transcript assembly and FPKM (RPKM) estimates for RNA-Seq data cufflinks cufflinks_wrapper.py --input=$input --assembled-isoforms-output=$assembled_isoforms --transcripts-expression-output=$transcripts_expression --genes-expression-output=$genes_expression --num-threads="4" -I $max_intron_len -F $min_isoform_fraction -j $pre_mrna_fraction -Q $min_map_quality #if $reference_annotation.use_ref == "Yes": -G $reference_annotation.reference_annotation_file #end if #if $singlePaired.sPaired == "paired": -m $singlePaired.mean_inner_distance -s $singlePaired.inner_distance_std_dev #end if **Cufflinks Overview** Cufflinks_ assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one. Please cite: Trapnell C, Williams BA, Pertea G, Mortazavi AM, Kwan G, van Baren MJ, Salzberg SL, Wold B, Pachter L. Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms. Nature Biotechnology doi:10.1038/nbt.1621 .. _Cufflinks: http://cufflinks.cbcb.umd.edu/ ------ **Know what you are doing** .. class:: warningmark There is no such thing (yet) as an automated gearshift in expression analysis. It is all like stick-shift driving in San Francisco. In other words, running this tool with default parameters will probably not give you meaningful results. A way to deal with this is to **understand** the parameters by carefully reading the `documentation`__ and experimenting. Fortunately, Galaxy makes experimenting easy. .. __: http://cufflinks.cbcb.umd.edu/manual.html ------ **Input formats** Cufflinks takes a text file of SAM alignments as input. The RNA-Seq read mapper TopHat produces output in this format, and is recommended for use with Cufflinks. However Cufflinks will accept SAM alignments generated by any read mapper. Here's an example of an alignment Cufflinks will accept:: s6.25mer.txt-913508 16 chr1 4482736 255 14M431N11M * 0 0 \ CAAGATGCTAGGCAAGTCTTGGAAG IIIIIIIIIIIIIIIIIIIIIIIII NM:i:0 XS:A:- Note the use of the custom tag XS. This attribute, which must have a value of "+" or "-", indicates which strand the RNA that produced this read came from. While this tag can be applied to any alignment, including unspliced ones, it must be present for all spliced alignment records (those with a 'N' operation in the CIGAR string). The SAM file supplied to Cufflinks must be sorted by reference position. If you aligned your reads with TopHat, your alignments will be properly sorted already. If you used another tool, you may want to make sure they are properly sorted as follows:: sort -k 3,3 -k 4,4n hits.sam > hits.sam.sorted NOTE: Cufflinks currently only supports SAM alignments with the CIGAR match ('M') and reference skip ('N') operations. Support for the other operations, such as insertions, deletions, and clipping, will be added in the future. ------ **Outputs** Cufflinks produces three output files: Transcripts and Genes: This GTF file contains Cufflinks' assembled isoforms. The first 7 columns are standard GTF, and the last column contains attributes, some of which are also standardized (e.g. gene_id, transcript_id). There one GTF record per row, and each record represents either a transcript or an exon within a transcript. The columns are defined as follows:: Column number Column name Example Description ----------------------------------------------------- 1 seqname chrX Chromosome or contig name 2 source Cufflinks The name of the program that generated this file (always 'Cufflinks') 3 feature exon The type of record (always either "transcript" or "exon"). 4 start 77696957 The leftmost coordinate of this record (where 0 is the leftmost possible coordinate) 5 end 77712009 The rightmost coordinate of this record, inclusive. 6 score 77712009 The most abundant isoform for each gene is assigned a score of 1000. Minor isoforms are scored by the ratio (minor FPKM/major FPKM) 7 strand + Cufflinks' guess for which strand the isoform came from. Always one of '+', '-' '.' 7 frame . Cufflinks does not predict where the start and stop codons (if any) are located within each transcript, so this field is not used. 8 attributes See below Each GTF record is decorated with the following attributes:: Attribute Example Description ----------------------------------------- gene_id CUFF.1 Cufflinks gene id transcript_id CUFF.1.1 Cufflinks transcript id FPKM 101.267 Isoform-level relative abundance in Reads Per Kilobase of exon model per Million mapped reads frac 0.7647 Reserved. Please ignore, as this attribute may be deprecated in the future conf_lo 0.07 Lower bound of the 95% confidence interval of the abundance of this isoform, as a fraction of the isoform abundance. That is, lower bound = FPKM * (1.0 - conf_lo) conf_hi 0.1102 Upper bound of the 95% confidence interval of the abundance of this isoform, as a fraction of the isoform abundance. That is, upper bound = FPKM * (1.0 + conf_lo) cov 100.765 Estimate for the absolute depth of read coverage across the whole transcript Transcripts only: This file is simply a tab delimited file containing one row per transcript and with columns containing the attributes above. There are a few additional attributes not in the table above, but these are reserved for debugging, and may change or disappear in the future. Genes only: This file contains gene-level coordinates and expression values. ------- **Cufflinks settings** All of the options have a default value. You can change any of them. Most of the options in Cufflinks have been implemented here. ------ **Cufflinks parameter list** This is a list of implemented Cufflinks options:: -m INT This is the expected (mean) inner distance between mate pairs. For, example, for paired end runs with fragments selected at 300bp, where each end is 50bp, you should set -r to be 200. The default is 45bp. -s INT The standard deviation for the distribution on inner distances between mate pairs. The default is 20bp. -I INT The minimum intron length. Cufflinks will not report transcripts with introns longer than this, and will ignore SAM alignments with REF_SKIP CIGAR operations longer than this. The default is 300,000. -F After calculating isoform abundance for a gene, Cufflinks filters out transcripts that it believes are very low abundance, because isoforms expressed at extremely low levels often cannot reliably be assembled, and may even be artifacts of incompletely spliced precursors of processed transcripts. This parameter is also used to filter out introns that have far fewer spliced alignments supporting them. The default is 0.05, or 5% of the most abundant isoform (the major isoform) of the gene. -j Some RNA-Seq protocols produce a significant amount of reads that originate from incompletely spliced transcripts, and these reads can confound the assembly of fully spliced mRNAs. Cufflinks uses this parameter to filter out alignments that lie within the intronic intervals implied by the spliced alignments. The minimum depth of coverage in the intronic region covered by the alignment is divided by the number of spliced reads, and if the result is lower than this parameter value, the intronic alignments are ignored. The default is 5%. -Q Instructs Cufflinks to ignore alignments with a SAM mapping quality lower than this number. The default is 0. -G Tells Cufflinks to use the supplied reference annotation to estimate isoform expression. It will not assemble novel transcripts, and the program will ignore alignments not structurally compatible with any reference transcript.