Cufflinks下主要包含cufflinks,cuffmerge,cuffcompare和cuffdiff等几支主要的程序。主要用于转录组的组装和差异表达分析。
一、Cuffdiff简介
用于寻找转录子表达的显著性差异。
二、Cuffdiff使用方法
(默认Linux操作,此处省略安装步骤)
cuffdiff主要是发现转录本表达,剪接,启动子使用的明显变化。
Usage: cuffdiff [options] [... sampleN_hits.sam]
Supply replicate SAMs as comma separated lists for each condition: sample1_rep1.sam,sample1_rep2.sam,...sample1_repM.sam
其中transcripts.gtf是由cufflinks,cuffcompare,cuffmerge所生成的文件,或是由其它程序生成的。一个样本有多个replicate,用逗号隔开。sample多于一个时,cuffdiff将比较samples间的基因表达的差异性。
cuffdiff接受bam/sam或cuffquant的CXB文件,同时也可以接受bam与sam的混合文件,不能接受bam/sam和CXB的混合文件。
三、Cuffdiff参数说明
General Options:
-o/--output-dir write all output files to this directory [ default: ./ ] #输出的文件夹目录
-L/--labels comma-separated list of condition labels #给每个sample一个样品名或者一个环境条件一个lable
--FDR False discovery rate used in testing [ default: 0.05 ] #允许的false discovery rate
-M/--mask-file ignore all alignment within transcripts in this file [ default: NULL ] #提供GFF文件。Cufflinks将忽略比对到该GTF文件的transcripts中的reads。该文件中常常是rRNA的注释,也可以包含线立体和其它希望忽略的transcripts的注释。将这些不需要的RNA去除后,对计算mRNA的表达量是有利的。
-C/--contrast-file Perform the constrasts specified in this file [ default: NULL ] #比对指定文件
-b/--frag-bias-correct use bias correction - reference fasta required [ default: NULL ] #提供一个fasta文件来指导Cufflinks运行新的bias detection and correction algorithm。这样能明显提高转录子丰度计算的精确性。
-u/--multi-read-correct use 'rescue method' for multi-reads [ default: FALSE ] #让Cufflinks来做initial estimation步骤,从而更精确衡量比对到genome多个位点的reads。
-p/--num-threads number of threads used during quantification [ default: 1 ] #使用的CPU线程数
--no-diff Don't generate differential analysis files [ default: FALSE ] #不需要生成差异分析文件
--no-js-tests Don't perform isoform switching tests [ default: FALSE ] #不需要进行isoform转换测试
-T/--time-series treat samples as a time-series [ default: FALSE ] #让Cuffdiff来按样品顺序来比对样品,而不是对所有的samples都进行两两比对。即第二个SAM和第一个SAM比;第三个SAM和第二个SAM比;第四个SAM和第三个SAM比...
--library-type Library prep used for input reads [ default: below ] #处理的reads具有链特异性。比对结果中将会有个XS标签。一般Illumina数据的library-type为 fr-unstranded。
--dispersion-method Method used to estimate dispersion models [ default: below ] #用于估计分散模型的方法
--library-norm-method Method used to normalize library sizes [ default: below ] #用于标准化库大小的方法
四、Cuffdiff输出
1. FPKM tracking files
cuffdiff计算每个样本中的转录本,初始转录本和基因的FPKM。其中,基因和初始转录本的FPKM的计算是在每个转录本group和基因group中的转录本的FPKM的求和。
1|isoforms.fpkm_tracking Transcript FPKMs
2|genes.fpkm_tracking Gene FPKMs. Tracks the summed FPKM of transcripts sharing each gene_id
3|cds.fpkm_tracking Coding sequence FPKMs. Tracks the summed FPKM of transcripts sharing each p_id, independent of tss_id
4|tss_groups.fpkm_tracking Primary transcript FPKMs. Tracks the summed FPKM of transcripts sharing each tss_id
文件格式:
1|tracking_id class_code nearest_ref_id gene_id gene_short_name tss_id locus length coverage P1_FPKM P1_conf_lo P1_conf_hi P1_status P2_FPKM P2_conf_lo P2_conf_hi P2_status P3_FPKM P3_conf_lo P3_conf_hi P3_status
2|ENST00000000233 - - ENSG00000004059 ARF5 - 7:127220671-127242198 1103 - 58.3768 0 139.888 OK 47.3478 0 113.046 OK 78.9705 0 184.419 OK
注:P1、P2、P3为样本名
2. Count tracking files
评估每个样本中来自每个 transcript, primary transcript, and gene的fragment数目。其中primary transcript, and gene的fragment数目是每个primary transcript group或gene group中trancript的数目之和。
1|isoforms.count_tracking Transcript counts
2|genes.count_tracking Gene counts. Tracks the summed counts of transcripts sharing each gene_id
3|cds.count_tracking Coding sequence counts. Tracks the summed counts of transcripts sharing each p_id, independent of tss_id
4|tss_groups.count_tracking Primary transcript counts. Tracks the summed counts of transcripts sharing each tss_id
文件格式:
1|tracking_id P1_count P1_count_variance P1_count_uncertainty_var P1_count_dispersion_var P1_status P2_count P2_count_variance P2_count_uncertainty_var P2_count_dispersion_var P2_status P3_count P3_count_variance P3_count_uncertainty_var P3_count_dispersion_var P3_status
2|ENST00000000233 1226.79 733396 0 591186 OK 992.56 474498 0 376391 OK 1661.82 1.22994e+06 0 1.22994e+06 OK
3. Read group tracking files
计算在每个repulate中每个transcript, primary transcript和gene的表达量和frage数目。
1|isoforms.read_group_tracking Transcript read group tracking
2|genes.read_group_tracking Gene read group tracking. Tracks the summed expression and counts of transcripts sharing each gene_id in each replicate
3|cds.read_group_tracking Coding sequence FPKMs. Tracks the summed expression and counts of transcripts sharing each p_id, independent of tss_id in each replicate
4|tss_groups.read_group_tracking Primary transcript FPKMs. Tracks the summed expression and counts of transcripts sharing each tss_id in each replicate
文件格式:
1|tracking_id condition replicate raw_frags internal_scaled_frags external_scaled_frags FPKM effective_length status
2|ENST00000000233 MofRCC 1 1307.38 1182.81 1182.81 56.4898 - OK
4. Differential expression test files
对于splicing transcript,primary transcripts, genes, and coding sequences.样本之间的表达差异检验。对于每一对样本x和y,都会有以下四个文件:
1|isoform_exp.diff Transcript differential FPKM.
2|gene_exp.diff Gene differential FPKM. Tests difference sin the summed FPKM of transcripts sharing each gene_id
3|tss_group_exp.diff Primary transcript differential FPKM. Tests differences in the summed FPKM of transcripts sharing each tss_id
4|cds_exp.diff Coding sequence differential FPKM. Tests differences in the summed FPKM of transcripts sharing each p_id independent of tss_id
文件格式:
1|test_id gene_id gene locus sample_1 sample_2 status value_1 value_2 log2(fold_change) test_stat p_value q_value significant
2|ENST00000000233 ENSG00000004059 ARF5 7:127220671-127242198 MofRCC NofRCC OK 58.3768 47.3478 -0.302097 -0.212748 0.7584 0.992833 no
5. Differential splicing tests – splicing.diff
对于每个primary transcript,鉴定的不同的isoform的差异性。只有2个或2个以上的isoforms的primary transcript存在。
文件格式:
1|test_id gene_id gene locus sample_1 sample_2 status value_1 value_2 sqrt(JS) test_stat p_value q_value significant
6. Differential coding output – cds.diff
对于每个基因,它的cds的鉴定。样本间的输出cds的差异性。只有2个或2个以上的cds(multi-protein genes)列举在文件中。
文件格式:
1|test_id gene_id gene locus sample_1 sample_2 status value_1 value_2 sqrt(JS) test_stat p_value q_value significant
7. Differential promoter use – promoters.diff
样本间启动子使用的差异性。只有表达2个或2个以上isoform的基因列举在这里。
文件格式:
1|test_id gene_id gene locus sample_1 sample_2 status value_1 value_2 sqrt(JS) test_stat p_value q_value significant
8. Read group info – read_groups.info
每个repulate,在进行定量分析时,cuffdiff的关键属性会列出。
文件格式:
1|file condition replicate_num total_mass norm_mass internal_scale external_scale
2|/PROJ/*/Quantification/P1/abundances.cxb MofRCC 0 2.8904e+07 2.44127e+07 1.20839 1
9. Run info – run.info
运行信息。