Command Line Tools for Genomic Data Science Coursera Quiz Answers 2022 | All Weeks Assessment Answers [💯Correct Answer]

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About Command Line Tools for Genomic Data Science Course

Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

SKILLS YOU WILL GAIN

• Bioinformatics
• Samtools
• Unix
• Command-Line Interface

Course Apply Link – Command Line Tools for Genomic Data Science

Command Line Tools for Genomic Data Science Quiz Answers

Week 1 Quiz Answers

Quiz 1: Module 1 Quiz

Q1. Which of the following Unix commands can be used to view the content of a file?

• wc
• uniq
• less
• pwd

Q2. Which of the following commands can be using to compress the content of a file?

• top
• cd
• gzip
• rmdir

Q3. The file “months” lists each of the 12 months on a separate line, and no further lines. What would be the result if the following command was run:

cat months | head -1000 | wc –l

• 12
• July
• September
• April

Q4. What is the effect of using the pipe operator ‘|’ in a sequence of commands:

• Replace the ‘;’ sequencing operator in a complex command
• Re-direct the standard input or standard output of a command
• Re-direct standard error only
• Act as a character separator between different shell commands, without any effects on the outcome

Q5. If typing ‘pwd’ produces “/home/userA/Coursera/L1/”, which of the following commands will list the file content of the current directory?

• cat .
• uniq –c
• sort * | ls
• ls .

Q6. Suppose your current working directory is “/home/Coursera/L1/”, and “peach”, “apple” and “pear” are subdirectories, each containing a single file named “genome”. What would be the current directory, as reported by running the ‘pwd’ command, after each of the four commands in the sequence below:

      cd apple
      rm *
      cd ../..
      mv apple plum

/home/Coursera/L1/apple/home/Coursera/L1/apple/home/Coursera/home/Coursera

L1Courseraappleplum

/home/Coursera/L1/home/Coursera/L1/appleL1/apple/home/Coursera/L1

plumapplepearstrawberry

Q7. Consider the file “seasons” with the following columns separated by spaces ‘ ‘:

January 1 winter
…
December 12 winter

What would be the sequence of outputs for the following commands:
cut -d ' ' -f1,3 seasons | sort -u | wc -l" and "cut -f1 seasons | sort | uniq -c | wc -l ?

• 4, 3
• 3, 12
• 5, 10
• 12, 4
• 4, 4
• 12, 20
• 12, 3
• 4, 12
• 3, 4
• 12, 12
• 4, 6

Q8. Your current working directory is named “Plants”. Its subdirectory “apple” contains the files “apple.genome”, “apple.samples” and “apple.genes”. What would be the result of the command rmdir apple?

• All files containing the string “apple” in their names will be removed
• The command will have no effect, since the directory is not empty
• None of these choices
• The “apple” directory and all of its content will be removed

Q9. Suppose that you have two files, A and B, containing experiment data:

File A: File B:

geneA + geneB +
geneB + geneC +
geneC –

What would be the sequence of outputs for the commands:

(1) comm -3 A B | wc –l
(2) comm -1 -3 A B | wc –l
(3) comm -2 A B | wc –l

• 1,1,4
• 1,2,4
• 1,1,3
• 3, 1, 3

Q10. The current working directory contains four subdirectories named “apple”, “pear”, “peach” and “strawberry”, each with the following files: “genome”, “genes” and “samples”. Which of the following commands would extract the top line from all of the “genes” files?

• head -1 */genes
• more /gs | tail -1
• cat */genes | head -1
• ls */genes

Quiz 2: Module 1 Exam

Q1. How many chromosomes are there in the genome?

3

Q2. How many genes?

5453

Q3. How many transcript variants?

5456

Q4. How many genes have a single splice variant?

5450

Q5. How may genes have 2 or more splice variants?

3

Q6. How many genes are there on the ‘+’ strand?

2662

Q7. How many genes are there on the ‘-’ strand?

2791

Q8. How many genes are there on chromosome chr1?

1624

Q9. How many genes are there on each chromosome chr2?

2058

Q10. How many genes are there on each chromosome chr3?

1771

Q11. How many transcripts are there on chr1?

1625

Q12. How many transcripts are there on chr2?

2059

Q13. How many transcripts are there on chr3?

1772

Q14. How many genes are in common between condition A and condition B?

2410

Q15. How many genes are specific to condition A?

1205

Q16. How many genes are specific to condition B?

1243

Q17. How many genes are in common to all three conditions?

1608

Week 2

Quiz 1: Module 2 Quiz

Q1. Which of the following strings cannot denote a DNA sequence:

• GACTACGAGCGATTTACAGCGAGCATT
• MASLLRG
• GGTACGAGC
• TACNATTCG

Q2. How many lines does it take to specify:

i) one fasta sequence? and ii) one fastq sequence?

Select the best answer.

• Fasta – 1 line; fastq – 2 lines
• Fasta – a fasta header followed by any number of sequence lines; fastq – 4 lines
• Fasta – 2 lines; fastq – 2 lines
• Fasta – 100 lines; fastq – 4 lines

Q3. Which of the following is incorrect:

• BEDtools can be used to align sequences to the genome.
• The length of a read with CIGAR 51M1D24M is 75 bp.
• ‘SRA” stands for “Short Read Archive”, an NCBI database that stores short read sequences.
• An unmapped read can be represented as a SAM record with a ‘*’ in column 7.

Q4. Which of the following is NOT an alignment operation:

• Cut and paste
• Hard clipping
• Padding
• Soft clipping

Q5. What is the minimum number of columns that are sufficient to specify a BED format?

• 1
• 2
• 3
• 4

Q6. Which of the following represents the most accurate conversion into BED of the GTF record:

chr1 CLASS exon 516 811 100 + . gene_id “genA”; transcript_id “genA.1”;chr1 CLASS exon 1001 1115 100 + . gene_id “genA”; transcript_id “genA.1”;chr1 CLASS exon 3010 3312 100 + . gene_id “genA”; transcript_id “genA.1”```

chr1 515 811 genA 100 + . 800 811 0 1 296 0

chr1 515 3312 genA.1 100 + 515 3312 0 3 296,115,303 0,485,2494

chr1 516 3312 genA.1 100 + 800 900 0 3 296,115,303 0,485,2494

chr1 516 3312 genA + 516 3312 0 2 296,303 0,2494

Q7. Determine the number of genes, transcripts, exons per transcript, gene orientation (strand), and the length of 5’ most exon(s) from the GTF snippet below. Select the correct answer.

chr1 HAVANA gene 3205901 3671498 . - . gene_id "MUSG51951.5";chr1 HAVANA transcript 3205901 3216344 . - . gene_id "MUSG51951.5"; transcript_id "MUST162897.1";chr1 HAVANA exon 3213609 3216344 . - . gene_id "MUSG51951.5"; transcript_id "MUST162897.1”;chr1 HAVANA exon 3205901 3207317 . - . gene_id "MUSG51951.5"; transcript_id "MUST162897.1chr1 HAVANA transcript 3206523 3215632 . - . gene_id "MUSG51951.5"; transcript_id "MUST159265.1”;chr1 HAVANA exon 3213439 3215632 . - . gene_id "MUSG51

• Genes: 1; Transcripts: 2; Exons: 2,2; Strand: -; Length of 5’ exon(s): 2736, 2194.
• Genes: 1; Transcripts: 2; Exons: 2,2; Strand: -; Length of 5’ exon(s): 2735, 2193.
• Genes: 1; Transcripts: 1; Exons: 4; Strand: -; Length of 5’ exon(s): 2736.
• Genes: 1; Transcripts: 4; Exons: 1,1,1,1; Strand: -; Length of 5’ exon(s): 2736, 1417,2194,795.

Q8. Which of the following is FALSE for the following read alignments:

R1 83 chr12 9232390 255 50M = 9232180 0ATGGCAGAGCCTAATATGTCTCCTAGAGAATGGGAGAGATGGGAAGTCAT HGHHHHHHHHHHHHHHHHHHHHHHHHHHIGIIIIHHHHHHHHHHHGHHFH NM:i:0 NH:i:1 HI:i:0R2 97 chr12 9232391 255 28M278N22M = 92425290 TGGCAGAGCCTAATATGTCTCCCAAAACTGAGACAGAAGCTCGGGCAGAT D>DDDHHHHHHHHHHIHIHHHHHIHHHHIGFFGGGHHHHHHHHHHFB.F NM:i:4 NH:i:3 HI:i:0 XS:A:+ NS:i:2R3 77 * 0 0 0 * * 0 0 CTGATATGAGGAAAGAGGATTGCTTAAGCCCAGGAGGTAGAGGCTGTACC @@@FFDFFHFFHHJJJJIJEGFGIGHHIHIIIIGCDE?D?FGGCBHDGGG

• R2 has an exact match to the genome.
• R2 maps in 3 places within the genome.
• R1 has an exact match to the genome.
• R1, R2 and R3 all have length 50.

Q9. For the alignment below, which statements are FALSE? The binary encoding for 97 is 972 = 0000 0110 00012. Select all answers that apply.

R2 97 chr12 9232391 255 28M278N22M = 92425290 TGGCAGAGCCTAATATGTCTCCCAAAACTGAGACAGAAGCTCGGGCAGAT D>DDDHHHHHHHHHHIHIHHHHHIHHHHIGFFGGGHHHHHHHHHHFB.F NM:i:4 XS:A:+ NS:i:2

• The read matches to the genome with 4 differences.
• The alignment passes quality checks.
• Both the read and its mate are mapped.
• The alignment represents a potential PCR or optical duplicate.
• The two mates are identical in sequence.
• The sequence of the read’s mate is reverse complemented in its alignment.

Q10. Files ‘A.bed’ and ‘B.bed’ contain the following sets of intervals:

File A File B
chr1 100 400 chr1 300 500
chr1 1000 1400 chr1 900 1600
chr1 2000 2400 chr12 2000 2200
What would be the answers for the following sequence of commands:
bedtools intersect –wao –a A.bed –b B.bed | sort –u | wc -l
bedtools intersect –wo –a A.bed –b B.bed | cut –f1-3 | sort –u | wc -l

• 3, 2, 2
• 3, 6, 3
• 3, 6, 6
• 3, 2, 6

Quiz 2: Module 2 Exam

Q1. How many alignments does the set contain?

221372

Q2. How many alignments show the read’s mate unmapped?

65521

Q3. How many alignments contain a deletion (D)?

2451

Q4. How many alignments show the read’s mate mapped to the same chromosome?

150913

Q5. How many alignments are spliced?

0

Q6. How many alignments does the set contain?

7081

Q7. How many alignments show the read’s mate unmapped?

1983

Q8. How many alignments contain a deletion (D)?

31

Q9. How many alignments show the read’s mate mapped to the same chromosome?

4670

Q10. How many alignments are spliced?

0

Q11. How many sequences are in the genome file?

7

Q12. What is the length of the first sequence in the genome file?

29923332

Q13. What alignment tool was used?

stampy

Q14. What is the read identifier (name) for the first alignment?

GAII05_0002:1:113:7822:3886#0

Q15. What is the start position of this read’s mate on the genome? Give this as ‘chrom:pos’ if the read was mapped, or ‘*” if unmapped.

Chr3:11700332

Q16. How many overlaps (each overlap is reported on one line) are reported?

3101

Q17. How many of these are 10 bases or longer?

2899

Q18. How many alignments overlap the annotations?

3101

Q19. Conversely, how many exons have reads mapped to them?

21

Q20. If you were to convert the transcript annotations in the file “athal_wu_0_A_annot.gtf” into BED format, how many BED records would be generated?

4

Week 3

Quiz 1: Module 3 Quiz

Q1. Which of the following statements is FALSE:

• SNP refers to a Single Non-defined Polymorhism
• SNVs encompass single nucleotide insertions, deletions and substitutions.
• SNV refers to a Single Nucleotide Variant.
• Structural variants include block deletions and insertions, among others.

Q2. Which of the following statements is FALSE:

• The BCF format is a binary compressed version of VCF.
• The VCF format shows the changes in amino acid resulting from the nucleotide mutation, in column 3.
• The VCF INFO lines describe characteristics of the variant, included in column 8.
• VCF stands for Variant Call Format.

Q3. What program can be used to generate a list of candidate sites of variation in an exome data set:

• bedtools
• samtools
• bcftools

mkdir

Q4. In a comprehensive effort to study genome variation in a patient cohort, you sequence and call variants in the exome, whole genome shotgun and RNA-seq data from each patient. Which of the following is FALSE when comparing these three types of resources:

• Exome sequencing comprehensively captures variants in the 3’ and 5’ UTRs of genes.
• Exome sequencing can capture variants in a pre-defined set of coding exons and their immediate surrounding area.
• Exome sequencing cannot determine variants in novel polymorphic alternative splicing events.
• Exome sequencing captures fewer variants than whole genome sequencing.
• Whole genome sequencing can potentially detect all variants that can be found with either exome sequencing or RNA-seq.

Q5. Which of the following options can be used to allow bowtie2 to generate partial alignments?

• -D
• –local
• –sensitive
• –ignore-quals

Q6. Select the correct interpretation for the snippet of ‘mpileup’ output below.

Chr3 11700316 C 8 .$……. 8C@C;CB3
Chr3 11951491 G 16 AAAA,……aA..A C2@2BCBCCCAC2CC4

Both sites show potential variation;

the alternate letter for site 1 is $, and for site 2 is A;

site 1 has 8 supporting reads, and site 2 has 16

Both sites show potential variation

the alternate letter for site 1 is $, and for site 2 is G;

site 1 has 8 supporting reads, and site 2 has 16

Both sites show potential variation;

the alternate letter for site 1 is C, and for site 2 is G;

site 1 has 8 supporting reads, and site 2 has 7

Only site 2 shows potential variation;

 the alternate letter for site 2 is A;

 site 1 has 8 supporting reads, and site 2 has 16

Q7. Given the set of variants described in the VCF excerpt below, which of the following is FALSE?

INFO=

INFO=

FORMAT=

FORMAT=

Chr3 11966312 . G A 15.9 . DP=5;MQ=15 GT:PL 1/1:43,9,0Chr3 11972108 . TAAAA TAAA 32.8 . INDEL;IDV=7;IMF=0.636364;DP=11;MQ=22 GT:PL 0/1:66,0,2Chr3 13792328 rs145271872 G T 5.5 . DP=1;MQ=40 GT

• The alternate allele for variant 3 is T
• The quality values for the three calls are 15.9, 32.8 and 5.5
• The sample contains only the alternate allele for variant 3
• The alternate allele for variant 1 is A

Q8. What does the following code do:

bowtie2 –x species/species –U in.fastq | grep –v “^@” | cut –f3 | sort | uniq –c

Run bowtie2 with a set of single-end reads, reporting the top 5 alignments for a read;

then determine the number of reads mapped reverse complemented

Run bowtie2 with a set of single-end reads, allowing for local matches;

then determine the number of matches with unmapped mates

Run bowtie2 with a set of single-end reads, reporting the best alignment only;

then determine the number of matches on each genomic sequence

Run bowtie2 with a set of single-end reads, allowing for local matches;

then determine the number of exact matches on each genomic sequence

Q9. What does the following snippet of code do NOT do:

samtools mpileup –O –f genome.fa in.bam | cut –f7

• Report in the intermediate mpileup output the qualities of all read bases aligned at that position
• Require a sorted BAM file
• Produce a 7-column intermediate mpileup file that is piped to ‘cut’
• Report an empty column

Q10. What does the following code do NOT do:

bcftools call –v –c –O z –o out.vcf.gz in.vcf.gz

• Call variants in a single sample
• Report output in compressed VCF format
• Skip indels
• Report variant sites only

Quiz 2: Module 3 Exam

Q1. How many sequences were in the genome?

7

Q2. What was the name of the third sequence in the genome file? Give the name only, without the “>” sign.

Chr3

Q3. What was the name of the last sequence in the genome file? Give the name only, without the “>” sign.

mitochondria

Q4. How many index files did the operation create?

6

Q5. What is the 3-character extension for the index files created?

bt2

Q6. How many reads were in the original fastq file?

147354

Q7. How many matches (alignments) were reported for the original (full-match) setting? Exclude lines in the file containing unmapped reads.

137719

Q8. How many matches (alignments) were reported with the local-match setting? Exclude lines in the file containing unmapped reads.

141044

Q9. How many reads were mapped in the scenario in Question 7?

137719

Q10. How many reads were mapped in the scenario in Question 8?

141044

Q11. How many reads had multiple matches in the scenario in Question 7? You can find this in the bowtie2 summary; note that by default bowtie2 only reports the best match for each read.​

43939

Q12. How many reads had multiple matches in the scenario in Question 8? Use the format above. You can find this in the bowtie2 summary; note that by default bowtie2 only reports the best match for each read.​

56105

Q13. How many alignments contained insertions and/or deletions, in the scenario in Question 7?

2782

Q14. How many alignments contained insertions and/or deletions, in the scenario in Question 8?

2614

QQ15. How many entries were reported for Chr3?

360295

Q16. How many entries have ‘A’ as the corresponding genome letter?

1150985

Q17. How many entries have exactly 20 supporting reads (read depth)?

1816

Q18. How many entries represent indels?

1972

Q19. How many entries are reported for position 175672 on Chr1?

2

Q20. How many variants are called on Chr3?

398

Q21. How many variants represent an A->T SNP? If useful, you can use ‘grep –P’ to allow tabular spaces in the search term.

392

Q22. How many entries are indels?

320

Q23. How many entries have precisely 20 supporting reads (read depth)?

2

Q24. What type of variant (i.e., SNP or INDEL) is called at position 11937923 on Chr3?

SNP

Week 4

Quiz 1: Module 4 Quiz

Q1. Which of the following is FALSE:

• A human gene can express at most 12 splice variants.
• The coding region with a protein-coding gene is used as the template for forming a protein.
• A codon is a nucleotide triplet that is translated into one amino acid.
• Alternative splicing is a common phenomenon in both animals and plants.

Q2. Which of the following is FALSE about the organization of a eukaryotic gene:

• Some eukaryotic gene transcripts can consist of a single exon.
• The number of introns in a transcript is one less than the number of exons.
• The length of an intron cannot be a multiple of 3.
• Genes that have only one exon are not alternatively spliced.

Q3. What programs could you use to align RNA-seq reads to: i) a reference genome, and ii) a transcript database?

• bowtie, bwa
• tophat, bwa
• bowtie, cufflinks
• bowtie, bcftools

Q4. Which of the following is FALSE:

• RNA-seq analyses can reveal known genes and their splice variants, as well as novel genes.
• RNA-seq can be used to quantify the expression levels of proteins.
• ‘Transfrag’ stands for ‘transcript fragments’, a reference to the fact than transcript assemblers cannot always reconstruct full-length splice variants.

Spliced reads can be used to determine the introns in a gene.

Q5. What programs could be used to: i) assemble transcripts from RNA-seq reads, and ii) identify potentially novel transcripts and genes?

• cufflinks, cufflinks
• tophat, cufflinks
• cufflinks, cuffmerge
• cufflinks, cuffcompare

Q6. Which of the following is FALSE about the gene annotations in the following GTF snippet:

chr1 MGF gene 3413609 3671498 . - . gene_id "MG051951";chr1 MGF transcript 3413609 3416344 . - .gene_id "MG051951"; transcript_id "MT162897";chr1 MGF exon 3413609 3416344 . - . gene_id "MG051951"; transcript_id "MT162897";chr1 MGF transcript 3421702 3671498 . - . gene_id "MG051951"; transcript_id "MT070533";chr1 MGF exon 3670552 3671498 . - . gene_id "MG051951"; transcript_id "MT070533";chr1 MGF CDS 3670552 3671348 . - 0 gene_id "MG051951"; transcript_id "MT070533";chr1 MGF exon 342170

• Both exons of MT70533 contain both coding and non-coding sequences.
• Transcript MT070533 is designated as coding.
• Transcript MT070533 has 4 exons.
• Gene MG051951 is protein-coding.

Q7. What does the following code NOT do:

BWT2IDX=/home/me/genomes/hg20/hg20
ANNOT=/home/me/genomes/hg20/myannot.gtf
ANNOTIDX=/home/me/genomes/hg20/myannot/myannot
mkdir -p /home/me/SRR100000
tophat2 -o /home/me/SRR100000 -p 10 --max-multihits 10 \
-r 26 –-mate-std-dev 25 \
-a 6 \
-G $ANNOT –-transcriptome-index $ANNOTIDX \

• Report spliced reads with at most 6 mismatches in the anchor site
• Create the output in the /home/me/SRR100000 directory
• Run multi-threaded, with 10 threads
• Report only reads with 10 or fewer alignments on the genome

Q8. What does the following code NOT do:

TOPHATDIR=/home/florea/Tophat/
mkdir –p Test1
cd Test1
ln –s $TOPHATDIR/accepted_hits.bam .
cufflinks -L Test1 -p 8 –j 0.10 –F 0.05 accepted_hits.bam

• Use the default reference transcript annotation to guide assembly
• Create the subdirectory Test1, if it does not already exist
• After creating the directory Test1, make it the current directory
• Generate output in the ./Test1 subdirectory

Q9. Which of the following is NOT described in the following summary file produced by tophat:

Left reads:Input : 60586968Mapped : 58163843 (96.0% of input)of these: 6832240 (11.7%) have multiple alignments (359075 have >10)Right reads:Input : 60586968Mapped : 56969290 (94.0% of input)of these: 6668479 (11.7%) have multiple alignments (358573 have >10)95.0% overall read mapping rate.

• The reads were 100 bp long
• Tophat was run with paired-end data
• There were 121,173,936 reads total in the input set
• 96.0% of the mate 1 reads could be mapped

Q10. Which of the following is NOT TRUE about the output below, obtained from a cuffdiff differential expression analysis:

XLOC_000002 XLOC_000002 AT1G01020 1:5927-8737 q1 q2 OK 1.13032 3.48406 1.62404 0.694576 0.5277 0.998846 noXLOC_000004 XLOC_000004 AT1G01073 1:44676-44787 q1 q2 NOTEST 0 0 0 0 1 1 noXLOC_000042 XLOC_000042 AT1G01580 1:209394-213041 q1 q2 OK 1.59512 0 -inf nan 5e-05 0.0096703 yes

• Locus XLOC_000004 corresponds to gene AT1G01073
• There are not enough alignments for testing for differential expression at locus XLOC_000004
• There are too many alignments for testing for differential expression at locus XLOC_000004
• Locus XLOC_000042 corresponds to gene AT1G01580

Quiz 2: Module 4 Exam

Q1. How many alignments were produced for the ‘Day8’ RNA-seq data set?

63845

Q2. How many alignments were produced for the ‘Day16’ RNA-seq data set?

58398

Q3. How many reads were mapped in ‘Day8’ RNA-seq data set?

63489

Q4. How many reads were mapped in ‘Day16’ RNA-seq data set?

57951

Q5. How many reads were uniquely aligned in ‘Day8’ RNA-seq data set?

63133

Q6. How many reads were uniquely aligned in ‘Day16’ RNA-seq data set?

57504

Q7. How many spliced alignments were reported for ‘Day8’ RNA-seq data set?

8596

Q8. How many spliced alignments were reported for ‘Day16’ RNA-seq data set?

10695

Q9. How many reads were left unmapped from ‘Day8’ RNA-seq data set?

84

Q10. How many reads were left unmapped from ‘Day16’ RNA-seq data set?

34

Q11. How many genes were generated by cufflinks for Day8?

186

Q12. How many genes were generated by cufflinks for Day16?

80

Q13. How many transcripts were reported for Day8?

192

Q14. How many transcripts were reported for Day16?

92

Q15. How many single transcript genes were produced for Day8?

180

Q16. How many single transcript genes were produced for Day16?

69

Q17. How many single-exon transcripts were in the Day8 set?

119

Q18. How many single-exon transcripts were in the Day16 set?

24

Q19. How many multi-exon transcripts were in the Day8 set?

73

Q20. How many multi-exon transcripts were in the Day16 set?

68

Q21. How many cufflinks transcripts fully reconstruct annotation transcripts in Day8?

16

Q22. How many cufflinks transcripts fully reconstruct annotation transcripts in Day16?

36

Q23. How many splice variants does the gene AT4G20240 have in the Day8 sample?

2

Q24. How many splice variants does the gene AT4G20240 have in the Day16 sample?

0

Q25. How many cufflinks transcripts are partial reconstructions of reference transcripts (‘contained’)? (Day8)

133

Q26. How many cufflinks transcripts are partial reconstructions of reference transcripts (‘contained’)? (Day16)

21

Q27. How many cufflinks transcripts are novel splice variants of reference genes? (Day8)

14

Q28. How many cufflinks transcripts are novel splice variants of reference genes? (Day16)

22

Q29. How many cufflinks transcripts were formed in the introns of reference genes? (Day8)

4

Q30. How many cufflinks transcripts were formed in the introns of reference genes? (Day16)

1

Q31. How many genes (loci) were reported in the merged.gtf file?

129

Q32. How many transcripts?

200

Q33. How many genes total were included in the gene expression report from cuffdiff?

129

Q34. How many genes were detected as differentially expressed?

4

Q35. How many transcripts were differentially expressed between the two samples?

5

Conclusion

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