目录
1.Module 1 - Introduction to RNA sequencing
- Installation
- Reference Genomes
- Annotations
- Indexing
- RNA-seq Data
- Pre-Alignment QC
2.Module 2 - RNA-seq Alignment and Visualization
- Adapter Trim
- Alignment
- IGV
- Alignment Visualization
- Alignment QC
3.Module 3 - Expression and Differential Expression
- Expression
- Differential Expression
- DE Visualization
- Kallisto for Reference-Free Abundance Estimation
4.Module 4 - Isoform Discovery and Alternative Expression
- Reference Guided Transcript Assembly
- de novo Transcript Assembly
- Transcript Assembly Merge
- Differential Splicing
- Splicing Visualization
5.Module 5 - De novo transcript reconstruction
- De novo RNA-Seq Assembly and Analysis Using Trinity
6.Module 6 - Functional Annotation of Transcripts
- Functional Annotation of Assembled Transcripts Using Trinotate
3.1 Expression
Stringtie
使用Stringtie从上一个模块中HISAT2生成的SAM/BAM文件中生成表达量统计
注意使用Stringtie从头发现转录本和差异表达
在本模块中,我们将以有参模式模式运行Stringtie。为了简化和减少运行时间,只使用已知的转录本。但是,Stringtie可以预测每个文库中存在的可能的转录本(通过删除Stringtie命令中的'-G'选项)。然后,Stringtie将为每个由数据组装的转录本分配任意的转录本id,并估计这些转录本的表达。
- Stringtie提供了一个merge命令合并不同文库的gtf文件
- 旦您有了一个合并的GTF文件,您就可以使用这个文件再次运行Stringtie,而不是我们上面使用的已知的transcripts GTF文件
- Stringtie还提供了“gffcompare”来比较预测的转录本和已知的转录本
- 参考Stringtie手册获得更详细的解释:
- https://ccb.jhu.edu/software/stringtie/index.shtml?t=manual
String的基础使用
stringtie [options]*
- '-p 8' tells Stringtie to use eight CPUs
- '-G
' reference annotation to use for guiding the assembly process (GTF/GFF3) - '-e' only estimate the abundance of given reference transcripts (requires -G)
- '-B' enable output of Ballgown table files which will be created in the same directory as the output GTF (requires -G, -o recommended)
- '-o' output path/file name for the assembled transcripts GTF (default: stdout)
- '-A' output path/file name for gene abundance estimates
stringtie -p 8 -G ../chr22_with_ERCC92.gtf -e -B -o HBR_Rep1/transcripts.gtf -A HBR_Rep1/gene_abundances.tsv HBR_Rep1.bam
stringtie -p 8 -G ../chr22_with_ERCC92.gtf -e -B -o HBR_Rep2/transcripts.gtf -A HBR_Rep2/gene_abundances.tsv HBR_Rep2.bam
stringtie -p 8 -G ../chr22_with_ERCC92.gtf -e -B -o HBR_Rep3/transcripts.gtf -A HBR_Rep3/gene_abundances.tsv HBR_Rep3.bam
stringtie -p 8 -G ../chr22_with_ERCC92.gtf -e -B -o UHR_Rep1/transcripts.gtf -A UHR_Rep1/gene_abundances.tsv UHR_Rep1.bam
stringtie -p 8 -G ../chr22_with_ERCC92.gtf -e -B -o UHR_Rep2/transcripts.gtf -A UHR_Rep2/gene_abundances.tsv UHR_Rep2.bam
stringtie -p 8 -G ../chr22_with_ERCC92.gtf -e -B -o UHR_Rep3/transcripts.gtf -A UHR_Rep3/gene_abundances.tsv UHR_Rep3.bam
Stringtie的原始输出是什么样子的?有关Stringtie输出文件的详细信息,请参阅Stringtie手册(输出部分)
less -S UHR_Rep1/transcripts.gtf
查看表达量
awk '{if ($3=="transcript") print}' UHR_Rep1/transcripts.gtf | cut -f 1,4,9 | less
22 15690026 gene_id "ENSG00000198062"; transcript_id "ENST00000343518"; ref_gene_name "POTEH"; cov "0.106554"; FPKM "2.778050"; TPM "3.623655";
22 15690078 gene_id "ENSG00000198062"; transcript_id "ENST00000621704"; ref_gene_name "POTEH"; cov "0.519912"; FPKM "13.555018"; TPM "17.681002";
基因和转录本水平表达值也可以在这两个文件中查看:
less -S UHR_Rep1/t_data.ctab
less -S UHR_Rep1/gene_abundances.tsv
创建一个整洁的表达式矩阵文件。这将在基因和转录水平上进行,还将产生各种不同的表达量表示方法:覆盖率、FPKM和TPM。
wget https://github.com/griffithlab/rnaseq_tutorial/blob/master/scripts/stringtie_expression_matrix.pl
chmod +x stringtie_expression_matrix.pl
./stringtie_expression_matrix.pl --expression_metric=TPM --result_dirs='HBR_Rep1,HBR_Rep2,HBR_Rep3,UHR_Rep1,UHR_Rep2,UHR_Rep3' --transcript_matrix_file=transcript_tpm_all_samples.tsv --gene_matrix_file=gene_tpm_all_samples.tsv
./stringtie_expression_matrix.pl --expression_metric=FPKM --result_dirs='HBR_Rep1,HBR_Rep2,HBR_Rep3,UHR_Rep1,UHR_Rep2,UHR_Rep3' --transcript_matrix_file=transcript_fpkm_all_samples.tsv --gene_matrix_file=gene_fpkm_all_samples.tsv
./stringtie_expression_matrix.pl --expression_metric=Coverage --result_dirs='HBR_Rep1,HBR_Rep2,HBR_Rep3,UHR_Rep1,UHR_Rep2,UHR_Rep3' --transcript_matrix_file=transcript_coverage_all_samples.tsv --gene_matrix_file=gene_coverage_all_samples.tsv
head transcript_tpm_all_samples.tsv gene_tpm_all_samples.tsv
HTSEQ-COUNT(粗略介绍)
http://www-huber.embl.de/users/anders/HTSeq/doc/count.html
htseq-count [options]
- '--format' specify the input file format one of BAM or SAM. Since we have BAM format files, select 'bam' for this option.
- '--order' provide the expected sort order of the input file. Previously we generated position sorted BAM files so use 'pos'.
- '--mode' determines how to deal with reads that overlap more than one feature. We believe the 'intersection-strict' mode is best.
- '--stranded' specifies whether data is stranded or not. The TruSeq strand-specific RNA libraries suggest the 'reverse' option for this parameter.
- '--minaqual' will skip all reads with alignment quality lower than the given minimum value
- '--type' specifies the feature type (3rd column in GFF file) to be used. (default, suitable for RNA-Seq and Ensembl GTF files: exon)
- '--idattr' The feature ID used to identity the counts in the output table. The default, suitable for RNA-SEq and Ensembl GTF files, is gene_id.
mkdir -p htseq_counts
cd htseq_counts
htseq-count --format bam --order pos --mode intersection-strict --stranded reverse --minaqual 1 --type exon --idattr gene_id ../UHR_Rep1.bam ../../chr22_with_ERCC92.gtf > UHR_Rep1_gene.tsv
htseq-count --format bam --order pos --mode intersection-strict --stranded reverse --minaqual 1 --type exon --idattr gene_id ../UHR_Rep2.bam ../../chr22_with_ERCC92.gtf > UHR_Rep2_gene.tsv
htseq-count --format bam --order pos --mode intersection-strict --stranded reverse --minaqual 1 --type exon --idattr gene_id ../UHR_Rep3.bam ../../chr22_with_ERCC92.gtf > UHR_Rep3_gene.tsv
htseq-count --format bam --order pos --mode intersection-strict --stranded reverse --minaqual 1 --type exon --idattr gene_id ../HBR_Rep1.bam ../../chr22_with_ERCC92.gtf > HBR_Rep1_gene.tsv
htseq-count --format bam --order pos --mode intersection-strict --stranded reverse --minaqual 1 --type exon --idattr gene_id ../HBR_Rep2.bam ../../chr22_with_ERCC92.gtf > HBR_Rep2_gene.tsv
htseq-count --format bam --order pos --mode intersection-strict --stranded reverse --minaqual 1 --type exon --idattr gene_id ../HBR_Rep3.bam ../../chr22_with_ERCC92.gtf > HBR_Rep3_gene.tsv
cd htseq_counts/
join UHR_Rep1_gene.tsv UHR_Rep2_gene.tsv | join - UHR_Rep3_gene.tsv | join - HBR_Rep1_gene.tsv | join - HBR_Rep2_gene.tsv | join - HBR_Rep3_gene.tsv > gene_read_counts_table_all.tsv
echo "GeneID UHR_Rep1 UHR_Rep2 UHR_Rep3 HBR_Rep1 HBR_Rep2 HBR_Rep3" > header.txt
cat header.txt gene_read_counts_table_all.tsv | grep -v "__" | perl -ne 'chomp $_; $_ =~ s/\s+/\t/g; print "$_\n"' > gene_read_counts_table_all_final.tsv
rm -f gene_read_counts_table_all.tsv header.txt
head gene_read_counts_table_all_final.tsv