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author nilesh
date Thu, 11 Jul 2013 12:24:01 -0400
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1 <tool id="infer_experiment" name="Infer Experiment">
2 <description>speculates how RNA-seq were configured</description>
3 <requirements>
4 <requirement type="package" version="2.3.7">rseqc</requirement>
5 </requirements>
6 <command interpreter="python"> infer_experiment.py -i $input -r $refgene
7
8 #if $sample_size.boolean
9 -s $sample_size.size
10 #end if
11
12 > $output
13 </command>
14 <inputs>
15 <param name="input" type="data" format="bam,sam" label="Input BAM/SAM file" />
16 <param name="refgene" type="data" format="bed" label="Reference gene model in bed format" />
17 <conditional name="sample_size">
18 <param name="boolean" type="boolean" label="Modify usable sampled reads" value="false" />
19 <when value="true">
20 <param name="size" type="integer" label="Number of usable sampled reads (default = 200000)" value="200000" />
21 </when>
22 </conditional>
23 </inputs>
24 <outputs>
25 <data format="txt" name="output" />
26 </outputs>
27 <help>
28 .. image:: https://code.google.com/p/rseqc/logo?cct=1336721062
29
30 -----
31
32 About RSeQC
33 +++++++++++
34
35 The RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. “Basic modules” quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while “RNA-seq specific modules” investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
36
37 The RSeQC package is licensed under the GNU GPL v3 license.
38
39 Inputs
40 ++++++++++++++
41
42 Input BAM/SAM file
43 Alignment file in BAM/SAM format.
44
45 Reference gene model
46 Gene model in BED format.
47
48 Number of usable sampled reads (default=200000)
49 Number of usable reads sampled from SAM/BAM file. More reads will give more accurate estimation, but make program little slower.
50
51
52 Output
53 ++++++++++++++
54 This program is used to speculate how RNA-seq sequencing were configured, especially how reads were stranded for strand-specific RNA-seq data, through comparing reads' mapping information to the underneath gene model. Generally, strand specific RNA-seq data should be handled differently in both visualization and RPKM calculation.
55
56 For pair-end RNA-seq, there are two different ways to strand reads:
57
58 1) 1++,1--,2+-,2-+
59 - read1 mapped to '+' strand indicates parental gene on '+' strand
60 - read1 mapped to '-' strand indicates parental gene on '-' strand
61 - read2 mapped to '+' strand indicates parental gene on '-' strand
62 - read2 mapped to '-' strand indicates parental gene on '+' strand
63 2) 1+-,1-+,2++,2--
64 - read1 mapped to '+' strand indicates parental gene on '-' strand
65 - read1 mapped to '-' strand indicates parental gene on '+' strand
66 - read2 mapped to '+' strand indicates parental gene on '+' strand
67 - read2 mapped to '-' strand indicates parental gene on '-' strand
68
69 For single-end RNA-seq, there are also two different ways to strand reads:
70
71 1) ++,--
72 -read mapped to '+' strand indicates parental gene on '+' strand
73 - read mapped to '-' strand indicates parental gene on '-' strand
74 2) +-,-+
75 - read mapped to '+' strand indicates parental gene on '-' strand
76 - read mapped to '-' strand indicates parental gene on '+' strand
77
78 Example Output
79 ++++++++++++++
80
81 **Example1** ::
82
83 =========================================================
84 This is PairEnd Data ::
85
86 Fraction of reads explained by "1++,1--,2+-,2-+": 0.4992
87 Fraction of reads explained by "1+-,1-+,2++,2--": 0.5008
88 Fraction of reads explained by other combinations: 0.0000
89 =========================================================
90
91 *Conclusion*: We can infer that this is NOT a strand specific because 50% of reads can be explained by "1++,1--,2+-,2-+", while the other 50% can be explained by "1+-,1-+,2++,2--".
92
93 **Example2** ::
94
95 ============================================================
96 This is PairEnd Data
97
98 Fraction of reads explained by "1++,1--,2+-,2-+": 0.9644 ::
99 Fraction of reads explained by "1+-,1-+,2++,2--": 0.0356
100 Fraction of reads explained by other combinations: 0.0000
101 ============================================================
102
103 *Conclusion*: We can infer that this is a strand-specific RNA-seq data. strandness of read1 is consistent with that of gene model, while strandness of read2 is opposite to the strand of reference gene model.
104
105 **Example3** ::
106
107 =========================================================
108 This is SingleEnd Data ::
109
110 Fraction of reads explained by "++,--": 0.9840 ::
111 Fraction of reads explained by "+-,-+": 0.0160
112 Fraction of reads explained by other combinations: 0.0000
113 =========================================================
114
115 *Conclusion*: This is single-end, strand specific RNA-seq data. Strandness of reads are concordant with strandness of reference gene.
116 </help>
117 </tool>