-expression [options] --alignments [--paired-end] input reference_name sample_name
- upstream_read_files(s)
- Comma-separated list of files containing single-end reads or upstream
reads for paired-end data. By default, these files are assumed to be in
FASTQ format. If the --no-qualities option is specified, then FASTA format
is expected.
- downstream_read_file(s)
- Comma-separated list of files containing downstream reads which are paired
with the upstream reads. By default, these files are assumed to be in
FASTQ format. If the --no-qualities option is specified, then FASTA format
is expected.
- input
- SAM/BAM/CRAM formatted input file. If "-" is specified for the
filename, the input is instead assumed to come from standard input. RSEM
requires all alignments of the same read group together. For paired-end
reads, RSEM also requires the two mates of any alignment be adjacent. In
addition, RSEM does not allow the SEQ and QUAL fields to be empty. See
Description section for how to make input file obey RSEM's
requirements.
- reference_name
- The name of the reference used. The user must have run
'rsem-prepare-reference' with this reference_name before running this
program.
- sample_name
- The name of the sample analyzed. All output files are prefixed by this
name (e.g., sample_name.genes.results)
- --paired-end
- Input reads are paired-end reads. (Default: off)
- --no-qualities
- Input reads do not contain quality scores. (Default: off)
- --strandedness
<none|forward|reverse>
- This option defines the strandedness of the RNA-Seq reads. It recognizes
three values: 'none', 'forward', and 'reverse'. 'none' refers to
non-strand-specific protocols. 'forward' means all (upstream) reads are
derived from the forward strand. 'reverse' means all (upstream) reads are
derived from the reverse strand. If 'forward'/'reverse' is set, the
'--norc'/'--nofw' Bowtie/Bowtie 2 option will also be enabled to avoid
aligning reads to the opposite strand. For Illumina TruSeq Stranded
protocols, please use 'reverse'. (Default: 'none')
- -p/--num-threads
<int>
- Number of threads to use. Both Bowtie/Bowtie2, expression estimation and
'samtools sort' will use this many threads. (Default: 1)
- --alignments
- Input file contains alignments in SAM/BAM/CRAM format. The exact file
format will be determined automatically. (Default: off)
- --fai
<file>
- If the header section of input alignment file does not contain reference
sequence information, this option should be turned on. <file> is a
FAI format file containing each reference sequence's name and length.
Please refer to the SAM official website for the details of FAI format.
(Default: off)
- --bowtie2
- Use Bowtie 2 instead of Bowtie to align reads. Since currently RSEM does
not handle indel, local and discordant alignments, the Bowtie2 parameters
are set in a way to avoid those alignments. In particular, we use options
'--sensitive --dpad 0 --gbar 99999999 --mp 1,1 --np 1 --score-min
L,0,-0.1' by default. The last parameter of '--score-min', '-0.1', is the
negative of maximum mismatch rate. This rate can be set by option
'--bowtie2-mismatch-rate'. If reads are paired-end, we additionally use
options '--no-mixed' and '--no-discordant'. (Default: off)
- --star
- Use STAR to align reads. Alignment parameters are from ENCODE3's STAR-RSEM
pipeline. To save computational time and memory resources, STAR's Output
BAM file is unsorted. It is stored in RSEM's temporary directory with name
as 'sample_name.bam'. Each STAR job will have its own private copy of the
genome in memory. (Default: off)
- --hisat2-hca
- Use HISAT2 to align reads to the transcriptome according to Human Cell
Atlast SMART-Seq2 pipeline. In particular, we use HISAT parameters
"-k 10 --secondary --rg-id=$sampleToken --rg SM:$sampleToken --rg
LB:$sampleToken --rg PL:ILLUMINA --rg PU:$sampleToken --new-summary
--summary-file $sampleName.log --met-file
$sampleName.hisat2.met.txt --met 5 --mp 1,1 --np 1
--score-min L,0,-0.1 --rdg 99999999,99999999 --rfg 99999999,99999999
--no-spliced-alignment --no-softclip --seed 12345". If inputs are
paired-end reads, we additionally use parameters "--no-mixed
--no-discordant". (Default: off)
- --append-names
- If gene_name/transcript_name is available, append it to the end of
gene_id/transcript_id (separated by '_') in files
'sample_name.isoforms.results' and 'sample_name.genes.results'. (Default:
off)
- --seed
<uint32>
- Set the seed for the random number generators used in calculating
posterior mean estimates and credibility intervals. The seed must be a
non-negative 32 bit integer. (Default: off)
- --single-cell-prior
- By default, RSEM uses Dirichlet(1) as the prior to calculate
posterior mean estimates and credibility intervals. However, much less
genes are expressed in single cell RNA-Seq data. Thus, if you want to
compute posterior mean estimates and/or credibility intervals and you have
single-cell RNA-Seq data, you are recommended to turn on this option. Then
RSEM will use Dirichlet(0.1) as the prior which encourage the sparsity of
the expression levels. (Default: off)
- --calc-pme
- Run RSEM's collapsed Gibbs sampler to calculate posterior mean estimates.
(Default: off)
- --calc-ci
- Calculate 95% credibility intervals and posterior mean estimates. The
credibility level can be changed by setting '--ci-credibility-level'.
(Default: off)
- -q/--quiet
- Suppress the output of logging information. (Default: off)
- -h/--help
- Show help information.
- --version
- Show version information.
- --sort-bam-by-read-name
- Sort BAM file aligned under transcript coordidate by read name. Setting
this option on will produce deterministic maximum likelihood estimations
from independent runs. Note that sorting will take long time and lots of
memory. (Default: off)
- --no-bam-output
- Do not output any BAM file. (Default: off)
- --sampling-for-bam
- When RSEM generates a BAM file, instead of outputting all alignments a
read has with their posterior probabilities, one alignment is sampled
according to the posterior probabilities. The sampling procedure includes
the alignment to the "noise" transcript, which does not appear
in the BAM file. Only the sampled alignment has a weight of 1. All other
alignments have weight 0. If the "noise" transcript is sampled,
all alignments appeared in the BAM file should have weight 0. (Default:
off)
- --output-genome-bam
- Generate a BAM file, 'sample_name.genome.bam', with alignments mapped to
genomic coordinates and annotated with their posterior probabilities. In
addition, RSEM will call samtools (included in RSEM package) to sort and
index the bam file. 'sample_name.genome.sorted.bam' and
'sample_name.genome.sorted.bam.bai' will be generated. (Default: off)
- --sort-bam-by-coordinate
- Sort RSEM generated transcript and genome BAM files by coordinates and
build associated indices. (Default: off)
- --sort-bam-memory-per-thread
<string>
- Set the maximum memory per thread that can be used by 'samtools sort'.
<string> represents the memory and accepts suffices 'K/M/G'. RSEM
will pass <string> to the '-m' option of 'samtools sort'. Note that
the default used here is different from the default used by samtools.
(Default: 1G)
- --seed-length
<int>
- Seed length used by the read aligner. Providing the correct value is
important for RSEM. If RSEM runs Bowtie, it uses this value for Bowtie's
seed length parameter. Any read with its or at least one of its mates'
(for paired-end reads) length less than this value will be ignored. If the
references are not added poly(A) tails, the minimum allowed value is 5,
otherwise, the minimum allowed value is 25. Note that this script will
only check if the value >= 5 and give a warning message if the value
< 25 but >= 5. (Default: 25)
- --phred33-quals
- Input quality scores are encoded as Phred+33. This option is used by
Bowtie, Bowtie 2 and HISAT2. (Default: on)
- --phred64-quals
- Input quality scores are encoded as Phred+64 (default for GA Pipeline ver.
>= 1.3). This option is used by Bowtie, Bowtie 2 and HISAT2. (Default:
off)
- --solexa-quals
- Input quality scores are solexa encoded (from GA Pipeline ver. < 1.3).
This option is used by Bowtie, Bowtie 2 and HISAT2. (Default: off)
- --bowtie-path
<path>
- The path to the Bowtie executables. (Default: the path to the Bowtie
executables is assumed to be in the user's PATH environment variable)
- --bowtie-n
<int>
- (Bowtie parameter) max # of mismatches in the seed. (Range: 0-3, Default:
2)
- --bowtie-e
<int>
- (Bowtie parameter) max sum of mismatch quality scores across the
alignment. (Default: 99999999)
- --bowtie-m
<int>
- (Bowtie parameter) suppress all alignments for a read if > <int>
valid alignments exist. (Default: 200)
- --bowtie-chunkmbs
<int>
- (Bowtie parameter) memory allocated for best first alignment calculation
(Default: 0 - use Bowtie's default)
- --bowtie2-path
<path>
- (Bowtie 2 parameter) The path to the Bowtie 2 executables. (Default: the
path to the Bowtie 2 executables is assumed to be in the user's PATH
environment variable)
- --bowtie2-mismatch-rate
<double>
- (Bowtie 2 parameter) The maximum mismatch rate allowed. (Default:
0.1)
- --bowtie2-k
<int>
- (Bowtie 2 parameter) Find up to <int> alignments per read. (Default:
200)
- --bowtie2-sensitivity-level
<string>
- (Bowtie 2 parameter) Set Bowtie 2's preset options in --end-to-end mode.
This option controls how hard Bowtie 2 tries to find alignments.
<string> must be one of "very_fast", "fast",
"sensitive" and "very_sensitive". The four candidates
correspond to Bowtie 2's "--very-fast", "--fast",
"--sensitive" and "--very-sensitive" options.
(Default: "sensitive" - use Bowtie 2's default)
- --star-path
<path>
- The path to STAR's executable. (Default: the path to STAR executable is
assumed to be in user's PATH environment variable)
- --star-gzipped-read-file
- (STAR parameter) Input read file(s) is compressed by gzip. (Default:
off)
- --star-bzipped-read-file
- (STAR parameter) Input read file(s) is compressed by bzip2. (Default:
off)
- --star-output-genome-bam
- (STAR parameter) Save the BAM file from STAR alignment under genomic
coordinate to 'sample_name.STAR.genome.bam'. This file is NOT sorted by
genomic coordinate. In this file, according to STAR's manual, 'paired ends
of an alignment are always adjacent, and multiple alignments of a read are
adjacent as well'. (Default: off)
- --hisat2-path
<path>
- The path to HISAT2's executable. (Default: the path to HISAT2 executable
is assumed to be in user's PATH environment variable)
- --tag
<string>
- The name of the optional field used in the SAM input for identifying a
read with too many valid alignments. The field should have the format
<tagName>:i:<value>, where a <value> bigger than 0
indicates a read with too many alignments. (Default: "")
- --fragment-length-min
<int>
- Minimum read/insert length allowed. This is also the value for the
Bowtie/Bowtie2 -I option. (Default: 1)
- --fragment-length-max
<int>
- Maximum read/insert length allowed. This is also the value for the
Bowtie/Bowtie 2 -X option. (Default: 1000)
- --fragment-length-mean
<double>
- (single-end data only) The mean of the fragment length distribution, which
is assumed to be a Gaussian. (Default: -1, which disables use of the
fragment length distribution)
- --fragment-length-sd
<double>
- (single-end data only) The standard deviation of the fragment length
distribution, which is assumed to be a Gaussian. (Default: 0, which
assumes that all fragments are of the same length, given by the rounded
value of --fragment-length-mean)
- --estimate-rspd
- Set this option if you want to estimate the read start position
distribution (RSPD) from data. Otherwise, RSEM will use a uniform RSPD.
(Default: off)
- --num-rspd-bins
<int>
- Number of bins in the RSPD. Only relevant when '--estimate-rspd' is
specified. Use of the default setting is recommended. (Default: 20)
- --gibbs-burnin
<int>
- The number of burn-in rounds for RSEM's Gibbs sampler. Each round passes
over the entire data set once. If RSEM can use multiple threads, multiple
Gibbs samplers will start at the same time and all samplers share the same
burn-in number. (Default: 200)
- --gibbs-number-of-samples
<int>
- The total number of count vectors RSEM will collect from its Gibbs
samplers. (Default: 1000)
- --gibbs-sampling-gap
<int>
- The number of rounds between two succinct count vectors RSEM collects. If
the count vector after round N is collected, the count vector after round
N + <int> will also be collected. (Default: 1)
- --ci-credibility-level
<double>
- The credibility level for credibility intervals. (Default: 0.95)
- --ci-memory
<int>
- Maximum size (in memory, MB) of the auxiliary buffer used for computing
credibility intervals (CI). (Default: 1024)
- --ci-number-of-samples-per-count-vector
<int>
- The number of read generating probability vectors sampled per sampled
count vector. The crebility intervals are calculated by first sampling P(C
| D) and then sampling P(Theta | C) for each sampled count vector. This
option controls how many Theta vectors are sampled per sampled count
vector. (Default: 50)
- --keep-intermediate-files
- Keep temporary files generated by RSEM. RSEM creates a temporary
directory, 'sample_name.temp', into which it puts all intermediate output
files. If this directory already exists, RSEM overwrites all files
generated by previous RSEM runs inside of it. By default, after RSEM
finishes, the temporary directory is deleted. Set this option to prevent
the deletion of this directory and the intermediate files inside of it.
(Default: off)
- --temporary-folder
<string>
- Set where to put the temporary files generated by RSEM. If the folder
specified does not exist, RSEM will try to create it. (Default:
sample_name.temp)
- --time
- Output time consumed by each step of RSEM to 'sample_name.time'. (Default:
off)
- --run-pRSEM
- Running prior-enhanced RSEM (pRSEM). Prior parameters, i.e. isoform's
initial pseudo-count for RSEM's Gibbs sampling, will be learned from input
RNA-seq data and an external data set. When pRSEM needs and only needs
ChIP-seq peak information to partition isoforms (e.g. in pRSEM's default
partition model), either ChIP-seq peak file (with the
'--chipseq-peak-file' option) or ChIP-seq FASTQ files for target and input
and the path for Bowtie executables are required (with the
'--chipseq-target-read-files <string>',
'--chipseq-control-read-files <string>', and '--bowtie-path
<path> options), otherwise, ChIP-seq FASTQ files for target and
control and the path to Bowtie executables are required. (Default:
off)
- --chipseq-peak-file
<string>
- Full path to a ChIP-seq peak file in ENCODE's narrowPeak, i.e. BED6+4,
format. This file is used when running prior-enhanced RSEM in the default
two-partition model. It partitions isoforms by whether they have ChIP-seq
overlapping with their transcription start site region or not. Each
partition will have its own prior parameter learned from a training set.
This file can be either gzipped or ungzipped. (Default: "")
- --chipseq-target-read-files
<string>
- Comma-separated full path of FASTQ read file(s) for ChIP-seq target. This
option is used when running prior-enhanced RSEM. It provides information
to calculate ChIP-seq peaks and signals. The file(s) can be either
ungzipped or gzipped with a suffix '.gz' or '.gzip'. The options
'--bowtie-path <path>' and '--chipseq-control-read-files
<string>' must be defined when this option is specified. (Default:
"")
- --chipseq-control-read-files
<string>
- Comma-separated full path of FASTQ read file(s) for ChIP-seq conrol. This
option is used when running prior-enhanced RSEM. It provides information
to call ChIP-seq peaks. The file(s) can be either ungzipped or gzipped
with a suffix '.gz' or '.gzip'. The options '--bowtie-path <path>'
and '--chipseq-target-read-files <string>' must be defined when this
option is specified. (Default: "")
- --chipseq-read-files-multi-targets
<string>
- Comma-separated full path of FASTQ read files for multiple ChIP-seq
targets. This option is used when running prior-enhanced RSEM, where prior
is learned from multiple complementary data sets. It provides information
to calculate ChIP-seq signals. All files can be either ungzipped or
gzipped with a suffix '.gz' or '.gzip'. When this option is specified, the
option '--bowtie-path <path>' must be defined and the option
'--partition-model <string>' will be set to 'cmb_lgt' automatically.
(Default: "")
- --chipseq-bed-files-multi-targets
<string>
- Comma-separated full path of BED files for multiple ChIP-seq targets. This
option is used when running prior-enhanced RSEM, where prior is learned
from multiple complementary data sets. It provides information of ChIP-seq
signals and must have at least the first six BED columns. All files can be
either ungzipped or gzipped with a suffix '.gz' or '.gzip'. When this
option is specified, the option '--partition-model <string>' will be
set to 'cmb_lgt' automatically. (Default: "")
- --cap-stacked-chipseq-reads
- Keep a maximum number of ChIP-seq reads that aligned to the same genomic
interval. This option is used when running prior-enhanced RSEM, where
prior is learned from multiple complementary data sets. This option is
only in use when either '--chipseq-read-files-multi-targets
<string>' or '--chipseq-bed-files-multi-targets <string>' is
specified. (Default: off)
- --n-max-stacked-chipseq-reads
<int>
- The maximum number of stacked ChIP-seq reads to keep. This option is used
when running prior-enhanced RSEM, where prior is learned from multiple
complementary data sets. This option is only in use when the option
'--cap-stacked-chipseq-reads' is set. (Default: 5)
- --partition-model
<string>
- A keyword to specify the partition model used by prior-enhanced RSEM. It
must be one of the following keywords:
- - pk
- Partitioned by whether an isoform has a ChIP-seq peak overlapping with its
transcription start site (TSS) region. The TSS region is defined as
[TSS-500bp, TSS+500bp]. For simplicity, we refer this type of peak as 'TSS
peak' when explaining other keywords.
- -
pk_lgtnopk
- First partitioned by TSS peak. Then, for isoforms in the 'no TSS peak'
set, a logistic model is employed to further classify them into two
partitions.
- - lm3, lm4,
lm5, or lm6
- Based on their ChIP-seq signals, isoforms are classified into 3, 4, 5, or
6 partitions by a linear regression model.
- -
nopk_lm2pk, nopk_lm3pk, nopk_lm4pk, or
nopk_lm5pk
- First partitioned by TSS peak. Then, for isoforms in the 'with TSS peak'
set, a linear regression model is employed to further classify them into
2, 3, 4, or 5 partitions.
- -
pk_lm2nopk, pk_lm3nopk, pk_lm4nopk, or
pk_lm5nopk
- First partitioned by TSS peak. Then, for isoforms in the 'no TSS peak'
set, a linear regression model is employed to further classify them into
2, 3, 4, or 5 partitions.
- -
cmb_lgt
- Using a logistic regression to combine TSS signals from multiple
complementary data sets and partition training set isoform into
'expressed' and 'not expressed'. This partition model is only in use when
either '--chipseq-read-files-multi-targets <string>' or
'--chipseq-bed-files-multi-targets <string> is specified.
Parameters for all the above models are learned from a training
set. For detailed explanations, please see prior-enhanced RSEM's paper.
(Default: 'pk')
The options in this section are deprecated. They are here
only for compatibility reasons and may be removed in future releases.
- --sam
- Inputs are alignments in SAM format. (Default: off)
- --bam
- Inputs are alignments in BAM format. (Default: off)
- --strand-specific
- Equivalent to '--strandedness forward'. (Default: off)
- --forward-prob
<double>
- Probability of generating a read from the forward strand of a transcript.
Set to 1 for a strand-specific protocol where all (upstream) reads are
derived from the forward strand, 0 for a strand-specific protocol where
all (upstream) read are derived from the reverse strand, or 0.5 for a
non-strand-specific protocol. (Default: off)
In its default mode, this program aligns input reads against a
reference transcriptome with Bowtie and calculates expression values using
the alignments. RSEM assumes the data are single-end reads with quality
scores, unless the '--paired-end' or '--no-qualities' options are specified.
Alternatively, users can use STAR to align reads using the '--star' option.
RSEM has provided options in 'rsem-prepare-reference' to prepare STAR's
genome indices. Users may use an alternative aligner by specifying
'--alignments', and providing an alignment file in SAM/BAM/CRAM format.
However, users should make sure that they align against the indices
generated by 'rsem-prepare-reference' and the alignment file satisfies the
requirements mentioned in ARGUMENTS section.
One simple way to make the alignment file satisfying RSEM's
requirements is to use the 'convert-sam-for-rsem' script. This script
accepts SAM/BAM/CRAM files as input and outputs a BAM file. For example,
type the following command to convert a SAM file, 'input.sam', to a
ready-for-use BAM file, 'input_for_rsem.bam':
convert-sam-for-rsem input.sam input_for_rsem
For details, please refer to 'convert-sam-for-rsem's documentation
page.
1. Users must run 'rsem-prepare-reference' with the appropriate
reference before using this program.
2. For single-end data, it is strongly recommended that the user
provide the fragment length distribution parameters (--fragment-length-mean
and --fragment-length-sd). For paired-end data, RSEM will automatically
learn a fragment length distribution from the data.
3. Some aligner parameters have default values different from
their original settings.
4. With the '--calc-pme' option, posterior mean estimates will be
calculated in addition to maximum likelihood estimates.
5. With the '--calc-ci' option, 95% credibility intervals and
posterior mean estimates will be calculated in addition to maximum
likelihood estimates.
6. The temporary directory and all intermediate files will be
removed when RSEM finishes unless '--keep-intermediate-files' is
specified.
With the '--run-pRSEM' option and associated options (see section
'PRIOR-ENHANCED RSEM OPTIONS' above for details), prior-enhanced RSEM will
be running. Prior parameters will be learned from supplied external data
set(s) and assigned as initial pseudo-counts for isoforms in the
corresponding partition for Gibbs sampling.
- sample_name.isoforms.results
- File containing isoform level expression estimates. The first line
contains column names separated by the tab character. The format of each
line in the rest of this file is:
transcript_id gene_id length effective_length expected_count
TPM FPKM IsoPct [posterior_mean_count
posterior_standard_deviation_of_count pme_TPM pme_FPKM
IsoPct_from_pme_TPM TPM_ci_lower_bound TPM_ci_upper_bound
TPM_coefficient_of_quartile_variation FPKM_ci_lower_bound
FPKM_ci_upper_bound FPKM_coefficient_of_quartile_variation]
Fields are separated by the tab character. Fields within
"[]" are optional. They will not be presented if neither
'--calc-pme' nor '--calc-ci' is set.
'transcript_id' is the transcript name of this transcript.
'gene_id' is the gene name of the gene which this transcript belongs to
(denote this gene as its parent gene). If no gene information is
provided, 'gene_id' and 'transcript_id' are the same.
'length' is this transcript's sequence length (poly(A) tail is
not counted). 'effective_length' counts only the positions that can
generate a valid fragment. If no poly(A) tail is added,
'effective_length' is equal to transcript length - mean fragment length
+ 1. If one transcript's effective length is less than 1, this
transcript's both effective length and abundance estimates are set to
0.
'expected_count' is the sum of the posterior probability of
each read comes from this transcript over all reads. Because 1) each
read aligning to this transcript has a probability of being generated
from background noise; 2) RSEM may filter some alignable low quality
reads, the sum of expected counts for all transcript are generally less
than the total number of reads aligned.
'TPM' stands for Transcripts Per Million. It is a relative
measure of transcript abundance. The sum of all transcripts' TPM is 1
million. 'FPKM' stands for Fragments Per Kilobase of transcript per
Million mapped reads. It is another relative measure of transcript
abundance. If we define l_bar be the mean transcript length in a sample,
which can be calculated as
l_bar = \sum_i TPM_i / 10^6 * effective_length_i (i goes
through every transcript),
the following equation is hold:
FPKM_i = 10^3 / l_bar * TPM_i.
We can see that the sum of FPKM is not a constant across
samples.
'IsoPct' stands for isoform percentage. It is the percentage
of this transcript's abandunce over its parent gene's abandunce. If its
parent gene has only one isoform or the gene information is not
provided, this field will be set to 100.
'posterior_mean_count', 'pme_TPM', 'pme_FPKM' are posterior
mean estimates calculated by RSEM's Gibbs sampler.
'posterior_standard_deviation_of_count' is the posterior standard
deviation of counts. 'IsoPct_from_pme_TPM' is the isoform percentage
calculated from 'pme_TPM' values.
'TPM_ci_lower_bound', 'TPM_ci_upper_bound',
'FPKM_ci_lower_bound' and 'FPKM_ci_upper_bound' are lower(l) and
upper(u) bounds of 95% credibility intervals for TPM and FPKM values.
The bounds are inclusive (i.e. [l, u]).
'TPM_coefficient_of_quartile_variation' and
'FPKM_coefficient_of_quartile_variation' are coefficients of quartile
variation (CQV) for TPM and FPKM values. CQV is a robust way of
measuring the ratio between the standard deviation and the mean. It is
defined as
CQV := (Q3 - Q1) / (Q3 + Q1),
where Q1 and Q3 are the first and third quartiles.
- sample_name.genes.results
- File containing gene level expression estimates. The first line contains
column names separated by the tab character. The format of each line in
the rest of this file is:
gene_id transcript_id(s) length effective_length
expected_count TPM FPKM [posterior_mean_count
posterior_standard_deviation_of_count pme_TPM pme_FPKM
TPM_ci_lower_bound TPM_ci_upper_bound
TPM_coefficient_of_quartile_variation FPKM_ci_lower_bound
FPKM_ci_upper_bound FPKM_coefficient_of_quartile_variation]
Fields are separated by the tab character. Fields within
"[]" are optional. They will not be presented if neither
'--calc-pme' nor '--calc-ci' is set.
'transcript_id(s)' is a comma-separated list of transcript_ids
belonging to this gene. If no gene information is provided, 'gene_id'
and 'transcript_id(s)' are identical (the 'transcript_id').
A gene's 'length' and 'effective_length' are defined as the
weighted average of its transcripts' lengths and effective lengths
(weighted by 'IsoPct'). A gene's abundance estimates are just the sum of
its transcripts' abundance estimates.
- sample_name.alleles.results
- Only generated when the RSEM references are built with allele-specific
transcripts.
This file contains allele level expression estimates for
allele-specific expression calculation. The first line contains column
names separated by the tab character. The format of each line in the
rest of this file is:
allele_id transcript_id gene_id length effective_length
expected_count TPM FPKM AlleleIsoPct AlleleGenePct [posterior_mean_count
posterior_standard_deviation_of_count pme_TPM pme_FPKM
AlleleIsoPct_from_pme_TPM AlleleGenePct_from_pme_TPM TPM_ci_lower_bound
TPM_ci_upper_bound TPM_coefficient_of_quartile_variation
FPKM_ci_lower_bound FPKM_ci_upper_bound
FPKM_coefficient_of_quartile_variation]
Fields are separated by the tab character. Fields within
"[]" are optional. They will not be presented if neither
'--calc-pme' nor '--calc-ci' is set.
'allele_id' is the allele-specific name of this
allele-specific transcript.
'AlleleIsoPct' stands for allele-specific percentage on
isoform level. It is the percentage of this allele-specific transcript's
abundance over its parent transcript's abundance. If its parent
transcript has only one allele variant form, this field will be set to
100.
'AlleleGenePct' stands for allele-specific percentage on gene
level. It is the percentage of this allele-specific transcript's
abundance over its parent gene's abundance.
'AlleleIsoPct_from_pme_TPM' and 'AlleleGenePct_from_pme_TPM'
have similar meanings. They are calculated based on posterior mean
estimates.
Please note that if this file is present, the fields 'length'
and 'effective_length' in 'sample_name.isoforms.results' should be
interpreted similarly as the corresponding definitions in
'sample_name.genes.results'.
- sample_name.transcript.bam
- Only generated when --no-bam-output is not specified.
'sample_name.transcript.bam' is a BAM-formatted file of read
alignments in transcript coordinates. The MAPQ field of each alignment
is set to min(100, floor(-10 * log10(1.0 - w) + 0.5)), where w is the
posterior probability of that alignment being the true mapping of a
read. In addition, RSEM pads a new tag ZW:f:value, where value is a
single precision floating number representing the posterior probability.
Because this file contains all alignment lines produced by bowtie or
user-specified aligners, it can also be used as a replacement of the
aligner generated BAM/SAM file.
- sample_name.transcript.sorted.bam
and sample_name.transcript.sorted.bam.bai
- Only generated when --no-bam-output is not specified and
--sort-bam-by-coordinate is specified.
'sample_name.transcript.sorted.bam' and
'sample_name.transcript.sorted.bam.bai' are the sorted BAM file and
indices generated by samtools (included in RSEM package).
- sample_name.genome.bam
- Only generated when --no-bam-output is not specified and
--output-genome-bam is specified.
'sample_name.genome.bam' is a BAM-formatted file of read
alignments in genomic coordinates. Alignments of reads that have
identical genomic coordinates (i.e., alignments to different isoforms
that share the same genomic region) are collapsed into one alignment.
The MAPQ field of each alignment is set to min(100, floor(-10 *
log10(1.0 - w) + 0.5)), where w is the posterior probability of that
alignment being the true mapping of a read. In addition, RSEM pads a new
tag ZW:f:value, where value is a single precision floating number
representing the posterior probability. If an alignment is spliced, a
XS:A:value tag is also added, where value is either '+' or '-'
indicating the strand of the transcript it aligns to.
- sample_name.genome.sorted.bam
and sample_name.genome.sorted.bam.bai
- Only generated when --no-bam-output is not specified, and
--sort-bam-by-coordinate and --output-genome-bam are specified.
'sample_name.genome.sorted.bam' and
'sample_name.genome.sorted.bam.bai' are the sorted BAM file and indices
generated by samtools (included in RSEM package).
- sample_name.time
- Only generated when --time is specified.
It contains time (in seconds) consumed by aligning reads,
estimating expression levels and calculating credibility intervals.
- sample_name.log
- Only generated when --alignments is not specified.
It captures alignment statistics outputted from the
user-specified aligner.
- sample_name.stat
- This is a folder instead of a file. All model related statistics are
stored in this folder. Use 'rsem-plot-model' can generate plots using this
folder.
'sample_name.stat/sample_name.cnt' contains alignment
statistics. The format and meanings of each field are described in
'cnt_file_description.txt' under RSEM directory.
'sample_name.stat/sample_name.model' stores RNA-Seq model
parameters learned from the data. The format and meanings of each filed
of this file are described in 'model_file_description.txt' under RSEM
directory.
The following four output files will be generated only by
prior-enhanced RSEM
- - 'sample_name.stat/sample_name_prsem.all_tr_features'
- It stores isofrom features for deriving and assigning pRSEM prior. The
first line is a header and the rest is one isoform per line. The
description for each column is:
- trid: transcript ID from input annotation
- geneid: gene ID from input anntation
- chrom: isoform's chromosome name
- strand: isoform's strand name
- start: isoform's end with the lowest genomic loci
- end: isoform's end with the highest genomic loci
- tss_mpp: average mappability of [TSS-500bp, TSS+500bp], where TSS
is isoform's transcription start site, i.e. 5'-end
- body_mpp: average mappability of (TSS+500bp, TES-500bp), where TES
is isoform's transcription end site, i.e. 3'-end
- tes_mpp: average mappability of [TES-500bp, TES+500bp]
- pme_count: isoform's fragment or read count from RSEM's posterior
mean estimates
- tss: isoform's TSS loci
- tss_pk: equal to 1 if isoform's [TSS-500bp, TSS+500bp] region
overlaps with a RNA Pol II peak; 0 otherwise
- is_training: equal to 1 if isoform is in the training set where Pol
II prior is learned; 0 otherwise
- - 'sample_name.stat/sample_name_prsem.all_tr_prior'
- It stores prior parameters for every isoform. This file does not have a
header. Each line contains a prior parameter and an isoform's transcript
ID delimited by ` # `.
- - 'sample_name.stat/sample_name_uniform_prior_1.isoforms.results'
- RSEM's posterior mean estimates on the isoform level with an initial
pseudo-count of one for every isoform. It is in the same format as the
'sample_name.isoforms.results'.
- - 'sample_name.stat/sample_name_uniform_prior_1.genes.results'
- RSEM's posterior mean estimates on the gene level with an initial
pseudo-count of one for every isoform. It is in the same format as the
'sample_name.genes.results'.
When learning prior from multiple external data sets in
prior-enhanced RSEM, two additional output files will be generated.
- - 'sample_name.stat/sample_name.pval_LL'
- It stores a p-value and a log-likelihood. The p-value indicates whether
the combination of multiple complementary data sets is informative for
RNA-seq quantification. The log-likelihood shows how well pRSEM's
Dirichlet-multinomial model fits the read counts of partitioned training
set isoforms.
- - 'sample_name.stat/sample_name.lgt_mdl.RData'
- It stores an R object named 'glmmdl', which is a logistic regression model
on the training set isoforms and multiple external data sets.
In addition, extra columns will be added to
'sample_name.stat/all_tr_features'
Assume the path to the bowtie executables is in the user's PATH
environment variable. Reference files are under '/ref' with name
'mouse_125'.
1) '/data/mmliver.fq', single-end reads with quality scores.
Quality scores are encoded as for 'GA pipeline version >= 1.3'. We want
to use 8 threads and generate a genome BAM file. In addition, we want to
append gene/transcript names to the result files:
rsem-calculate-expression --phred64-quals \
-p 8 \
--append-names \
--output-genome-bam \
/data/mmliver.fq \
/ref/mouse_125 \
mmliver_single_quals
2) '/data/mmliver_1.fq' and '/data/mmliver_2.fq', stranded
paired-end reads with quality scores. Suppose the library is prepared using
TruSeq Stranded Kit, which means the first mate should map to the reverse
strand. Quality scores are in SANGER format. We want to use 8 threads and do
not generate a genome BAM file:
rsem-calculate-expression -p 8 \
--paired-end \
--strandedness reverse \
/data/mmliver_1.fq \
/data/mmliver_2.fq \
/ref/mouse_125 \
mmliver_paired_end_quals
3) '/data/mmliver.fa', single-end reads without quality scores. We
want to use 8 threads:
rsem-calculate-expression -p 8 \
--no-qualities \
/data/mmliver.fa \
/ref/mouse_125 \
mmliver_single_without_quals
4) Data are the same as 1). This time we assume the bowtie
executables are under '/sw/bowtie'. We want to take a fragment length
distribution into consideration. We set the fragment length mean to 150 and
the standard deviation to 35. In addition to a BAM file, we also want to
generate credibility intervals. We allow RSEM to use 1GB of memory for CI
calculation:
rsem-calculate-expression --bowtie-path /sw/bowtie \
--phred64-quals \
--fragment-length-mean 150.0 \
--fragment-length-sd 35.0 \
-p 8 \
--output-genome-bam \
--calc-ci \
--ci-memory 1024 \
/data/mmliver.fq \
/ref/mouse_125 \
mmliver_single_quals
5) '/data/mmliver_paired_end_quals.bam', BAM-formatted alignments
for paired-end reads with quality scores. We want to use 8 threads:
rsem-calculate-expression --paired-end \
--alignments \
-p 8 \
/data/mmliver_paired_end_quals.bam \
/ref/mouse_125 \
mmliver_paired_end_quals
6) '/data/mmliver_1.fq.gz' and '/data/mmliver_2.fq.gz', paired-end
reads with quality scores and read files are compressed by gzip. We want to
use STAR to aligned reads and assume STAR executable is '/sw/STAR'. Suppose
we want to use 8 threads and do not generate a genome BAM file:
rsem-calculate-expression --paired-end \
--star \
--star-path /sw/STAR \
--gzipped-read-file \
--paired-end \
-p 8 \
/data/mmliver_1.fq.gz \
/data/mmliver_2.fq.gz \
/ref/mouse_125 \
mmliver_paired_end_quals
7) In the above example, suppose we want to run prior-enhanced
RSEM instead. Assuming we want to learn priors from a ChIP-seq peak file
'/data/mmlive.narrowPeak.gz':
rsem-calculate-expression --star \
--star-path /sw/STAR \
--gzipped-read-file \
--paired-end \
--calc-pme \
--run-pRSEM \
--chipseq-peak-file /data/mmliver.narrowPeak.gz \
-p 8 \
/data/mmliver_1.fq.gz \
/data/mmliver_2.fq.gz \
/ref/mouse_125 \
mmliver_paired_end_quals
8) Similar to the example in 7), suppose we want to use the
partition model 'pk_lm2nopk' (partitioning isoforms by Pol II TSS peak first
and then partitioning 'no TSS peak' isoforms into two bins by a linear
regression model), and we want to partition isoforms by RNA Pol II's
ChIP-seq read files '/data/mmliver_PolIIRep1.fq.gz' and
'/data/mmliver_PolIIRep2.fq.gz', and the control ChIP-seq read files
'/data/mmliver_ChIPseqCtrl.fq.gz'. Also, assuming Bowtie's executables are
under '/sw/bowtie/':
rsem-calculate-expression --star \
--star-path /sw/STAR \
--gzipped-read-file \
--paired-end \
--calc-pme \
--run-pRSEM \
--chipseq-target-read-files /data/mmliver_PolIIRep1.fq.gz,/data/mmliver_PolIIRep2.fq.gz \
--chipseq-control-read-files /data/mmliver_ChIPseqCtrl.fq.gz \
--partition-model pk_lm2nopk \
--bowtie-path /sw/bowtie \
-p 8 \
/data/mmliver_1.fq.gz \
/data/mmliver_2.fq.gz \
/ref/mouse_125 \
mmliver_paired_end_quals
9) Similar to the example in 8), suppose we want to derive prior
from four histone modification ChIP-seq read data sets:
'/data/H3K27Ac.fastq.gz', '/data/H3K4me1.fastq.gz',
'/data/H3K4me2.fastq.gz', and '/data/H3K4me3.fastq.gz'. Also, assuming
Bowtie's executables are under '/sw/bowtie/':
rsem-calculate-expression --star \
--star-path /sw/STAR \
--gzipped-read-file \
--paired-end \
--calc-pme \
--run-pRSEM \
--partition-model cmb_lgt \
--chipseq-read-files-multi-targets /data/H3K27Ac.fastq.gz,/data/H3K4me1.fastq.gz,/data/H3K4me2.fastq.gz,/data/H3K4me3.fastq.gz \
--bowtie-path /sw/bowtie \
-p 8 \
/data/mmliver_1.fq.gz \
/data/mmliver_2.fq.gz \
/ref/mouse_125 \
mmliver_paired_end_quals