# Quantification using RSEM Like the previous exercise, we can use RSEM to estimate the expression levels of the re-constructed transcripts under the four conditions: logarithmic growth, plateau phase, heat shock and diauxic shift. First, we align the RNA-Seq reads to the Trinity transcripts using Bowtie. Then we run RSEM to estimate the number of reads mapped to each transcript. We do not need a splice-aware aligner (such as STAR) in this case because we are mapping the reads to cDNAs instead of a genomic sequence. Also the gap-free alignment produced by Bowtie is used as input for RSEM. ## Execute Locate `util/align_and_estimate_abundance.pl` in the trinityrnaseq-2.2.0 distribution, and run ``` cd ~/LSLNGS2015/Trinity bsub -q 4G -o ./RSEM_Sp_ds.std -e ./RSEM_Sp_ds.err -J RSEM_Sp_ds \ "PATH_TO_TRINITY/util/align_and_estimate_abundance.pl --seqType fq \ --left RNASEQ_data/Sp_ds.left.fq.gz --right RNASEQ_data/Sp_ds.right.fq.gz \ --transcripts trinity_reference/Trinity.fasta \ --output_prefix Sp_ds --est_method RSEM --aln_method bowtie \ --trinity_mode --prep_reference --output_dir RSEM_Sp_ds" bsub -q 4G -o ./RSEM_Sp_hs.std -e ./RSEM_Sp_hs.err -J RSEM_Sp_hs \ "PATH_TO_TRINITY/util/align_and_estimate_abundance.pl --seqType fq \ --left RNASEQ_data/Sp_hs.left.fq.gz --right RNASEQ_data/Sp_hs.right.fq.gz \ --transcripts trinity_reference/Trinity.fasta \ --output_prefix Sp_hs --est_method RSEM --aln_method bowtie \ --trinity_mode --prep_reference --output_dir RSEM_Sp_hs" bsub -q 4G -o ./RSEM_Sp_log.std -e ./RSEM_Sp_log.err -J RSEM_Sp_log \ "PATH_TO_TRINITY/util/align_and_estimate_abundance.pl --seqType fq \ --left RNASEQ_data/Sp_log.left.fq.gz --right RNASEQ_data/Sp_log.right.fq.gz \ --transcripts trinity_reference/Trinity.fasta \ --output_prefix Sp_log --est_method RSEM --aln_method bowtie \ --trinity_mode --prep_reference --output_dir RSEM_Sp_log" bsub -q 4G -o ./RSEM_Sp_plat.std -e ./RSEM_Sp_plat.err -J RSEM_Sp_plat \ "PATH_TO_TRINITY/util/align_and_estimate_abundance.pl --seqType fq \ --left RNASEQ_data/Sp_plat.left.fq.gz --right RNASEQ_data/Sp_plat.right.fq.gz \ --transcripts trinity_reference/Trinity.fasta \ --output_prefix Sp_plat --est_method RSEM --aln_method bowtie \ --trinity_mode --prep_reference --output_dir RSEM_Sp_plat" ``` Get status with `bjobs` ``` JOBID USER STAT QUEUE FROM_HOST EXEC_HOST JOB_NAME SUBMIT_TIME 993742 s00ycm0 RUN 4G alps1 2*alps1-40 RSEM_Sp_ds Nov 18 23:12 993743 s00ycm0 RUN 4G alps1 2*alps1-41 RSEM_Sp_hs Nov 18 23:12 993744 s00ycm0 RUN 4G alps1 2*alps1-42 *EM_Sp_log Nov 18 23:12 993745 s00ycm0 RUN 4G alps1 2*alps1-43 *M_Sp_plat Nov 18 23:12 ``` ## Resource usage | Job | ALPS Queue Name | CPU Time | Max Memory | Duration | | -------------- | --------------- | ---------- | ---------- | ---------- | | RSEM\_Sp\_ds | 4G | 42.28 sec. | - | 32 seconds | | RSEM\_Sp\_hs | 4G | 36.40 sec. | - | 26 seconds | | RSEM\_Sp\_log | 4G | 14.28 sec. | - | 13 seconds | | RSEM\_Sp\_plat | 4G | 48.40 sec. | - | 38 seconds | ## Estimations Once the jobs are completed, we will find `*.isoforms.results` and `*.genes.results` in the output folders. These files contain the expected counts and normalized expression values of the Trinity transcripts (isoforms) and components (genes). `ls -la RSEM_Sp_*/*results` ``` -rw-rw-r-- 1 ycl6 ycl6 28893 Oct 27 12:42 RSEM_Sp_ds/Sp_ds.genes.results -rw-rw-r-- 1 ycl6 ycl6 30731 Oct 27 12:42 RSEM_Sp_ds/Sp_ds.isoforms.results -rw-rw-r-- 1 ycl6 ycl6 28579 Oct 27 12:42 RSEM_Sp_hs/Sp_hs.genes.results -rw-rw-r-- 1 ycl6 ycl6 30369 Oct 27 12:42 RSEM_Sp_hs/Sp_hs.isoforms.results -rw-rw-r-- 1 ycl6 ycl6 28928 Oct 27 12:42 RSEM_Sp_log/Sp_log.genes.results -rw-rw-r-- 1 ycl6 ycl6 30754 Oct 27 12:42 RSEM_Sp_log/Sp_log.isoforms.results -rw-rw-r-- 1 ycl6 ycl6 28866 Oct 27 12:42 RSEM_Sp_plat/Sp_plat.genes.results -rw-rw-r-- 1 ycl6 ycl6 30685 Oct 27 12:42 RSEM_Sp_plat/Sp_plat.isoforms.results ``` We can use `head` to examine these files. Your values may not be the same because the assembly results are not deterministic. `head RSEM_Sp_ds/Sp_ds.genes.results` ``` gene_id transcript_id(s) length effective_length expected_count TPM FPKM TRINITY_DN0_c0_g1 TRINITY_DN0_c0_g1_i1 1420.00 1155.49 34.00 333.15 308.72 TRINITY_DN100_c0_g1 TRINITY_DN100_c0_g1_i1 289.00 39.76 21.72 6183.87 5730.39 TRINITY_DN101_c0_g1 TRINITY_DN101_c0_g1_i1 1695.00 1430.49 24.00 189.96 176.03 TRINITY_DN102_c0_g1 TRINITY_DN102_c0_g1_i1 3075.00 2810.49 110.00 443.14 410.65 TRINITY_DN103_c0_g1 TRINITY_DN103_c0_g1_i1 251.00 17.89 0.00 0.00 0.00 TRINITY_DN104_c0_g1 TRINITY_DN104_c0_g1_i1 3373.00 3108.49 106.00 386.09 357.78 TRINITY_DN105_c0_g1 TRINITY_DN105_c0_g1_i1 784.00 519.49 34.00 741.02 686.68 TRINITY_DN106_c0_g1 TRINITY_DN106_c0_g1_i1 1741.00 1476.49 83.87 643.14 595.98 TRINITY_DN107_c0_g1 TRINITY_DN107_c0_g1_i1 2416.00 2151.49 60.00 315.75 292.60 ``` `head RSEM_Sp_ds/Sp_ds.isoforms.results` ``` transcript_id gene_id length effective_length expected_count TPM FPKM IsoPct TRINITY_DN0_c0_g1_i1 TRINITY_DN0_c0_g1 1420 1155.49 34.00 333.15 308.72 100.00 TRINITY_DN100_c0_g1_i1 TRINITY_DN100_c0_g1 289 39.76 21.72 6183.87 5730.39 100.00 TRINITY_DN101_c0_g1_i1 TRINITY_DN101_c0_g1 1695 1430.49 24.00 189.96 176.03 100.00 TRINITY_DN102_c0_g1_i1 TRINITY_DN102_c0_g1 3075 2810.49 110.00 443.14 410.65 100.00 TRINITY_DN103_c0_g1_i1 TRINITY_DN103_c0_g1 251 17.89 0.00 0.00 0.00 0.00 TRINITY_DN104_c0_g1_i1 TRINITY_DN104_c0_g1 3373 3108.49 106.00 386.09 357.78 100.00 TRINITY_DN105_c0_g1_i1 TRINITY_DN105_c0_g1 784 519.49 34.00 741.02 686.68 100.00 TRINITY_DN106_c0_g1_i1 TRINITY_DN106_c0_g1 1741 1476.49 83.87 643.14 595.98 100.00 TRINITY_DN107_c0_g1_i1 TRINITY_DN107_c0_g1 2416 2151.49 60.00 315.75 292.60 100.00 ``` --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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