```bash
salmon quant -h
```
salmon v1.10.2
===============

salmon quant has two modes --- one quantifies expression using raw reads
and the other makes use of already-aligned reads (in BAM/SAM format).
Which algorithm is used depends on the arguments passed to salmon quant.
If you provide salmon with alignments '-a [ --alignments ]' then the
alignment-based algorithm will be used, otherwise the algorithm for
quantifying from raw reads will be used.

to view the help for salmon's selective-alignment-based mode, use the command

salmon quant --help-reads

To view the help for salmon's alignment-based mode, use the command

salmon quant --help-alignment


```bash
salmon quant --help-reads
```
Quant
==========
Perform dual-phase, selective-alignment-based estimation of
transcript abundance from RNA-seq reads

salmon quant options:


mapping input options:
  -l [ --libType ] arg                  Format string describing the library 
                                        type
  -i [ --index ] arg                    salmon index
  -r [ --unmatedReads ] arg             List of files containing unmated reads 
                                        of (e.g. single-end reads)
  -1 [ --mates1 ] arg                   File containing the #1 mates
  -2 [ --mates2 ] arg                   File containing the #2 mates


basic options:
  -v [ --version ]                      print version string
  -h [ --help ]                         produce help message
  -o [ --output ] arg                   Output quantification directory.
  --seqBias                             Perform sequence-specific bias 
                                        correction.
  --gcBias                              [beta for single-end reads] Perform 
                                        fragment GC bias correction.
  --posBias                             Perform positional bias correction.
  -p [ --threads ] arg (=16)            The number of threads to use 
                                        concurrently.
  --incompatPrior arg (=0)              This option sets the prior probability 
                                        that an alignment that disagrees with 
                                        the specified library type (--libType) 
                                        results from the true fragment origin. 
                                        Setting this to 0 specifies that 
                                        alignments that disagree with the 
                                        library type should be "impossible", 
                                        while setting it to 1 says that 
                                        alignments that disagree with the 
                                        library type are no less likely than 
                                        those that do
  -g [ --geneMap ] arg                  File containing a mapping of 
                                        transcripts to genes.  If this file is 
                                        provided salmon will output both 
                                        quant.sf and quant.genes.sf files, 
                                        where the latter contains aggregated 
                                        gene-level abundance estimates.  The 
                                        transcript to gene mapping should be 
                                        provided as either a GTF file, or a in 
                                        a simple tab-delimited format where 
                                        each line contains the name of a 
                                        transcript and the gene to which it 
                                        belongs separated by a tab.  The 
                                        extension of the file is used to 
                                        determine how the file should be 
                                        parsed.  Files ending in '.gtf', '.gff'
                                        or '.gff3' are assumed to be in GTF 
                                        format; files with any other extension 
                                        are assumed to be in the simple format.
                                        In GTF / GFF format, the 
                                        "transcript_id" is assumed to contain 
                                        the transcript identifier and the 
                                        "gene_id" is assumed to contain the 
                                        corresponding gene identifier.
  --auxTargetFile arg                   A file containing a list of "auxiliary"
                                        targets.  These are valid targets 
                                        (i.e., not decoys) to which fragments 
                                        are allowed to map and be assigned, and
                                        which will be quantified, but for which
                                        auxiliary models like sequence-specific
                                        and fragment-GC bias correction should 
                                        not be applied.
  --meta                                If you're using Salmon on a metagenomic
                                        dataset, consider setting this flag to 
                                        disable parts of the abundance 
                                        estimation model that make less sense 
                                        for metagenomic data.


options specific to mapping mode:
  --discardOrphansQuasi                 [selective-alignment mode only] : 
                                        Discard orphan mappings in 
                                        selective-alignment mode.  If this flag
                                        is passed then only paired mappings 
                                        will be considered toward 
                                        quantification estimates.  The default 
                                        behavior is to consider orphan mappings
                                        if no valid paired mappings exist.  
                                        This flag is independent of the option 
                                        to write the orphaned mappings to file 
                                        (--writeOrphanLinks).
  --validateMappings                    [*deprecated* (no effect; 
                                        selective-alignment is the default)]
  --consensusSlack arg (=0.349999994)   [selective-alignment mode only] : The 
                                        amount of slack allowed in the 
                                        selective-alignment filtering 
                                        mechanism.  If this is set to a 
                                        fraction, X, greater than 0 (and in 
                                        [0,1)), then uniMEM chains with scores 
                                        below (100 * X)% of the best chain 
                                        score for a read, and read pairs with a
                                        sum of chain scores below (100 * X)% of
                                        the best chain score for a read pair 
                                        will be discounted as a mapping 
                                        candidates.  The default value of this 
                                        option is 0.35.
  --preMergeChainSubThresh arg (=0.75)  [selective-alignment mode only] : The 
                                        threshold of sub-optimal chains, 
                                        compared to the best chain on a given 
                                        target, that will be retained and 
                                        passed to the next phase of mapping.  
                                        Specifically, if the best chain for a 
                                        read (or read-end in paired-end mode) 
                                        to target t has score X_t, then all 
                                        chains for this read with score >= X_t 
                                        * preMergeChainSubThresh will be 
                                        retained and passed to subsequent 
                                        mapping phases.  This value must be in 
                                        the range [0, 1].
  --postMergeChainSubThresh arg (=0.90000000000000002)
                                        [selective-alignment mode only] : The 
                                        threshold of sub-optimal chain pairs, 
                                        compared to the best chain pair on a 
                                        given target, that will be retained and
                                        passed to the next phase of mapping.  
                                        This is different than  
                                        preMergeChainSubThresh, because this is
                                        applied to pairs of chains (from the 
                                        ends of paired-end reads) after merging
                                        (i.e. after checking concordancy 
                                        constraints etc.).  Specifically, if 
                                        the best chain pair to target t has 
                                        score X_t, then all chain pairs for 
                                        this read pair with score >= X_t * 
                                        postMergeChainSubThresh will be 
                                        retained and passed to subsequent 
                                        mapping phases.  This value must be in 
                                        the range [0, 1]. Note: This option is 
                                        only meaningful for paired-end 
                                        libraries, and is ignored for 
                                        single-end libraries.
  --orphanChainSubThresh arg (=0.94999999999999996)
                                        [selective-alignment mode only] : This 
                                        threshold sets a global sub-optimality 
                                        threshold for chains corresponding to 
                                        orphan mappings.  That is, if the 
                                        merging procedure results in no 
                                        concordant mappings then only orphan 
                                        mappings with a chain score >= 
                                        orphanChainSubThresh * bestChainScore 
                                        will be retained and passed to 
                                        subsequent mapping phases.  This value 
                                        must be in the range [0, 1]. Note: This
                                        option is only meaningful for 
                                        paired-end libraries, and is ignored 
                                        for single-end libraries.
  --scoreExp arg (=1)                   [selective-alignment mode only] : The 
                                        factor by which sub-optimal alignment 
                                        scores are downweighted to produce a 
                                        probability.  If the best alignment 
                                        score for the current read is S, and 
                                        the score for a particular alignment is
                                        w, then the probability will be 
                                        computed porportional to exp( - 
                                        scoreExp * (S-w) ).
  --minScoreFraction arg                [selective-alignment mode only] : The 
                                        fraction of the optimal possible 
                                        alignment score that a mapping must 
                                        achieve in order to be considered 
                                        "valid" --- should be in (0,1].
                                        Salmon Default 0.65 and Alevin Default 
                                        0.87
  --mismatchSeedSkip arg (=3)           [selective-alignment mode only] : After
                                        a k-mer hit is extended to a uni-MEM, 
                                        the uni-MEM extension can terminate for
                                        one of 3 reasons; the end of the read, 
                                        the end of the unitig, or a mismatch.  
                                        If the extension ends because of a 
                                        mismatch, this is likely the result of 
                                        a sequencing error.  To avoid looking 
                                        up many k-mers that will likely fail to
                                        be located in the index, the search 
                                        procedure skips by a factor of 
                                        mismatchSeedSkip until it either (1) 
                                        finds another match or (2) is k-bases 
                                        past the mismatch position. This value 
                                        controls that skip length.  A smaller 
                                        value can increase sensitivity, while a
                                        larger value can speed up seeding.
  --disableChainingHeuristic            [selective-alignment mode only] : By 
                                        default, the heuristic of (Li 2018) is 
                                        implemented, which terminates the 
                                        chaining DP once a given number of 
                                        valid backpointers are found.  This 
                                        speeds up the seed (MEM) chaining step,
                                        but may result in sub-optimal chains in
                                        complex situations (e.g. sequences with
                                        many repeats and overlapping repeats). 
                                        Passing this flag will disable the 
                                        chaining heuristic, and perform the 
                                        full chaining dynamic program, 
                                        guaranteeing the optimal chain is found
                                        in this step.
  --decoyThreshold arg (=1)             [selective-alignment mode only] : For 
                                        an alignemnt to an annotated transcript
                                        to be considered invalid, it must have 
                                        an alignment score < (decoyThreshold * 
                                        bestDecoyScore).  A value of 1.0 means 
                                        that any alignment strictly worse than 
                                        the best decoy alignment will be 
                                        discarded.  A smaller value will allow 
                                        reads to be allocated to transcripts 
                                        even if they strictly align better to 
                                        the decoy sequence.
  --ma arg (=2)                         [selective-alignment mode only] : The 
                                        value given to a match between read and
                                        reference nucleotides in an alignment.
  --mp arg (=-4)                        [selective-alignment mode only] : The 
                                        value given to a mis-match between read
                                        and reference nucleotides in an 
                                        alignment.
  --go arg (=6)                         [selective-alignment mode only] : The 
                                        value given to a gap opening in an 
                                        alignment.
  --ge arg (=2)                         [selective-alignment mode only] : The 
                                        value given to a gap extension in an 
                                        alignment.
  --bandwidth arg (=15)                 [selective-alignment mode only] : The 
                                        value used for the bandwidth passed to 
                                        ksw2.  A smaller bandwidth can make the
                                        alignment verification run more 
                                        quickly, but could possibly miss valid 
                                        alignments.
  --allowDovetail                       [selective-alignment mode only] : allow
                                        dovetailing mappings.
  --recoverOrphans                      [selective-alignment mode only] : 
                                        Attempt to recover the mates of 
                                        orphaned reads. This uses edlib for 
                                        orphan recovery, and so introduces some
                                        computational overhead, but it can 
                                        improve sensitivity.
  --mimicBT2                            [selective-alignment mode only] : Set 
                                        flags to mimic parameters similar to 
                                        Bowtie2 with --no-discordant and 
                                        --no-mixed flags.  This increases 
                                        disallows dovetailing reads, and 
                                        discards orphans. Note, this does not 
                                        impose the very strict parameters 
                                        assumed by RSEM+Bowtie2, like gapless 
                                        alignments.  For that behavior, use the
                                        --mimiStrictBT2 flag below.
  --mimicStrictBT2                      [selective-alignment mode only] : Set 
                                        flags to mimic the very strict 
                                        parameters used by RSEM+Bowtie2.  This 
                                        increases --minScoreFraction to 0.8, 
                                        disallows dovetailing reads, discards 
                                        orphans, and disallows gaps in 
                                        alignments.
  --softclip                            [selective-alignment mode only 
                                        (experimental)] : Allos soft-clipping 
                                        of reads during selective-alignment. If
                                        this option is provided, then regions 
                                        at the beginning or end of the read can
                                        be withheld from alignment without any 
                                        effect on the resulting score (i.e. 
                                        neither adding nor removing from the 
                                        score).  This will drastically reduce 
                                        the penalty if there are mismatches at 
                                        the beginning or end of the read due to
                                        e.g. low-quality bases or adapters.  
                                        NOTE: Even with soft-clipping enabled, 
                                        the read must still achieve a score of 
                                        at least minScoreFraction * maximum 
                                        achievable score, where the maximum 
                                        achievable score is computed based on 
                                        the full (un-clipped) read length.
  --softclipOverhangs                   [selective-alignment mode only] : Allow
                                        soft-clipping of reads that overhang 
                                        the beginning or ends of the 
                                        transcript.  In this case, the 
                                        overhaning section of the read will 
                                        simply be unaligned, and will not 
                                        contribute or detract from the 
                                        alignment score.  The default policy is
                                        to force an end-to-end alignment of the
                                        entire read, so that overhanings will 
                                        result in some deletion of nucleotides 
                                        from the read.
  --fullLengthAlignment                 [selective-alignment mode only] : 
                                        Perform selective alignment over the 
                                        full length of the read, beginning from
                                        the (approximate) initial mapping 
                                        location and using extension alignment.
                                          This is in contrast with the default 
                                        behavior which is to only perform 
                                        alignment between the MEMs in the 
                                        optimal chain (and before the first and
                                        after the last MEM if applicable).  The
                                        default strategy forces the MEMs to 
                                        belong to the alignment, but has the 
                                        benefit that it can discover indels 
                                        prior to the first hit shared between 
                                        the read and reference. Except in very 
                                        rare circumstances, the default mode 
                                        should be more accurate.
  --hardFilter                          [selective-alignemnt mode only] : 
                                        Instead of weighting mappings by their 
                                        alignment score, this flag will discard
                                        any mappings with sub-optimal alignment
                                        score.  The default option of 
                                        soft-filtering (i.e. weighting mappings
                                        by their alignment score) usually 
                                        yields slightly more accurate abundance
                                        estimates but this flag may be 
                                        desirable if you want more accurate 
                                        'naive' equivalence classes, rather 
                                        than range factorized equivalence 
                                        classes.
  --minAlnProb arg (=1.0000000000000001e-05)
                                        [selective-alignment mode only] : Any 
                                        mapping whose alignment probability (as
                                        computed by P(aln) = exp(-scoreExp * 
                                        difference from best mapping score) is 
                                        less than minAlnProb will not be 
                                        considered as a valid alignment for 
                                        this read.  The goal of this flag is to
                                        remove very low probability alignments 
                                        that are unlikely to have any 
                                        non-trivial effect on the final 
                                        quantifications.  Filtering such 
                                        alignments reduces the number of 
                                        variables that need to be considered 
                                        and can result in slightly faster 
                                        inference and 'cleaner' equivalence 
                                        classes.
  -z [ --writeMappings ] [=arg(=-)]     If this option is provided, then the 
                                        selective-alignment results will be 
                                        written out in SAM-compatible format.  
                                        By default, output will be directed to 
                                        stdout, but an alternative file name 
                                        can be provided instead.
  --writeQualities                      This flag only has meaning if mappings 
                                        are being written (with 
                                        --writeMappings/-z). If this flag is 
                                        provided, then the output SAM file will
                                        contain quality strings as well as read
                                        sequences. Note that this can greatly 
                                        increase the size of the output file.
  --hitFilterPolicy arg (=AFTER)        [selective-alignment mode only] : 
                                        Determines the policy by which hits are
                                        filtered in selective alignment.  
                                        Filtering hits after chaining (the 
                                        default) is more sensitive, but more 
                                        computationally intensive, because it 
                                        performs the chaining dynamic program 
                                        for all hits.  Filtering before 
                                        chaining is faster, but some true hits 
                                        may be missed.  The options are BEFORE,
                                        AFTER, BOTH and NONE.


advanced options:
  --alternativeInitMode                 [Experimental]: Use an alternative 
                                        strategy (rather than simple 
                                        interpolation between) the online and 
                                        uniform abundance estimates to 
                                        initialize the EM / VBEM algorithm.
  --auxDir arg (=aux_info)              The sub-directory of the quantification
                                        directory where auxiliary information 
                                        e.g. bootstraps, bias parameters, etc. 
                                        will be written.
  --skipQuant                           Skip performing the actual transcript 
                                        quantification (including any Gibbs 
                                        sampling or bootstrapping).
  --dumpEq                              Dump the simple equivalence class 
                                        counts that were computed during 
                                        mapping or alignment.
  -d [ --dumpEqWeights ]                Dump conditional probabilities 
                                        associated with transcripts when 
                                        equivalence class information is being 
                                        dumped to file. Note, this will dump 
                                        the factorization that is actually used
                                        by salmon's offline phase for 
                                        inference.  If you are using 
                                        range-factorized equivalence classes 
                                        (the default) then the same transcript 
                                        set may appear multiple times with 
                                        different associated conditional 
                                        probabilities.
  --minAssignedFrags arg (=10)          The minimum number of fragments that 
                                        must be assigned to the transcriptome 
                                        for quantification to proceed.
  --reduceGCMemory                      If this option is selected, a more 
                                        memory efficient (but slightly slower) 
                                        representation is used to compute 
                                        fragment GC content. Enabling this will
                                        reduce memory usage, but can also 
                                        reduce speed.  However, the results 
                                        themselves will remain the same.
  --biasSpeedSamp arg (=5)              The value at which the fragment length 
                                        PMF is down-sampled when evaluating 
                                        sequence-specific & GC fragment bias.  
                                        Larger values speed up effective length
                                        correction, but may decrease the 
                                        fidelity of bias modeling results.
  --fldMax arg (=1000)                  The maximum fragment length to consider
                                        when building the empirical 
                                        distribution
  --fldMean arg (=250)                  The mean used in the fragment length 
                                        distribution prior
  --fldSD arg (=25)                     The standard deviation used in the 
                                        fragment length distribution prior
  -f [ --forgettingFactor ] arg (=0.65000000000000002)
                                        The forgetting factor used in the 
                                        online learning schedule.  A smaller 
                                        value results in quicker learning, but 
                                        higher variance and may be unstable.  A
                                        larger value results in slower learning
                                        but may be more stable.  Value should 
                                        be in the interval (0.5, 1.0].
  --initUniform                         initialize the offline inference with 
                                        uniform parameters, rather than seeding
                                        with online parameters.
  --maxOccsPerHit arg (=1000)           When collecting "hits" (MEMs), hits 
                                        having more than maxOccsPerHit 
                                        occurrences won't be considered.
  -w [ --maxReadOcc ] arg (=200)        Reads "mapping" to more than this many 
                                        places won't be considered.
  --maxRecoverReadOcc arg (=2500)       Relevant for alevin with '--sketch' 
                                        mode only: if a read has valid seed 
                                        matches, but no read has matches 
                                        leading to fewer than "maxReadOcc" 
                                        mappings, then try to recover mappings 
                                        for this read as long as there are 
                                        fewer than "maxRecoverReadOcc" 
                                        mappings.
  --noLengthCorrection                  [experimental] : Entirely disables 
                                        length correction when estimating the 
                                        abundance of transcripts.  This option 
                                        can be used with protocols where one 
                                        expects that fragments derive from 
                                        their underlying targets without regard
                                        to that target's length (e.g. QuantSeq)
  --noEffectiveLengthCorrection         Disables effective length correction 
                                        when computing the probability that a 
                                        fragment was generated from a 
                                        transcript.  If this flag is passed in,
                                        the fragment length distribution is not
                                        taken into account when computing this 
                                        probability.
  --noSingleFragProb                    Disables the estimation of an 
                                        associated fragment length probability 
                                        for single-end reads or for orphaned 
                                        mappings in paired-end libraries.  The 
                                        default behavior is to consider the 
                                        probability of all possible fragment 
                                        lengths associated with the retained 
                                        mapping.  Enabling this flag (i.e. 
                                        turning this default behavior off) will
                                        simply not attempt to estimate a 
                                        fragment length probability in such 
                                        cases.
  --noFragLengthDist                    [experimental] : Don't consider 
                                        concordance with the learned fragment 
                                        length distribution when trying to 
                                        determine the probability that a 
                                        fragment has originated from a 
                                        specified location.  Normally, 
                                        Fragments with unlikely lengths will be
                                        assigned a smaller relative probability
                                        than those with more likely lengths.  
                                        When this flag is passed in, the 
                                        observed fragment length has no effect 
                                        on that fragment's a priori 
                                        probability.
  --noBiasLengthThreshold               [experimental] : If this option is 
                                        enabled, then no (lower) threshold will
                                        be set on how short bias correction can
                                        make effective lengths. This can 
                                        increase the precision of bias 
                                        correction, but harm robustness.  The 
                                        default correction applies a threshold.
  --numBiasSamples arg (=2000000)       Number of fragment mappings to use when
                                        learning the sequence-specific bias 
                                        model.
  --numAuxModelSamples arg (=5000000)   The first <numAuxModelSamples> are used
                                        to train the auxiliary model parameters
                                        (e.g. fragment length distribution, 
                                        bias, etc.).  After ther first 
                                        <numAuxModelSamples> observations the 
                                        auxiliary model parameters will be 
                                        assumed to have converged and will be 
                                        fixed.
  --numPreAuxModelSamples arg (=5000)   The first <numPreAuxModelSamples> will 
                                        have their assignment likelihoods and 
                                        contributions to the transcript 
                                        abundances computed without applying 
                                        any auxiliary models.  The purpose of 
                                        ignoring the auxiliary models for the 
                                        first <numPreAuxModelSamples> 
                                        observations is to avoid applying these
                                        models before their parameters have 
                                        been learned sufficiently well.
  --useEM                               Use the traditional EM algorithm for 
                                        optimization in the batch passes.
  --useVBOpt                            Use the Variational Bayesian EM 
                                        [default]
  --rangeFactorizationBins arg (=4)     Factorizes the likelihood used in 
                                        quantification by adopting a new notion
                                        of equivalence classes based on the 
                                        conditional probabilities with which 
                                        fragments are generated from different 
                                        transcripts.  This is a more 
                                        fine-grained factorization than the 
                                        normal rich equivalence classes.  The 
                                        default value (4) corresponds to the 
                                        default used in Zakeri et al. 2017 
                                        (doi: 10.1093/bioinformatics/btx262), 
                                        and larger values imply a more 
                                        fine-grained factorization.  If range 
                                        factorization is enabled, a common 
                                        value to select for this parameter is 
                                        4. A value of 0 signifies the use of 
                                        basic rich equivalence classes.
  --numGibbsSamples arg (=0)            Number of Gibbs sampling rounds to 
                                        perform.
  --noGammaDraw                         This switch will disable drawing 
                                        transcript fractions from a Gamma 
                                        distribution during Gibbs sampling.  In
                                        this case the sampler does not account 
                                        for shot-noise, but only assignment 
                                        ambiguity
  --numBootstraps arg (=0)              Number of bootstrap samples to 
                                        generate. Note: This is mutually 
                                        exclusive with Gibbs sampling.
  --bootstrapReproject                  This switch will learn the parameter 
                                        distribution from the bootstrapped 
                                        counts for each sample, but will 
                                        reproject those parameters onto the 
                                        original equivalence class counts.
  --thinningFactor arg (=16)            Number of steps to discard for every 
                                        sample kept from the Gibbs chain. The 
                                        larger this number, the less chance 
                                        that subsequent samples are 
                                        auto-correlated, but the slower 
                                        sampling becomes.
  -q [ --quiet ]                        Be quiet while doing quantification 
                                        (don't write informative output to the 
                                        console unless something goes wrong).
  --perTranscriptPrior                  The prior (either the default or the 
                                        argument provided via --vbPrior) will 
                                        be interpreted as a transcript-level 
                                        prior (i.e. each transcript will be 
                                        given a prior read count of this value)
  --perNucleotidePrior                  The prior (either the default or the 
                                        argument provided via --vbPrior) will 
                                        be interpreted as a nucleotide-level 
                                        prior (i.e. each nucleotide will be 
                                        given a prior read count of this value)
  --sigDigits arg (=3)                  The number of significant digits to 
                                        write when outputting the 
                                        EffectiveLength and NumReads columns
  --vbPrior arg (=0.01)                 The prior that will be used in the VBEM
                                        algorithm.  This is interpreted as a 
                                        per-transcript prior, unless the 
                                        --perNucleotidePrior flag is also 
                                        given.  If the --perNucleotidePrior 
                                        flag is given, this is used as a 
                                        nucleotide-level prior.  If the default
                                        is used, it will be divided by 1000 
                                        before being used as a nucleotide-level
                                        prior, i.e. the default per-nucleotide 
                                        prior will be 1e-5.
  --writeOrphanLinks                    Write the transcripts that are linked 
                                        by orphaned reads.
  --writeUnmappedNames                  Write the names of un-mapped reads to 
                                        the file unmapped_names.txt in the 
                                        auxiliary directory.


```bash
salmon quant --help-alignment
```
Quant
==========
Perform dual-phase, alignment-based estimation of
transcript abundance from RNA-seq reads

salmon quant options:


alignment input options:
  --discardOrphans                      [alignment-based mode only] : Discard 
                                        orphan alignments in the input .  If 
                                        this flag is passed, then only paired 
                                        alignments will be considered toward 
                                        quantification estimates.  The default 
                                        behavior is to consider orphan 
                                        alignments if no valid paired mappings 
                                        exist.
  -l [ --libType ] arg                  Format string describing the library 
                                        type
  -a [ --alignments ] arg               input alignment (BAM) file(s).
  -e [ --eqclasses ] arg                input salmon weighted equivalence class
                                        file.
  -t [ --targets ] arg                  FASTA format file containing target 
                                        transcripts.
  --ont                                 use alignment model for Oxford Nanopore
                                        long reads


basic options:
  -v [ --version ]                      print version string
  -h [ --help ]                         produce help message
  -o [ --output ] arg                   Output quantification directory.
  --seqBias                             Perform sequence-specific bias 
                                        correction.
  --gcBias                              [beta for single-end reads] Perform 
                                        fragment GC bias correction.
  --posBias                             Perform positional bias correction.
  -p [ --threads ] arg (=8)             The number of threads to use 
                                        concurrently.
  --incompatPrior arg (=0)              This option sets the prior probability 
                                        that an alignment that disagrees with 
                                        the specified library type (--libType) 
                                        results from the true fragment origin. 
                                        Setting this to 0 specifies that 
                                        alignments that disagree with the 
                                        library type should be "impossible", 
                                        while setting it to 1 says that 
                                        alignments that disagree with the 
                                        library type are no less likely than 
                                        those that do
  -g [ --geneMap ] arg                  File containing a mapping of 
                                        transcripts to genes.  If this file is 
                                        provided salmon will output both 
                                        quant.sf and quant.genes.sf files, 
                                        where the latter contains aggregated 
                                        gene-level abundance estimates.  The 
                                        transcript to gene mapping should be 
                                        provided as either a GTF file, or a in 
                                        a simple tab-delimited format where 
                                        each line contains the name of a 
                                        transcript and the gene to which it 
                                        belongs separated by a tab.  The 
                                        extension of the file is used to 
                                        determine how the file should be 
                                        parsed.  Files ending in '.gtf', '.gff'
                                        or '.gff3' are assumed to be in GTF 
                                        format; files with any other extension 
                                        are assumed to be in the simple format.
                                        In GTF / GFF format, the 
                                        "transcript_id" is assumed to contain 
                                        the transcript identifier and the 
                                        "gene_id" is assumed to contain the 
                                        corresponding gene identifier.
  --auxTargetFile arg                   A file containing a list of "auxiliary"
                                        targets.  These are valid targets 
                                        (i.e., not decoys) to which fragments 
                                        are allowed to map and be assigned, and
                                        which will be quantified, but for which
                                        auxiliary models like sequence-specific
                                        and fragment-GC bias correction should 
                                        not be applied.
  --meta                                If you're using Salmon on a metagenomic
                                        dataset, consider setting this flag to 
                                        disable parts of the abundance 
                                        estimation model that make less sense 
                                        for metagenomic data.


alignment-specific options:
  --noErrorModel                        Turn off the alignment error model, 
                                        which takes into account the the 
                                        observed frequency of different types 
                                        of mismatches / indels when computing 
                                        the likelihood of a given alignment. 
                                        Turning this off can speed up 
                                        alignment-based salmon, but can harm 
                                        quantification accuracy.
  --numErrorBins arg (=6)               The number of bins into which to divide
                                        each read when learning and applying 
                                        the error model.  For example, a value 
                                        of 10 would mean that effectively, a 
                                        separate error model is leared and 
                                        applied to each 10th of the read, while
                                        a value of 3 would mean that a separate
                                        error model is applied to the read 
                                        beginning (first third), middle (second
                                        third) and end (final third).
  -s [ --sampleOut ]                    Write a "postSample.bam" file in the 
                                        output directory that will sample the 
                                        input alignments according to the 
                                        estimated transcript abundances. If 
                                        you're going to perform downstream 
                                        analysis of the alignments with tools 
                                        which don't, themselves, take fragment 
                                        assignment ambiguity into account, you 
                                        should use this output.
  -u [ --sampleUnaligned ]              In addition to sampling the aligned 
                                        reads, also write the un-aligned reads 
                                        to "postSample.bam".
  --gencode                             This flag will expect the input 
                                        transcript fasta to be in GENCODE 
                                        format, and will split the transcript 
                                        name at the first '|' character.  These
                                        reduced names will be used in the 
                                        output and when looking for these 
                                        transcripts in a gene to transcript 
                                        GTF.
  --scoreExp arg (=1)                   The factor by which sub-optimal 
                                        alignment scores are downweighted to 
                                        produce a probability.  If the best 
                                        alignment score for the current read is
                                        S, and the score for a particular 
                                        alignment is w, then the probability 
                                        will be computed porportional to exp( -
                                        scoreExp * (S-w) ). NOTE: This flag 
                                        only has an effect if you are parsing 
                                        alignments produced by salmon itself 
                                        (i.e. pufferfish or RapMap in 
                                        selective-alignment mode).
  --mappingCacheMemoryLimit arg (=2000000)
                                        If the file contained fewer than this 
                                        many mapped reads, then just keep the 
                                        data in memory for subsequent rounds of
                                        inference. Obviously, this value should
                                        not be too large if you wish to keep a 
                                        low memory usage, but setting it large 
                                        enough to accommodate all of the mapped
                                        read can substantially speed up 
                                        inference on "small" files that contain
                                        only a few million reads.


advanced options:
  --alternativeInitMode                 [Experimental]: Use an alternative 
                                        strategy (rather than simple 
                                        interpolation between) the online and 
                                        uniform abundance estimates to 
                                        initialize the EM / VBEM algorithm.
  --auxDir arg (=aux_info)              The sub-directory of the quantification
                                        directory where auxiliary information 
                                        e.g. bootstraps, bias parameters, etc. 
                                        will be written.
  --skipQuant                           Skip performing the actual transcript 
                                        quantification (including any Gibbs 
                                        sampling or bootstrapping).
  --dumpEq                              Dump the simple equivalence class 
                                        counts that were computed during 
                                        mapping or alignment.
  -d [ --dumpEqWeights ]                Dump conditional probabilities 
                                        associated with transcripts when 
                                        equivalence class information is being 
                                        dumped to file. Note, this will dump 
                                        the factorization that is actually used
                                        by salmon's offline phase for 
                                        inference.  If you are using 
                                        range-factorized equivalence classes 
                                        (the default) then the same transcript 
                                        set may appear multiple times with 
                                        different associated conditional 
                                        probabilities.
  --minAssignedFrags arg (=10)          The minimum number of fragments that 
                                        must be assigned to the transcriptome 
                                        for quantification to proceed.
  --reduceGCMemory                      If this option is selected, a more 
                                        memory efficient (but slightly slower) 
                                        representation is used to compute 
                                        fragment GC content. Enabling this will
                                        reduce memory usage, but can also 
                                        reduce speed.  However, the results 
                                        themselves will remain the same.
  --biasSpeedSamp arg (=5)              The value at which the fragment length 
                                        PMF is down-sampled when evaluating 
                                        sequence-specific & GC fragment bias.  
                                        Larger values speed up effective length
                                        correction, but may decrease the 
                                        fidelity of bias modeling results.
  --fldMax arg (=1000)                  The maximum fragment length to consider
                                        when building the empirical 
                                        distribution
  --fldMean arg (=250)                  The mean used in the fragment length 
                                        distribution prior
  --fldSD arg (=25)                     The standard deviation used in the 
                                        fragment length distribution prior
  -f [ --forgettingFactor ] arg (=0.65000000000000002)
                                        The forgetting factor used in the 
                                        online learning schedule.  A smaller 
                                        value results in quicker learning, but 
                                        higher variance and may be unstable.  A
                                        larger value results in slower learning
                                        but may be more stable.  Value should 
                                        be in the interval (0.5, 1.0].
  --initUniform                         initialize the offline inference with 
                                        uniform parameters, rather than seeding
                                        with online parameters.
  --maxOccsPerHit arg (=1000)           When collecting "hits" (MEMs), hits 
                                        having more than maxOccsPerHit 
                                        occurrences won't be considered.
  -w [ --maxReadOcc ] arg (=200)        Reads "mapping" to more than this many 
                                        places won't be considered.
  --maxRecoverReadOcc arg (=2500)       Relevant for alevin with '--sketch' 
                                        mode only: if a read has valid seed 
                                        matches, but no read has matches 
                                        leading to fewer than "maxReadOcc" 
                                        mappings, then try to recover mappings 
                                        for this read as long as there are 
                                        fewer than "maxRecoverReadOcc" 
                                        mappings.
  --noLengthCorrection                  [experimental] : Entirely disables 
                                        length correction when estimating the 
                                        abundance of transcripts.  This option 
                                        can be used with protocols where one 
                                        expects that fragments derive from 
                                        their underlying targets without regard
                                        to that target's length (e.g. QuantSeq)
  --noEffectiveLengthCorrection         Disables effective length correction 
                                        when computing the probability that a 
                                        fragment was generated from a 
                                        transcript.  If this flag is passed in,
                                        the fragment length distribution is not
                                        taken into account when computing this 
                                        probability.
  --noSingleFragProb                    Disables the estimation of an 
                                        associated fragment length probability 
                                        for single-end reads or for orphaned 
                                        mappings in paired-end libraries.  The 
                                        default behavior is to consider the 
                                        probability of all possible fragment 
                                        lengths associated with the retained 
                                        mapping.  Enabling this flag (i.e. 
                                        turning this default behavior off) will
                                        simply not attempt to estimate a 
                                        fragment length probability in such 
                                        cases.
  --noFragLengthDist                    [experimental] : Don't consider 
                                        concordance with the learned fragment 
                                        length distribution when trying to 
                                        determine the probability that a 
                                        fragment has originated from a 
                                        specified location.  Normally, 
                                        Fragments with unlikely lengths will be
                                        assigned a smaller relative probability
                                        than those with more likely lengths.  
                                        When this flag is passed in, the 
                                        observed fragment length has no effect 
                                        on that fragment's a priori 
                                        probability.
  --noBiasLengthThreshold               [experimental] : If this option is 
                                        enabled, then no (lower) threshold will
                                        be set on how short bias correction can
                                        make effective lengths. This can 
                                        increase the precision of bias 
                                        correction, but harm robustness.  The 
                                        default correction applies a threshold.
  --numBiasSamples arg (=2000000)       Number of fragment mappings to use when
                                        learning the sequence-specific bias 
                                        model.
  --numAuxModelSamples arg (=5000000)   The first <numAuxModelSamples> are used
                                        to train the auxiliary model parameters
                                        (e.g. fragment length distribution, 
                                        bias, etc.).  After ther first 
                                        <numAuxModelSamples> observations the 
                                        auxiliary model parameters will be 
                                        assumed to have converged and will be 
                                        fixed.
  --numPreAuxModelSamples arg (=5000)   The first <numPreAuxModelSamples> will 
                                        have their assignment likelihoods and 
                                        contributions to the transcript 
                                        abundances computed without applying 
                                        any auxiliary models.  The purpose of 
                                        ignoring the auxiliary models for the 
                                        first <numPreAuxModelSamples> 
                                        observations is to avoid applying these
                                        models before their parameters have 
                                        been learned sufficiently well.
  --useEM                               Use the traditional EM algorithm for 
                                        optimization in the batch passes.
  --useVBOpt                            Use the Variational Bayesian EM 
                                        [default]
  --rangeFactorizationBins arg (=4)     Factorizes the likelihood used in 
                                        quantification by adopting a new notion
                                        of equivalence classes based on the 
                                        conditional probabilities with which 
                                        fragments are generated from different 
                                        transcripts.  This is a more 
                                        fine-grained factorization than the 
                                        normal rich equivalence classes.  The 
                                        default value (4) corresponds to the 
                                        default used in Zakeri et al. 2017 
                                        (doi: 10.1093/bioinformatics/btx262), 
                                        and larger values imply a more 
                                        fine-grained factorization.  If range 
                                        factorization is enabled, a common 
                                        value to select for this parameter is 
                                        4. A value of 0 signifies the use of 
                                        basic rich equivalence classes.
  --numGibbsSamples arg (=0)            Number of Gibbs sampling rounds to 
                                        perform.
  --noGammaDraw                         This switch will disable drawing 
                                        transcript fractions from a Gamma 
                                        distribution during Gibbs sampling.  In
                                        this case the sampler does not account 
                                        for shot-noise, but only assignment 
                                        ambiguity
  --numBootstraps arg (=0)              Number of bootstrap samples to 
                                        generate. Note: This is mutually 
                                        exclusive with Gibbs sampling.
  --bootstrapReproject                  This switch will learn the parameter 
                                        distribution from the bootstrapped 
                                        counts for each sample, but will 
                                        reproject those parameters onto the 
                                        original equivalence class counts.
  --thinningFactor arg (=16)            Number of steps to discard for every 
                                        sample kept from the Gibbs chain. The 
                                        larger this number, the less chance 
                                        that subsequent samples are 
                                        auto-correlated, but the slower 
                                        sampling becomes.
  -q [ --quiet ]                        Be quiet while doing quantification 
                                        (don't write informative output to the 
                                        console unless something goes wrong).
  --perTranscriptPrior                  The prior (either the default or the 
                                        argument provided via --vbPrior) will 
                                        be interpreted as a transcript-level 
                                        prior (i.e. each transcript will be 
                                        given a prior read count of this value)
  --perNucleotidePrior                  The prior (either the default or the 
                                        argument provided via --vbPrior) will 
                                        be interpreted as a nucleotide-level 
                                        prior (i.e. each nucleotide will be 
                                        given a prior read count of this value)
  --sigDigits arg (=3)                  The number of significant digits to 
                                        write when outputting the 
                                        EffectiveLength and NumReads columns
  --vbPrior arg (=0.01)                 The prior that will be used in the VBEM
                                        algorithm.  This is interpreted as a 
                                        per-transcript prior, unless the 
                                        --perNucleotidePrior flag is also 
                                        given.  If the --perNucleotidePrior 
                                        flag is given, this is used as a 
                                        nucleotide-level prior.  If the default
                                        is used, it will be divided by 1000 
                                        before being used as a nucleotide-level
                                        prior, i.e. the default per-nucleotide 
                                        prior will be 1e-5.
  --writeOrphanLinks                    Write the transcripts that are linked 
                                        by orphaned reads.
  --writeUnmappedNames                  Write the names of un-mapped reads to 
                                        the file unmapped_names.txt in the 
                                        auxiliary directory.