- About The Coursera
- About Command Line Tools for Genomic Data Science Course
- Command Line Tools for Genomic Data Science Quiz Answers
- Week 1 Quiz Answers
- Week 2
- Week 3
- Week 4
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Here, you will find Command Line Tools for Genomic Data Science Exam Answers in Bold Color which are given below.
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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
- 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?
Q2. Which of the following commands can be using to compress the content of a file?
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
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
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
- 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 +
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
- 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?
Q2. How many genes?
Q3. How many transcript variants?
Q4. How many genes have a single splice variant?
Q5. How may genes have 2 or more splice variants?
Q6. How many genes are there on the ‘+’ strand?
Q7. How many genes are there on the ‘-’ strand?
Q8. How many genes are there on chromosome chr1?
Q9. How many genes are there on each chromosome chr2?
Q10. How many genes are there on each chromosome chr3?
Q11. How many transcripts are there on chr1?
Q12. How many transcripts are there on chr2?
Q13. How many transcripts are there on chr3?
Q14. How many genes are in common between condition A and condition B?
Q15. How many genes are specific to condition A?
Q16. How many genes are specific to condition B?
Q17. How many genes are in common to all three conditions?
Quiz 1: Module 2 Quiz
Q1. Which of the following strings cannot denote a DNA sequence:
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
- Soft clipping
Q5. What is the minimum number of columns that are sufficient to specify a BED format?
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?
Q2. How many alignments show the read’s mate unmapped?
Q3. How many alignments contain a deletion (D)?
Q4. How many alignments show the read’s mate mapped to the same chromosome?
Q5. How many alignments are spliced?
Q6. How many alignments does the set contain?
Q7. How many alignments show the read’s mate unmapped?
Q8. How many alignments contain a deletion (D)?
Q9. How many alignments show the read’s mate mapped to the same chromosome?
Q10. How many alignments are spliced?
Q11. How many sequences are in the genome file?
Q12. What is the length of the first sequence in the genome file?
Q13. What alignment tool was used?
Q14. What is the read identifier (name) for the first alignment?
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.
Q16. How many overlaps (each overlap is reported on one line) are reported?
Q17. How many of these are 10 bases or longer?
Q18. How many alignments overlap the annotations?
Q19. Conversely, how many exons have reads mapped to them?
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?
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:
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?
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?
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?
Q2. What was the name of the third sequence in the genome file? Give the name only, without the “>” sign.
Q3. What was the name of the last sequence in the genome file? Give the name only, without the “>” sign.
Q4. How many index files did the operation create?
Q5. What is the 3-character extension for the index files created?
Q6. How many reads were in the original fastq file?
Q7. How many matches (alignments) were reported for the original (full-match) setting? Exclude lines in the file containing unmapped reads.
Q8. How many matches (alignments) were reported with the local-match setting? Exclude lines in the file containing unmapped reads.
Q9. How many reads were mapped in the scenario in Question 7?
Q10. How many reads were mapped in the scenario in Question 8?
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.
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.
Q13. How many alignments contained insertions and/or deletions, in the scenario in Question 7?
Q14. How many alignments contained insertions and/or deletions, in the scenario in Question 8?
QQ15. How many entries were reported for Chr3?
Q16. How many entries have ‘A’ as the corresponding genome letter?
Q17. How many entries have exactly 20 supporting reads (read depth)?
Q18. How many entries represent indels?
Q19. How many entries are reported for position 175672 on Chr1?
Q20. How many variants are called on Chr3?
Q21. How many variants represent an A->T SNP? If useful, you can use ‘grep –P’ to allow tabular spaces in the search term.
Q22. How many entries are indels?
Q23. How many entries have precisely 20 supporting reads (read depth)?
Q24. What type of variant (i.e., SNP or INDEL) is called at position 11937923 on Chr3?
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?
Q2. How many alignments were produced for the ‘Day16’ RNA-seq data set?
Q3. How many reads were mapped in ‘Day8’ RNA-seq data set?
Q4. How many reads were mapped in ‘Day16’ RNA-seq data set?
Q5. How many reads were uniquely aligned in ‘Day8’ RNA-seq data set?
Q6. How many reads were uniquely aligned in ‘Day16’ RNA-seq data set?
Q7. How many spliced alignments were reported for ‘Day8’ RNA-seq data set?
Q8. How many spliced alignments were reported for ‘Day16’ RNA-seq data set?
Q9. How many reads were left unmapped from ‘Day8’ RNA-seq data set?
Q10. How many reads were left unmapped from ‘Day16’ RNA-seq data set?
Q11. How many genes were generated by cufflinks for Day8?
Q12. How many genes were generated by cufflinks for Day16?
Q13. How many transcripts were reported for Day8?
Q14. How many transcripts were reported for Day16?
Q15. How many single transcript genes were produced for Day8?
Q16. How many single transcript genes were produced for Day16?
Q17. How many single-exon transcripts were in the Day8 set?
Q18. How many single-exon transcripts were in the Day16 set?
Q19. How many multi-exon transcripts were in the Day8 set?
Q20. How many multi-exon transcripts were in the Day16 set?
Q21. How many cufflinks transcripts fully reconstruct annotation transcripts in Day8?
Q22. How many cufflinks transcripts fully reconstruct annotation transcripts in Day16?
Q23. How many splice variants does the gene AT4G20240 have in the Day8 sample?
Q24. How many splice variants does the gene AT4G20240 have in the Day16 sample?
Q25. How many cufflinks transcripts are partial reconstructions of reference transcripts (‘contained’)? (Day8)
Q26. How many cufflinks transcripts are partial reconstructions of reference transcripts (‘contained’)? (Day16)
Q27. How many cufflinks transcripts are novel splice variants of reference genes? (Day8)
Q28. How many cufflinks transcripts are novel splice variants of reference genes? (Day16)
Q29. How many cufflinks transcripts were formed in the introns of reference genes? (Day8)
Q30. How many cufflinks transcripts were formed in the introns of reference genes? (Day16)
Q31. How many genes (loci) were reported in the merged.gtf file?
Q32. How many transcripts?
Q33. How many genes total were included in the gene expression report from cuffdiff?
Q34. How many genes were detected as differentially expressed?
Q35. How many transcripts were differentially expressed between the two samples?
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