{
"$schema": "http://json-schema.org/draft-07/schema",
"title": "rsem_calculate_expression",
"description": "Calculate expression with RSEM. \n",
"type": "object",
"definitions": {

    
    
    "input" : {
    "title": "Input",
    "type": "object",
    "description": "No description",
    "properties": {
    
        
                "id": {
                "type":
                "string",
                "description": "Type: `string`. Sample ID",
                "help_text": "Type: `string`. Sample ID."
            
            }
    

        ,
                "strandedness": {
                "type":
                "string",
                "description": "Type: `string`, choices: ``forward`, `reverse`, `unstranded``. Sample strand-specificity",
                "help_text": "Type: `string`, choices: ``forward`, `reverse`, `unstranded``. Sample strand-specificity. Must be one of unstranded, forward, reverse",
                "enum": ["forward", "reverse", "unstranded"]
            
            
            }
    

        ,
                "paired": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Paired-end reads or not?",
                "help_text": "Type: `boolean_true`, default: `false`. Paired-end reads or not?"
            ,
                "default":false
            }
    

        ,
                "input": {
                "type":
                "string",
                "description": "Type: List of `file`, multiple_sep: `\";\"`. Input reads for quantification",
                "help_text": "Type: List of `file`, multiple_sep: `\";\"`. Input reads for quantification."
            
            }
    

        ,
                "index": {
                "type":
                "string",
                "description": "Type: `file`. RSEM index",
                "help_text": "Type: `file`. RSEM index."
            
            }
    

        ,
                "extra_args": {
                "type":
                "string",
                "description": "Type: `string`. Extra rsem-calculate-expression arguments in addition to the examples",
                "help_text": "Type: `string`. Extra rsem-calculate-expression arguments in addition to the examples."
            
            }
    

}
},
    
    
    "output" : {
    "title": "Output",
    "type": "object",
    "description": "No description",
    "properties": {
    
        
                "counts_gene": {
                "type":
                "string",
                "description": "Type: `file`, default: `$id.$key.counts_gene.results`, example: `$id.genes.results`. Expression counts on gene level",
                "help_text": "Type: `file`, default: `$id.$key.counts_gene.results`, example: `$id.genes.results`. Expression counts on gene level"
            ,
                "default":"$id.$key.counts_gene.results"
            }
    

        ,
                "counts_transcripts": {
                "type":
                "string",
                "description": "Type: `file`, default: `$id.$key.counts_transcripts.results`, example: `$id.isoforms.results`. Expression counts on transcript level",
                "help_text": "Type: `file`, default: `$id.$key.counts_transcripts.results`, example: `$id.isoforms.results`. Expression counts on transcript level"
            ,
                "default":"$id.$key.counts_transcripts.results"
            }
    

        ,
                "stat": {
                "type":
                "string",
                "description": "Type: `file`, default: `$id.$key.stat.stat`, example: `$id.stat`. RSEM statistics",
                "help_text": "Type: `file`, default: `$id.$key.stat.stat`, example: `$id.stat`. RSEM statistics"
            ,
                "default":"$id.$key.stat.stat"
            }
    

        ,
                "logs": {
                "type":
                "string",
                "description": "Type: `file`, default: `$id.$key.logs.log`, example: `$id.log`. RSEM logs",
                "help_text": "Type: `file`, default: `$id.$key.logs.log`, example: `$id.log`. RSEM logs"
            ,
                "default":"$id.$key.logs.log"
            }
    

        ,
                "bam_star": {
                "type":
                "string",
                "description": "Type: `file`, default: `$id.$key.bam_star.bam`, example: `$id.STAR.genome.bam`. BAM file generated by STAR (optional)",
                "help_text": "Type: `file`, default: `$id.$key.bam_star.bam`, example: `$id.STAR.genome.bam`. BAM file generated by STAR (optional)"
            ,
                "default":"$id.$key.bam_star.bam"
            }
    

        ,
                "bam_genome": {
                "type":
                "string",
                "description": "Type: `file`, default: `$id.$key.bam_genome.bam`, example: `$id.genome.bam`. Genome BAM file (optional)",
                "help_text": "Type: `file`, default: `$id.$key.bam_genome.bam`, example: `$id.genome.bam`. Genome BAM file (optional)"
            ,
                "default":"$id.$key.bam_genome.bam"
            }
    

        ,
                "bam_transcript": {
                "type":
                "string",
                "description": "Type: `file`, default: `$id.$key.bam_transcript.bam`, example: `$id.transcript.bam`. Transcript BAM file (optional)",
                "help_text": "Type: `file`, default: `$id.$key.bam_transcript.bam`, example: `$id.transcript.bam`. Transcript BAM file (optional)"
            ,
                "default":"$id.$key.bam_transcript.bam"
            }
    

        ,
                "sort_bam_by_read_name": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Sort BAM file aligned under transcript coordidate by read name",
                "help_text": "Type: `boolean_true`, default: `false`. Sort BAM file aligned under transcript coordidate by read name. Setting this option on will produce \ndeterministic maximum likelihood estimations from independent runs. Note that sorting will take long \ntime and lots of memory.\n"
            ,
                "default":false
            }
    

        ,
                "no_bam_output": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Do not output any BAM file",
                "help_text": "Type: `boolean_true`, default: `false`. Do not output any BAM file."
            ,
                "default":false
            }
    

        ,
                "sampling_for_bam": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. When RSEM generates a BAM file, instead of outputting all alignments a read has with their posterior \nprobabilities, one alignment is sampled according to the posterior probabilities",
                "help_text": "Type: `boolean_true`, default: `false`. When RSEM generates a BAM file, instead of outputting all alignments a read has with their posterior \nprobabilities, one alignment is sampled according to the posterior probabilities. The sampling procedure \nincludes the alignment to the \"noise\" transcript, which does not appear in the BAM file. Only the \nsampled alignment has a weight of 1. All other alignments have weight 0. If the \"noise\" transcript is \nsampled, all alignments appeared in the BAM file should have weight 0.\n"
            ,
                "default":false
            }
    

        ,
                "output_genome_bam": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Generate a BAM file, \u0027sample_name",
                "help_text": "Type: `boolean_true`, default: `false`. Generate a BAM file, \u0027sample_name.genome.bam\u0027, with alignments mapped to genomic coordinates and \nannotated with their posterior probabilities. In addition, RSEM will call samtools (included in RSEM \npackage) to sort and index the bam file. \u0027sample_name.genome.sorted.bam\u0027 and \u0027sample_name.genome.sorted.bam.bai\u0027 \nwill be generated.\n"
            ,
                "default":false
            }
    

        ,
                "sort_bam_by_coordinate": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Sort RSEM generated transcript and genome BAM files by coordinates and build associated indices",
                "help_text": "Type: `boolean_true`, default: `false`. Sort RSEM generated transcript and genome BAM files by coordinates and build associated indices.\n"
            ,
                "default":false
            }
    

}
},
    
    
    "basic options" : {
    "title": "Basic Options",
    "type": "object",
    "description": "No description",
    "properties": {
    
        
                "no_qualities": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Input reads do not contain quality scores",
                "help_text": "Type: `boolean_true`, default: `false`. Input reads do not contain quality scores."
            ,
                "default":false
            }
    

        ,
                "alignments": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Input file contains alignments in SAM/BAM/CRAM format",
                "help_text": "Type: `boolean_true`, default: `false`. Input file contains alignments in SAM/BAM/CRAM format. The exact file format will be determined \nautomatically.\n"
            ,
                "default":false
            }
    

        ,
                "fai": {
                "type":
                "string",
                "description": "Type: `file`. If the header section of input alignment file does not contain reference sequence information, \nthis option should be turned on",
                "help_text": "Type: `file`. If the header section of input alignment file does not contain reference sequence information, \nthis option should be turned on. \u003cfile\u003e is a FAI format file containing each reference sequence\u0027s \nname and length. Please refer to the SAM official website for the details of FAI format.\n"
            
            }
    

        ,
                "bowtie2": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Use Bowtie 2 instead of Bowtie to align reads",
                "help_text": "Type: `boolean_true`, default: `false`. Use Bowtie 2 instead of Bowtie to align reads. Since currently RSEM does not handle indel, local \nand discordant alignments, the Bowtie2 parameters are set in a way to avoid those alignments. In \nparticular, we use options \u0027--sensitive --dpad 0 --gbar 99999999 --mp 1,1 --np 1 --score_min L,0,-0.1\u0027 \nby default. The last parameter of \u0027--score_min\u0027, \u0027-0.1\u0027, is the negative of maximum mismatch rate. \nThis rate can be set by option \u0027--bowtie2_mismatch_rate\u0027. If reads are paired-end, we additionally \nuse options \u0027--no_mixed\u0027 and \u0027--no_discordant\u0027.\n"
            ,
                "default":false
            }
    

        ,
                "star": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Use STAR to align reads",
                "help_text": "Type: `boolean_true`, default: `false`. Use STAR to align reads. Alignment parameters are from ENCODE3\u0027s STAR-RSEM pipeline. To save \ncomputational time and memory resources, STAR\u0027s Output BAM file is unsorted. It is stored in RSEM\u0027s \ntemporary directory with name as \u0027sample_name.bam\u0027. Each STAR job will have its own private copy of \nthe genome in memory.\n"
            ,
                "default":false
            }
    

        ,
                "hisat2_hca": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Use HISAT2 to align reads to the transcriptome according to Human Cell Atlast",
                "help_text": "Type: `boolean_true`, default: `false`. Use HISAT2 to align reads to the transcriptome according to Human Cell Atlast.\n"
            ,
                "default":false
            }
    

        ,
                "append_names": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. If gene_name/transcript_name is available, append it to the end of gene_id/transcript_id (separated \nby \u0027_\u0027) in files \u0027sample_name",
                "help_text": "Type: `boolean_true`, default: `false`. If gene_name/transcript_name is available, append it to the end of gene_id/transcript_id (separated \nby \u0027_\u0027) in files \u0027sample_name.isoforms.results\u0027 and \u0027sample_name.genes.results\u0027.\n"
            ,
                "default":false
            }
    

        ,
                "seed": {
                "type":
                "integer",
                "description": "Type: `integer`. Set the seed for the random number generators used in calculating posterior mean estimates and \ncredibility intervals",
                "help_text": "Type: `integer`. Set the seed for the random number generators used in calculating posterior mean estimates and \ncredibility intervals. The seed must be a non-negative 32 bit integer.\n"
            
            }
    

        ,
                "single_cell_prior": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. By default, RSEM uses Dirichlet(1) as the prior to calculate posterior mean estimates and credibility \nintervals",
                "help_text": "Type: `boolean_true`, default: `false`. By default, RSEM uses Dirichlet(1) as the prior to calculate posterior mean estimates and credibility \nintervals. However, much less genes are expressed in single cell RNA-Seq data. Thus, if you want to \ncompute posterior mean estimates and/or credibility intervals and you have single-cell RNA-Seq data, \nyou are recommended to turn on this option. Then RSEM will use Dirichlet(0.1) as the prior which \nencourage the sparsity of the expression levels.\n"
            ,
                "default":false
            }
    

        ,
                "calc_pme": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Run RSEM\u0027s collapsed Gibbs sampler to calculate posterior mean estimates",
                "help_text": "Type: `boolean_true`, default: `false`. Run RSEM\u0027s collapsed Gibbs sampler to calculate posterior mean estimates."
            ,
                "default":false
            }
    

        ,
                "calc_ci": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Calculate 95% credibility intervals and posterior mean estimates",
                "help_text": "Type: `boolean_true`, default: `false`. Calculate 95% credibility intervals and posterior mean estimates. The credibility level can be \nchanged by setting \u0027--ci_credibility_level\u0027.\n"
            ,
                "default":false
            }
    

        ,
                "quiet": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Suppress the output of logging information",
                "help_text": "Type: `boolean_true`, default: `false`. Suppress the output of logging information."
            ,
                "default":false
            }
    

}
},
    
    
    "aligner options" : {
    "title": "Aligner Options",
    "type": "object",
    "description": "No description",
    "properties": {
    
        
                "seed_length": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `25`. Seed length used by the read aligner",
                "help_text": "Type: `integer`, example: `25`. Seed length used by the read aligner. Providing the correct value is important for RSEM. If RSEM \nruns Bowtie, it uses this value for Bowtie\u0027s seed length parameter. Any read with its or at least \none of its mates\u0027 (for paired-end reads) length less than this value will be ignored. If the \nreferences are not added poly(A) tails, the minimum allowed value is 5, otherwise, the minimum \nallowed value is 25. Note that this script will only check if the value \u003e= 5 and give a warning \nmessage if the value \u003c 25 but \u003e= 5. (Default: 25)\n"
            
            }
    

        ,
                "phred64_quals": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Input quality scores are encoded as Phred+64 (default for GA Pipeline ver",
                "help_text": "Type: `boolean_true`, default: `false`. Input quality scores are encoded as Phred+64 (default for GA Pipeline ver. \u003e= 1.3). This option is \nused by Bowtie, Bowtie 2 and HISAT2. Otherwise, quality score will be encoded as Phred+33. (Default: false)\n"
            ,
                "default":false
            }
    

        ,
                "solexa_quals": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Input quality scores are solexa encoded (from GA Pipeline ver",
                "help_text": "Type: `boolean_true`, default: `false`. Input quality scores are solexa encoded (from GA Pipeline ver. \u003c 1.3). This option is used by \nBowtie, Bowtie 2 and HISAT2. Otherwise, quality score will be encoded as Phred+33. (Default: false)\n"
            ,
                "default":false
            }
    

        ,
                "bowtie_n": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `2`, choices: ``0`, `1`, `2`, `3``. (Bowtie parameter) max # of mismatches in the seed",
                "help_text": "Type: `integer`, example: `2`, choices: ``0`, `1`, `2`, `3``. (Bowtie parameter) max # of mismatches in the seed. (Range: 0-3, Default: 2)\n",
                "enum": [0, 1, 2, 3]
            
            
            }
    

        ,
                "bowtie_e": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `99999999`. (Bowtie parameter) max sum of mismatch quality scores across the alignment",
                "help_text": "Type: `integer`, example: `99999999`. (Bowtie parameter) max sum of mismatch quality scores across the alignment. (Default: 99999999)\n"
            
            }
    

        ,
                "bowtie_m": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `200`. (Bowtie parameter) suppress all alignments for a read if \u003e \u003cint\u003e valid alignments exist",
                "help_text": "Type: `integer`, example: `200`. (Bowtie parameter) suppress all alignments for a read if \u003e \u003cint\u003e valid alignments exist. (Default: 200)\n"
            
            }
    

        ,
                "bowtie_chunkmbs": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `0`. (Bowtie parameter) memory allocated for best first alignment calculation (Default: 0 - use Bowtie\u0027s default)\n",
                "help_text": "Type: `integer`, example: `0`. (Bowtie parameter) memory allocated for best first alignment calculation (Default: 0 - use Bowtie\u0027s default)\n"
            
            }
    

        ,
                "bowtie2_mismatch_rate": {
                "type":
                "number",
                "description": "Type: `double`, example: `0.1`. (Bowtie 2 parameter) The maximum mismatch rate allowed",
                "help_text": "Type: `double`, example: `0.1`. (Bowtie 2 parameter) The maximum mismatch rate allowed. (Default: 0.1)\n"
            
            }
    

        ,
                "bowtie2_k": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `200`. (Bowtie 2 parameter) Find up to \u003cint\u003e alignments per read",
                "help_text": "Type: `integer`, example: `200`. (Bowtie 2 parameter) Find up to \u003cint\u003e alignments per read. (Default: 200)\n"
            
            }
    

        ,
                "bowtie2_sensitivity_level": {
                "type":
                "string",
                "description": "Type: `string`, example: `sensitive`, choices: ``very_fast`, `fast`, `sensitive`, `very_sensitive``. (Bowtie 2 parameter) Set Bowtie 2\u0027s preset options in --end-to-end mode",
                "help_text": "Type: `string`, example: `sensitive`, choices: ``very_fast`, `fast`, `sensitive`, `very_sensitive``. (Bowtie 2 parameter) Set Bowtie 2\u0027s preset options in --end-to-end mode. This option controls how \nhard Bowtie 2 tries to find alignments. \u003cstring\u003e must be one of \"very_fast\", \"fast\", \"sensitive\" \nand \"very_sensitive\". The four candidates correspond to Bowtie 2\u0027s \"--very-fast\", \"--fast\", \n\"--sensitive\" and \"--very-sensitive\" options. (Default: \"sensitive\" - use Bowtie 2\u0027s default)\n",
                "enum": ["very_fast", "fast", "sensitive", "very_sensitive"]
            
            
            }
    

        ,
                "star_gzipped_read_file": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Input read file(s) is compressed by gzip",
                "help_text": "Type: `boolean_true`, default: `false`. Input read file(s) is compressed by gzip. (Default: false)\n"
            ,
                "default":false
            }
    

        ,
                "star_bzipped_read_file": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Input read file(s) is compressed by bzip2",
                "help_text": "Type: `boolean_true`, default: `false`. Input read file(s) is compressed by bzip2. (Default: false)\n"
            ,
                "default":false
            }
    

        ,
                "star_output_genome_bam": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Save the BAM file from STAR alignment under genomic coordinate to \u0027sample_name",
                "help_text": "Type: `boolean_true`, default: `false`. Save the BAM file from STAR alignment under genomic coordinate to \u0027sample_name.STAR.genome.bam\u0027. \nThis file is NOT sorted by genomic coordinate. In this file, according to STAR\u0027s manual, \u0027paired \nends of an alignment are always adjacent, and multiple alignments of a read are adjacent as well\u0027. \n(Default: false)\n"
            ,
                "default":false
            }
    

}
},
    
    
    "advanced options" : {
    "title": "Advanced Options",
    "type": "object",
    "description": "No description",
    "properties": {
    
        
                "tag": {
                "type":
                "string",
                "description": "Type: `string`, example: ``. The name of the optional field used in the SAM input for identifying a read with too many valid \nalignments",
                "help_text": "Type: `string`, example: ``. The name of the optional field used in the SAM input for identifying a read with too many valid \nalignments. The field should have the format \u003ctagName\u003e:i:\u003cvalue\u003e, where a \u003cvalue\u003e bigger than 0 \nindicates a read with too many alignments. (Default: \"\")\n"
            
            }
    

        ,
                "fragment_length_min": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `1`. Minimum read/insert length allowed",
                "help_text": "Type: `integer`, example: `1`. Minimum read/insert length allowed. This is also the value for the Bowtie/Bowtie2 -I option. \n(Default: 1)\n"
            
            }
    

        ,
                "fragment_length_max": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `1000`. Maximum read/insert length allowed",
                "help_text": "Type: `integer`, example: `1000`. Maximum read/insert length allowed. This is also the value for the Bowtie/Bowtie 2 -X option. \n(Default: 1000)\n"
            
            }
    

        ,
                "fragment_length_mean": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `-1`. (single-end data only) The mean of the fragment length distribution, which is assumed to be a \nGaussian",
                "help_text": "Type: `integer`, example: `-1`. (single-end data only) The mean of the fragment length distribution, which is assumed to be a \nGaussian. (Default: -1, which disables use of the fragment length distribution)\n"
            
            }
    

        ,
                "gragment_length_sd": {
                "type":
                "number",
                "description": "Type: `double`, example: `0.0`. (single-end data only) The standard deviation of the fragment length distribution, which is \nassumed to be a Gaussian",
                "help_text": "Type: `double`, example: `0.0`. (single-end data only) The standard deviation of the fragment length distribution, which is \nassumed to be a Gaussian. (Default: 0, which assumes that all fragments are of the same length, \ngiven by the rounded value of --fragment_length_mean).\n"
            
            }
    

        ,
                "estimate_rspd": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Set this option if you want to estimate the read start position distribution (RSPD) from data",
                "help_text": "Type: `boolean_true`, default: `false`. Set this option if you want to estimate the read start position distribution (RSPD) from data.\nOtherwise, RSEM will use a uniform RSPD.\n"
            ,
                "default":false
            }
    

        ,
                "num_rspd_bins": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `20`. Number of bins in the RSPD",
                "help_text": "Type: `integer`, example: `20`. Number of bins in the RSPD. Only relevant when \u0027--estimate_rspd\u0027 is specified. Use of the default \nsetting is recommended. (Default: 20)\n"
            
            }
    

        ,
                "gibbs_burnin": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `200`. The number of burn-in rounds for RSEM\u0027s Gibbs sampler",
                "help_text": "Type: `integer`, example: `200`. The number of burn-in rounds for RSEM\u0027s Gibbs sampler. Each round passes over the entire data set \nonce. If RSEM can use multiple threads, multiple Gibbs samplers will start at the same time and all \nsamplers share the same burn-in number. (Default: 200)\n"
            
            }
    

        ,
                "gibbs_number_of_samples": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `1000`. The total number of count vectors RSEM will collect from its Gibbs samplers",
                "help_text": "Type: `integer`, example: `1000`. The total number of count vectors RSEM will collect from its Gibbs samplers. (Default: 1000)\n"
            
            }
    

        ,
                "gibbs_sampling_gap": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `1`. The number of rounds between two succinct count vectors RSEM collects",
                "help_text": "Type: `integer`, example: `1`. The number of rounds between two succinct count vectors RSEM collects. If the count vector after \nround N is collected, the count vector after round N + \u003cint\u003e will also be collected. (Default: 1)\n"
            
            }
    

        ,
                "ci_credibility_level": {
                "type":
                "number",
                "description": "Type: `double`, example: `0.95`. The credibility level for credibility intervals",
                "help_text": "Type: `double`, example: `0.95`. The credibility level for credibility intervals. (Default: 0.95)\n"
            
            }
    

        ,
                "ci_number_of_samples_per_count_vector": {
                "type":
                "integer",
                "description": "Type: `integer`, example: `50`. The number of read generating probability vectors sampled per sampled count vector",
                "help_text": "Type: `integer`, example: `50`. The number of read generating probability vectors sampled per sampled count vector. The crebility \nintervals are calculated by first sampling P(C | D) and then sampling P(Theta | C) for each sampled \ncount vector. This option controls how many Theta vectors are sampled per sampled count vector. \n(Default: 50)\n"
            
            }
    

        ,
                "keep_intermediate_files": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Keep temporary files generated by RSEM",
                "help_text": "Type: `boolean_true`, default: `false`. Keep temporary files generated by RSEM. RSEM creates a temporary directory, \u0027sample_name.temp\u0027, \ninto which it puts all intermediate output files. If this directory already exists, RSEM overwrites \nall files generated by previous RSEM runs inside of it. By default, after RSEM finishes, the \ntemporary directory is deleted. Set this option to prevent the deletion of this directory and the \nintermediate files inside of it.\n"
            ,
                "default":false
            }
    

        ,
                "temporary_folder": {
                "type":
                "string",
                "description": "Type: `string`, example: `sample_name.temp`. Set where to put the temporary files generated by RSEM",
                "help_text": "Type: `string`, example: `sample_name.temp`. Set where to put the temporary files generated by RSEM. If the folder specified does not exist, \nRSEM will try to create it. (Default: sample_name.temp)\n"
            
            }
    

        ,
                "time": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Output time consumed by each step of RSEM to \u0027sample_name",
                "help_text": "Type: `boolean_true`, default: `false`. Output time consumed by each step of RSEM to \u0027sample_name.time\u0027.\n"
            ,
                "default":false
            }
    

}
},
    
    
    "prior-enhanced rsem options" : {
    "title": "Prior-Enhanced RSEM Options",
    "type": "object",
    "description": "No description",
    "properties": {
    
        
                "run_pRSEM": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Running prior-enhanced RSEM (pRSEM)",
                "help_text": "Type: `boolean_true`, default: `false`. Running prior-enhanced RSEM (pRSEM). Prior parameters, i.e. isoform\u0027s initial pseudo-count for \nRSEM\u0027s Gibbs sampling, will be learned from input RNA-seq data and an external data set. When pRSEM \nneeds and only needs ChIP-seq peak information to partition isoforms (e.g. in pRSEM\u0027s default \npartition model), either ChIP-seq peak file (with the \u0027--chipseq_peak_file\u0027 option) or ChIP-seq \nFASTQ files for target and input and the path for Bowtie executables are required (with the \n\u0027--chipseq_target_read_files \u003cstring\u003e\u0027, \u0027--chipseq_control_read_files \u003cstring\u003e\u0027, and \u0027--bowtie_path \n\u003cpath\u003e options), otherwise, ChIP-seq FASTQ files for target and control and the path to Bowtie \nexecutables are required.\n"
            ,
                "default":false
            }
    

        ,
                "chipseq_peak_file": {
                "type":
                "string",
                "description": "Type: `file`. Full path to a ChIP-seq peak file in ENCODE\u0027s narrowPeak, i",
                "help_text": "Type: `file`. Full path to a ChIP-seq peak file in ENCODE\u0027s narrowPeak, i.e. BED6+4, format. This file is used \nwhen running prior-enhanced RSEM in the default two-partition model. It partitions isoforms by \nwhether they have ChIP-seq overlapping with their transcription start site region or not. Each \npartition will have its own prior parameter learned from a training set. This file can be either \ngzipped or ungzipped.\n"
            
            }
    

        ,
                "chipseq_target_read_files": {
                "type":
                "string",
                "description": "Type: `file`. Comma-separated full path of FASTQ read file(s) for ChIP-seq target",
                "help_text": "Type: `file`. Comma-separated full path of FASTQ read file(s) for ChIP-seq target. This option is used when running \nprior-enhanced RSEM. It provides information to calculate ChIP-seq peaks and signals. The file(s) \ncan be either ungzipped or gzipped with a suffix \u0027.gz\u0027 or \u0027.gzip\u0027. The options \u0027--bowtie_path \u003cpath\u003e\u0027 \nand \u0027--chipseq_control_read_files \u003cstring\u003e\u0027 must be defined when this option is specified.\n"
            
            }
    

        ,
                "chipseq_control_read_files": {
                "type":
                "string",
                "description": "Type: `file`. Comma-separated full path of FASTQ read file(s) for ChIP-seq conrol",
                "help_text": "Type: `file`. Comma-separated full path of FASTQ read file(s) for ChIP-seq conrol. This option is used when running \nprior-enhanced RSEM. It provides information to call ChIP-seq peaks. The file(s) can be either \nungzipped or gzipped with a suffix \u0027.gz\u0027 or \u0027.gzip\u0027. The options \u0027--bowtie_path \u003cpath\u003e\u0027 and \n\u0027--chipseq_target_read_files \u003cstring\u003e\u0027 must be defined when this option is specified.\n"
            
            }
    

        ,
                "chipseq_read_files_multi_targets": {
                "type":
                "string",
                "description": "Type: `file`. Comma-separated full path of FASTQ read files for multiple ChIP-seq targets",
                "help_text": "Type: `file`. Comma-separated full path of FASTQ read files for multiple ChIP-seq targets. This option is used when \nrunning prior-enhanced RSEM, where prior is learned from multiple complementary data sets. It provides \ninformation to calculate ChIP-seq signals. All files can be either ungzipped or gzipped with a suffix \n\u0027.gz\u0027 or \u0027.gzip\u0027. When this option is specified, the option \u0027--bowtie_path \u003cpath\u003e\u0027 must be defined and \nthe option \u0027--partition_model \u003cstring\u003e\u0027 will be set to \u0027cmb_lgt\u0027 automatically.\n"
            
            }
    

        ,
                "chipseq_bed_files_multi_targets": {
                "type":
                "string",
                "description": "Type: `file`. Comma-separated full path of BED files for multiple ChIP-seq targets",
                "help_text": "Type: `file`. Comma-separated full path of BED files for multiple ChIP-seq targets. This option is used when running \nprior-enhanced RSEM, where prior is learned from multiple complementary data sets. It provides information \nof ChIP-seq signals and must have at least the first six BED columns. All files can be either ungzipped \nor gzipped with a suffix \u0027.gz\u0027 or \u0027.gzip\u0027. When this option is specified, the option \u0027--partition_model \n\u003cstring\u003e\u0027 will be set to \u0027cmb_lgt\u0027 automatically.\n"
            
            }
    

        ,
                "cap_stacked_chipseq_reads": {
                "type":
                "boolean",
                "description": "Type: `boolean_true`, default: `false`. Keep a maximum number of ChIP-seq reads that aligned to the same genomic interval",
                "help_text": "Type: `boolean_true`, default: `false`. Keep a maximum number of ChIP-seq reads that aligned to the same genomic interval. This option is used \nwhen running prior-enhanced RSEM, where prior is learned from multiple complementary data sets. This \noption is only in use when either \u0027--chipseq_read_files_multi_targets \u003cstring\u003e\u0027 or \n\u0027--chipseq_bed_files_multi_targets \u003cstring\u003e\u0027 is specified.\n"
            ,
                "default":false
            }
    

        ,
                "n_max_stacked_chipseq_reads": {
                "type":
                "integer",
                "description": "Type: `integer`. The maximum number of stacked ChIP-seq reads to keep",
                "help_text": "Type: `integer`. The maximum number of stacked ChIP-seq reads to keep. This option is used when running prior-enhanced \nRSEM, where prior is learned from multiple complementary data sets. This option is only in use when the \noption \u0027--cap_stacked_chipseq_reads\u0027 is set.\n"
            
            }
    

        ,
                "partition_model": {
                "type":
                "string",
                "description": "Type: `string`, example: `pk`. A keyword to specify the partition model used by prior-enhanced RSEM",
                "help_text": "Type: `string`, example: `pk`. A keyword to specify the partition model used by prior-enhanced RSEM. It must be one of the following \nkeywords:\n* pk\n* pk_lgtnopk\n* lm3, lm4, lm5, or lm6\n* nopk_lm2pk, nopk_lm3pk, nopk_lm4pk, or nopk_lm5pk\n* pk_lm2nopk, pk_lm3nopk, pk_lm4nopk, or pk_lm5nopk\n* cmb_lgt\nParameters for all the above models are learned from a training set. For detailed explanations, please \nsee prior-enhanced RSEM\u0027s paper. (Default: \u0027pk\u0027)\n"
            
            }
    

}
},
    
    
    "nextflow input-output arguments" : {
    "title": "Nextflow input-output arguments",
    "type": "object",
    "description": "Input/output parameters for Nextflow itself. Please note that both publishDir and publish_dir are supported but at least one has to be configured.",
    "properties": {
    
        
                "publish_dir": {
                "type":
                "string",
                "description": "Type: `string`, required, example: `output/`. Path to an output directory",
                "help_text": "Type: `string`, required, example: `output/`. Path to an output directory."
            
            }
    

        ,
                "param_list": {
                "type":
                "string",
                "description": "Type: `string`, example: `my_params.yaml`. Allows inputting multiple parameter sets to initialise a Nextflow channel",
                "help_text": "Type: `string`, example: `my_params.yaml`. Allows inputting multiple parameter sets to initialise a Nextflow channel. A `param_list` can either be a list of maps, a csv file, a json file, a yaml file, or simply a yaml blob.\n\n* A list of maps (as-is) where the keys of each map corresponds to the arguments of the pipeline. Example: in a `nextflow.config` file: `param_list: [ [\u0027id\u0027: \u0027foo\u0027, \u0027input\u0027: \u0027foo.txt\u0027], [\u0027id\u0027: \u0027bar\u0027, \u0027input\u0027: \u0027bar.txt\u0027] ]`.\n* A csv file should have column names which correspond to the different arguments of this pipeline. Example: `--param_list data.csv` with columns `id,input`.\n* A json or a yaml file should be a list of maps, each of which has keys corresponding to the arguments of the pipeline. Example: `--param_list data.json` with contents `[ {\u0027id\u0027: \u0027foo\u0027, \u0027input\u0027: \u0027foo.txt\u0027}, {\u0027id\u0027: \u0027bar\u0027, \u0027input\u0027: \u0027bar.txt\u0027} ]`.\n* A yaml blob can also be passed directly as a string. Example: `--param_list \"[ {\u0027id\u0027: \u0027foo\u0027, \u0027input\u0027: \u0027foo.txt\u0027}, {\u0027id\u0027: \u0027bar\u0027, \u0027input\u0027: \u0027bar.txt\u0027} ]\"`.\n\nWhen passing a csv, json or yaml file, relative path names are relativized to the location of the parameter file. No relativation is performed when `param_list` is a list of maps (as-is) or a yaml blob.",
                "hidden": true
            
            }
    

}
}
},
"allOf": [

    {
    "$ref": "#/definitions/input"
    },

    {
    "$ref": "#/definitions/output"
    },

    {
    "$ref": "#/definitions/basic options"
    },

    {
    "$ref": "#/definitions/aligner options"
    },

    {
    "$ref": "#/definitions/advanced options"
    },

    {
    "$ref": "#/definitions/prior-enhanced rsem options"
    },

    {
    "$ref": "#/definitions/nextflow input-output arguments"
    }
]
}
