comparison mageck_mle.xml @ 2:9cd937788131 draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/mageck commit 49e456dda49db1f52fc876f406a10273a408b1a2

1:93f268840b0c

#if $adv.cnv_norm:
    --cnv-norm $adv.cnv_norm
#end if

--norm-method $adv.norm_method
--genes-varmodeling $adv.genes_var
--permutation-round $adv.permutation
--adjust-method $adv.adjust_method

#if $adv.sgrnaeff_file:
    --sgrna-efficiency $adv.sgrnaeff_file
    --sgrna-eff-name-column $adv.sgrnaid_col
    --sgrna-eff-score-column $adv.sgrnaeff_col

            </param>
            <when value="dmatrix">
                <param name="design_matrix" argument="--design-matrix" type="data" format="tabular" label="Design Matrix file" help="Provide a design matrix, either a file name or a quoted string of the design matrix. For example, 1,1;1,0. The row of the design matrix must match the order of the samples in the count table (if --include-samples is not specified), or the order of the samples by the --include-samples option" />
            </when>
            <when value="labels">
                <param name="include_samples" argument="--include-samples" type="text" label="Sample labels" help="Specify the sample labels if the design matrix is not given by file in the --design-matrix option. Sample labels are separated by comma (,) and must match the labels in the count table" />
                <param name="day0_label" argument="--day0-label" type="text" format="tabular" optional="true" value="" label="Control sample" help="Specify the control sample label (usually day 0 or plasmid). For every other sample label, the MLE module will treat it as a single condition and generate an corresponding design matrix" />
                <param name="beta_labels" argument="--beta-labels" type="text" label="Variables" help="Specify the labels of the variables (i.e., beta), if the design matrix is not given by file in the --design-matrix option. Should be separated by commas (,), and the number of labels must equal to the number of columns of design matrix), including baseline labels. Default: bata_0,beta_1,beta_2,...." />
            </when>
        </conditional>

        <section name="adv" title="Advanced Options">
        <param name="control_sgrna" argument="--control-sgrna" type="data" format="tabular" optional="true" label="Control sgRNAs file" help="A list of control sgRNAs for normalization and for generating the null distribution of RRA" />
            <param name="cnv_norm" argument="--cnv-norm" type="data" format="tabular" optional="true" label="CNV profile file" help="A matrix of copy number variation data across cell lines to normalize CNV-biased BetaScores" />
            <param name="norm_method" argument="--norm-method" type="select" label="Method for normalization" help="If control is specified, the size factor will be estimated using control sgRNAs specified in --control-sgrna option. Default: Median" >
                <option value="none">None</option>
                <option value="median" selected="True">Median</option>
                <option value="total">Total</option>
                <option value="control">Control</option>
            </param>
            <param name="genes_var" argument="--genes-varmodeling" type="integer" value="1000" label="Number of genes for mean-variance modeling" help="Default: 1000" />
            <param name="permutation" argument="--permutation-round" type="integer" value="2" label="Number of permutations" help="The rounds for permutation. The permutation time is (# genes) * x for x rounds of permutation. Default: 2" />
            <param name="remove_outliers" argument="--remove-outliers" type="boolean" truevalue="--remove-outliers" falsevalue="" checked="false" optional="true" label="Try to remove outliers" help="Turning this option on will slow the algorithm" />
            <param name="adjust_method" argument="--adjust-method" type="select" label="P-Value Adjustment Method" help="Method for sgRNA-level p-value adjustment, including False Discovery Rate (FDR), Holm's method (Holm), or Pounds's method (Pounds). Default: FDR">
                <option value="fdr" selected="True">FDR</option>
                <option value="holm">Holm</option>
                <option value="pounds">Pounds</option>
            </param>
            <param name="sgrnaeff_file" argument="--sgrna-efficiency" type="data" format="tabular" optional="true" label="sgRNA efficiency file" help="An optional file of sgRNA efficiency prediction. The efficiency prediction will be used as an initial guess of the probability an sgRNA is efficient. Must contain at least two columns, one containing sgRNA ID, the other containing sgRNA efficiency prediction" />
            <param name="sgrnaeff_name_col" argument="--sgrna-eff-score-column" type="data_column" data_ref="sgrnaeff_file" value="1" optional="true" label="sgRNA score column" help="The sgRNA efficiency prediction column in sgRNA efficiency prediction file (specified by the --sgrna-efficiency option). Default is 1 (the second column)." />

The optional Control sgRNAs file is used to generate null distribution when calculating the p values. If this option is not specified, MAGeCK generates the null distribution of RRA scores by assuming all of the genes in the library are non-essential, see **More Information** below. This approach is sometimes over-conservative, and you can improve this if you know some genes are not essential. By providing the corresponding sgRNA IDs in this option, MAGeCK will have a better estimation of p values. To use this option, you need to prepare a text file specifying the IDs of control sgRNAs, one line for one sgRNA ID.

**Outputs**

If successful, MAGeCK mle will generate two files, the gene_summary file (including gene beta scores), and the sgrna_summary file (including sgRNA efficiency probability predictions).

**Gene summary file (including beta scores)**

An example of the gene summary output file is below. This file includes the beta scores in two conditions specified in the design matrix (HL60|beta and KBM7|beta), and the associated statistics. For more information, check the output format specification of the **mageck test** *Gene Summary* file.

======== ========= ============= ========== ================ ============ ===================== ================= ============= =========== ================ ============ ===================== =================
**Gene** **sgRNA** **HL60|beta** **HL60|z** **HL60|p-value** **HL60|fdr** **HL60|wald-p-value** **HL60|wald-fdr** **KBM7|beta** **KBM7|ze** **KBM7|p-value** **KBM7|fdr** **KBM7|wald-p-value** **KBM7|wald-fdr**

RNF10    10        0.10159       0.29373    0.92087          0.98235      0.76896               0.9999            0.11341       0.32794     0.90145          0.97365      0.74296               0.98421
RNF11    10        3.6354        10.513     0.00028          0.021739     7.5197e-26            1.3376e-22        2.5928        7.4925      0.0014898        0.032024     6.7577e-14            1.33e-11
======== ========= ============= ========== ================ ============ ===================== ================= ============= =========== ================ ============ ===================== =================


**sgRNA summary file (including sgRNA efficiency probability predictions)**

An example of the sgRNA ranking output is as follows:

================  ========  ================= ===================  ================  ============== =======  ===============  ===========  =========  ========= =========== ============== ===========  =====================
**sgrna**         **Gene**  **control_count** **treatment_count**  **control_mean**  **treat_mean** **LFC**  **control_var**  **adj_var**  **score**  **p.low** **p.high**  **p.twosided** **FDR**      **high_in_treatment**

2:9cd937788131

#if $adv.cnv_norm:
    --cnv-norm $adv.cnv_norm
#end if

#if $adv.norm_method:
    --norm-method $adv.norm_method
#end if

#if $adv.genes_var:
    --genes-varmodeling $adv.genes_var
#end if

#if $adv.permutation:
    --permutation-round $adv.permutation
#end if

#if $adv.adjust_method:
    --adjust-method $adv.adjust_method
#end if

#if $adv.sgrnaeff_file:
    --sgrna-efficiency $adv.sgrnaeff_file
    --sgrna-eff-name-column $adv.sgrnaid_col
    --sgrna-eff-score-column $adv.sgrnaeff_col

            </param>
            <when value="dmatrix">
                <param name="design_matrix" argument="--design-matrix" type="data" format="tabular" label="Design Matrix file" help="Provide a design matrix, either a file name or a quoted string of the design matrix. For example, 1,1;1,0. The row of the design matrix must match the order of the samples in the count table (if --include-samples is not specified), or the order of the samples by the --include-samples option" />
            </when>
            <when value="labels">
                <param name="include_samples" argument="--include-samples" type="text" label="Sample labels" help="Specify the sample labels if the design matrix is not given by file in the --design-matrix option. Sample labels are separated by comma (,) and must match the labels in the count table">
                    <validator type="regex" message="Please only use letters, numbers or underscores in sample labels, and separate labels by commas">^[\w,]+$</validator>
                </param>
                <param name="day0_label" argument="--day0-label" type="text" format="tabular" optional="true" value="" label="Control sample" help="Specify the control sample label (usually day 0 or plasmid). For every other sample label, the MLE module will treat it as a single condition and generate an corresponding design matrix">
                    <validator type="regex" message="Please only use letters, numbers or underscores in sample label">^[\w]+$</validator>
                </param>
                <param name="beta_labels" argument="--beta-labels" type="text" label="Variables" help="Specify the labels of the variables (i.e., beta), if the design matrix is not given by file in the --design-matrix option. Should be separated by commas (,), and the number of labels must equal to the number of columns of design matrix), including baseline labels. Default: bata_0,beta_1,beta_2,....">
                    <validator type="regex" message="Please only use letters, numbers or underscores in labels, and separate labels by commas">^[\w,]+$</validator>
                </param>
            </when>
        </conditional>

        <section name="adv" title="Advanced Options">
        <param name="control_sgrna" argument="--control-sgrna" type="data" format="tabular" optional="true" label="Control sgRNAs file" help="A list of control sgRNAs for normalization and for generating the null distribution of RRA" />
            <param name="cnv_norm" argument="--cnv-norm" type="data" format="tabular" optional="true" label="CNV profile file" help="A matrix of copy number variation data across cell lines to normalize CNV-biased BetaScores" />
            <param name="norm_method" argument="--norm-method" type="select" optional="true" label="Method for normalization" help="If control is specified, the size factor will be estimated using control sgRNAs specified in --control-sgrna option. Default: Median" >
                <option value="median" selected="True">Median</option>
                <option value="none">None</option>
                <option value="total">Total</option>
                <option value="control">Control</option>
            </param>
            <param name="genes_var" argument="--genes-varmodeling" type="integer" optional="true" label="Number of genes for mean-variance modeling" help="Default: 1000" />
            <param name="permutation" argument="--permutation-round" type="integer" optional="true" label="Number of permutations" help="The rounds for permutation. The permutation time is (# genes) * x for x rounds of permutation. Default: 2" />
            <param name="remove_outliers" argument="--remove-outliers" type="boolean" truevalue="--remove-outliers" falsevalue="" checked="false" optional="true" label="Try to remove outliers" help="Turning this option on will slow the algorithm" />
            <param name="adjust_method" argument="--adjust-method" type="select" optional="true" label="P-Value Adjustment Method" help="Method for sgRNA-level p-value adjustment, including False Discovery Rate (FDR), Holm's method (Holm), or Pounds's method (Pounds). Default: FDR">
                <option value="fdr">FDR</option>
                <option value="holm">Holm</option>
                <option value="pounds">Pounds</option>
            </param>
            <param name="sgrnaeff_file" argument="--sgrna-efficiency" type="data" format="tabular" optional="true" label="sgRNA efficiency file" help="An optional file of sgRNA efficiency prediction. The efficiency prediction will be used as an initial guess of the probability an sgRNA is efficient. Must contain at least two columns, one containing sgRNA ID, the other containing sgRNA efficiency prediction" />
            <param name="sgrnaeff_name_col" argument="--sgrna-eff-score-column" type="data_column" data_ref="sgrnaeff_file" value="1" optional="true" label="sgRNA score column" help="The sgRNA efficiency prediction column in sgRNA efficiency prediction file (specified by the --sgrna-efficiency option). Default is 1 (the second column)." />

The optional Control sgRNAs file is used to generate null distribution when calculating the p values. If this option is not specified, MAGeCK generates the null distribution of RRA scores by assuming all of the genes in the library are non-essential, see **More Information** below. This approach is sometimes over-conservative, and you can improve this if you know some genes are not essential. By providing the corresponding sgRNA IDs in this option, MAGeCK will have a better estimation of p values. To use this option, you need to prepare a text file specifying the IDs of control sgRNAs, one line for one sgRNA ID.

**Outputs**

This tool outputs

    * a ranked sgRNA Summary file
    * a ranked Gene Summary file

Optionally, under **Output Options** you can choose to output

    * a Log file of the analysis

If successful, MAGeCK mle will generate two files, the Gene Summary file (including gene beta scores), and the sgRNA Summary file (including sgRNA efficiency probability predictions).

**Gene Summary file (including beta scores)**

An example of the gene summary output file is below. This file includes the beta scores in two conditions specified in the design matrix (HL60|beta and KBM7|beta), and the associated statistics. For more information, check the output format specification of the **mageck test** *Gene Summary* file.

======== ========= ============= ========== ================ ============ ===================== ================= ============= =========== ================ ============ ===================== =================
**Gene** **sgRNA** **HL60|beta** **HL60|z** **HL60|p-value** **HL60|fdr** **HL60|wald-p-value** **HL60|wald-fdr** **KBM7|beta** **KBM7|ze** **KBM7|p-value** **KBM7|fdr** **KBM7|wald-p-value** **KBM7|wald-fdr**

RNF10    10        0.10159       0.29373    0.92087          0.98235      0.76896               0.9999            0.11341       0.32794     0.90145          0.97365      0.74296               0.98421
RNF11    10        3.6354        10.513     0.00028          0.021739     7.5197e-26            1.3376e-22        2.5928        7.4925      0.0014898        0.032024     6.7577e-14            1.33e-11
======== ========= ============= ========== ================ ============ ===================== ================= ============= =========== ================ ============ ===================== =================


**sgRNA Summary file (including sgRNA efficiency probability predictions)**

An example of the sgRNA ranking output is as follows:

================  ========  ================= ===================  ================  ============== =======  ===============  ===========  =========  ========= =========== ============== ===========  =====================
**sgrna**         **Gene**  **control_count** **treatment_count**  **control_mean**  **treat_mean** **LFC**  **control_var**  **adj_var**  **score**  **p.low** **p.high**  **p.twosided** **FDR**      **high_in_treatment**