Chapter 4 Read Mapping
last updated: 2023-10-27
As usual, make sure we have the right packages for this exercise
if (!require("pacman")) install.packages("pacman"); library(pacman)
# let's load all of the files we were using and want to have again today
p_load("tidyverse", "knitr", "readr",
"pander", "BiocManager",
"dplyr", "stringr")
# We also need the Bioconductor packages "Rsubread" for today's activity.
p_load("Rsubread")Previously, we filtered and trimmed our raw fastq files. They should be in the folder below, unless you chose a different place to store them.
dir_trimmed.fq_files <- "~/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp"
trimmed_fastq_files <- list.files(path = dir_trimmed.fq_files,
pattern = ".fastq.gz$",
full.names = TRUE)
trimmed_fastq_files## [1] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_ETOH_REP1_R1.fastq.gz"
## [2] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_ETOH_REP2_R1.fastq.gz"
## [3] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_ETOH_REP3_R1.fastq.gz"
## [4] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_ETOH_REP4_R1.fastq.gz"
## [5] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_MOCK_REP1_R1.fastq.gz"
## [6] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_MOCK_REP2_R1.fastq.gz"
## [7] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_MOCK_REP3_R1.fastq.gz"
## [8] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_MOCK_REP4_R1.fastq.gz"
## [9] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_ETOH_REP1_R1.fastq.gz"
## [10] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_ETOH_REP2_R1.fastq.gz"
## [11] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_ETOH_REP3_R1.fastq.gz"
## [12] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_ETOH_REP4_R1.fastq.gz"
## [13] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_MOCK_REP1_R1.fastq.gz"
## [14] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_MOCK_REP2_R1.fastq.gz"
## [15] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_MOCK_REP3_R1.fastq.gz"
## [16] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_MOCK_REP4_R1.fastq.gz"You should see the full paths to all 16 trimmed fastq files that we will be mapping to the reference genome today.
4.1 Alignment
Read sequences are stored in compressed (gzipped) FASTQ files. Before the differential expression analysis can proceed, these reads must be aligned to the yeast genome and counted into annotated genes. This can be achieved with functions in the Rsubread package.
4.2 Retrieve the genome
We will use a bash code chunk to download the latest genome
# Define the destination file path
# You can change this file path to the path you want your data to go, or leave it.
REF_DIR="/Users/$USER/Desktop/Genomic_Data_Analysis/Reference"
# make that directory if it doesn't already
mkdir -p $REF_DIR
# Define the URL of reference genome
# (latest from ensembl)
url="ftp://ftp.ensembl.org/pub/release-110/fasta/saccharomyces_cerevisiae/dna/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa.gz"
# Check if the file already exists at the destination location
if [ ! -f "$REF_DIR/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa.gz" ]; then
echo "Reference genome not found, downloading..."
# If the file does not exist, download it using curl
curl -o "$REF_DIR/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa.gz" "$url"
echo "Downloading finished"
else
echo "File already exists at $REF_DIR Skipping download."
fi## File already exists at /Users/clstacy/Desktop/Genomic_Data_Analysis/Reference Skipping download.4.3 Build Rsubread Index
The first step in performing the alignment is to build an index. In order to build an index you need to have the fasta file (.fa), which can be downloaded from the UCSC genome browser. This may take several minutes to run. Building the full index using the whole genome usually takes about 30 minutes to an hr on a server for larger Eukaryotic genomes. Because yeast has a relatively small genome size, we are able to build the full index in class.
library(Rsubread)
# Set path of the reference fasta file
reference_genome = path.expand("~/Desktop/Genomic_Data_Analysis/Reference/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa.gz")
index_reference_genome = path.expand("~/Desktop/Genomic_Data_Analysis/Reference/index_rsubread_Saccharomyces_cerevisiae.R64-1-1")
# build the index
buildindex(basename=index_reference_genome, reference=reference_genome)##
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## Rsubread 2.14.2
##
## //================================= setting ==================================\\
## || ||
## || Index name : index_rsubread_Saccharomyces_cerevisiae.R6 ... ||
## || Index space : base space ||
## || Index split : no-split ||
## || Repeat threshold : 100 repeats ||
## || Gapped index : no ||
## || ||
## || Free / total memory : 1.4GB / 8.0GB ||
## || ||
## || Input files : 1 file in total ||
## || o Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa.gz ||
## || ||
## || ||
## || WARNING: the free memory is lower than 3.0GB. ||
## || the program may run very slow or crash. ||
## || ||
## \\============================================================================//
##
## //================================= Running ==================================\\
## || ||
## || Check the integrity of provided reference sequences ... ||
## || No format issues were found ||
## || Scan uninformative subreads in reference sequences ... ||
## || 11 uninformative subreads were found. ||
## || These subreads were excluded from index building. ||
## || Estimate the index size... ||
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## || WARNING: available memory is lower than 3.0 GB. ||
## || The program may run very slow. ||
## || Build a gapped index and/or split index into blocks to reduce memory use. ||
## || ||
## || Build the index... ||
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## || Total running time: 1.4 minutes. ||
## ||Index /Users/clstacy/Desktop/Genomic_Data_Analysis/Reference/index_rsu ... ||
## || ||
## \\============================================================================//We can see the arguments available with the align function from the Rsubread package
## function (index, readfile1, readfile2 = NULL, type = "rna", input_format = "gzFASTQ",
## output_format = "BAM", output_file = paste(readfile1, "subread",
## output_format, sep = "."), phredOffset = 33, nsubreads = 10,
## TH1 = 3, TH2 = 1, maxMismatches = 3, unique = FALSE, nBestLocations = 1,
## indels = 5, complexIndels = FALSE, nTrim5 = 0, nTrim3 = 0,
## minFragLength = 50, maxFragLength = 600, PE_orientation = "fr",
## nthreads = 1, readGroupID = NULL, readGroup = NULL, keepReadOrder = FALSE,
## sortReadsByCoordinates = FALSE, color2base = FALSE, DP_GapOpenPenalty = -1,
## DP_GapExtPenalty = 0, DP_MismatchPenalty = 0, DP_MatchScore = 2,
## detectSV = FALSE, useAnnotation = FALSE, annot.inbuilt = "mm39",
## annot.ext = NULL, isGTF = FALSE, GTF.featureType = "exon",
## GTF.attrType = "gene_id", chrAliases = NULL)
## NULLThis process takes some time to finish.
# run the alignment on all of the trimmed_fastq_files
align(index=index_reference_genome,
readfile1=trimmed_fastq_files,
type = "rna",
input_format = "gzFASTQ",
output_format = "BAM",
unique = TRUE,
nBestLocations = 1,
sortReadsByCoordinates = TRUE,
nthreads=6
)The output of the alignment are bam corresponding to each fastq file.
We can get a summary of the proportion of reads that mapped to the reference genome using the propmapped function.
# create an object in R listing
bam_files <- list.files(path = dir_trimmed.fq_files, pattern = ".BAM$", full.names = TRUE)
bam_files## [1] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_ETOH_REP1_R1.fastq.gz.subread.BAM"
## [2] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_ETOH_REP2_R1.fastq.gz.subread.BAM"
## [3] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_ETOH_REP3_R1.fastq.gz.subread.BAM"
## [4] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_ETOH_REP4_R1.fastq.gz.subread.BAM"
## [5] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_MOCK_REP1_R1.fastq.gz.subread.BAM"
## [6] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_MOCK_REP2_R1.fastq.gz.subread.BAM"
## [7] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_MOCK_REP3_R1.fastq.gz.subread.BAM"
## [8] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_MSN24_MOCK_REP4_R1.fastq.gz.subread.BAM"
## [9] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_ETOH_REP1_R1.fastq.gz.subread.BAM"
## [10] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_ETOH_REP2_R1.fastq.gz.subread.BAM"
## [11] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_ETOH_REP3_R1.fastq.gz.subread.BAM"
## [12] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_ETOH_REP4_R1.fastq.gz.subread.BAM"
## [13] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_MOCK_REP1_R1.fastq.gz.subread.BAM"
## [14] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_MOCK_REP2_R1.fastq.gz.subread.BAM"
## [15] "/Users/clstacy/Desktop/Genomic_Data_Analysis/Data/Trimmed_rfastp/YPS606_WT_MOCK_REP3_R1.fastq.gz.subread.BAM"# find the proportion of reads that mapped for each sample
props <- propmapped(files=bam_files)
props |> print()## NumTotal NumMapped PropMapped
## YPS606_MSN24_ETOH_REP1_R1.fastq.gz.subread.BAM 0 0 NaN
## YPS606_MSN24_ETOH_REP2_R1.fastq.gz.subread.BAM 0 0 NaN
## YPS606_MSN24_ETOH_REP3_R1.fastq.gz.subread.BAM 199076 173693 0.872496
## YPS606_MSN24_ETOH_REP4_R1.fastq.gz.subread.BAM 205792 178785 0.868766
## YPS606_MSN24_MOCK_REP1_R1.fastq.gz.subread.BAM 167075 143114 0.856585
## YPS606_MSN24_MOCK_REP2_R1.fastq.gz.subread.BAM 169754 146302 0.861847
## YPS606_MSN24_MOCK_REP3_R1.fastq.gz.subread.BAM 210001 178664 0.850777
## YPS606_MSN24_MOCK_REP4_R1.fastq.gz.subread.BAM 208329 177749 0.853213
## YPS606_WT_ETOH_REP1_R1.fastq.gz.subread.BAM 181587 159200 0.876715
## YPS606_WT_ETOH_REP2_R1.fastq.gz.subread.BAM 201551 176904 0.877713
## YPS606_WT_ETOH_REP3_R1.fastq.gz.subread.BAM 214745 188499 0.877781
## YPS606_WT_ETOH_REP4_R1.fastq.gz.subread.BAM 187319 164152 0.876323
## YPS606_WT_MOCK_REP1_R1.fastq.gz.subread.BAM 223539 193407 0.865205
## YPS606_WT_MOCK_REP2_R1.fastq.gz.subread.BAM 187469 161251 0.860148
## YPS606_WT_MOCK_REP3_R1.fastq.gz.subread.BAM 0 0 NaN4.4 Pseudomapping with Salmon
Salmon is a widely used pseudomapper. It is not available to use in R, but we can use bash code chunks to run it in the same markdown document.
4.4.1 Create Conda Env
First, we need to create a new conda environment for salmon.
Depending on your computer, we might need to run this code in terminal.
## Warning, if you did not complete Working_with_Sequences.Rmd activity,
# your conda might not be set up correctly for this code.
# create an environment for our pseudomapping with Salmon
# this code is "extra" because it only creates env if not already existing.
if conda info --envs | grep -q salmon; then echo "environment 'salmon' already exists"; else CONDA_SUBDIR=osx-64 conda create -y -n salmon -c conda-forge -c bioconda salmon=1.10.0; fi
# the channel priority order above is needed to get a recent version via conda.
# see available conda environments
conda env list
# activate our QC environment
conda activate salmon
# make sure desired packages are working
which salmon
# help page for using salmon
salmon -h
# it's always good coding practice to deactivate
# a conda environment at the end of a chunk
conda deactivate4.4.2 Download transcriptome
To make an index for Salmon, we need transcript sequences in the FASTA format.
# Define the destination file path
# Be sure to change this file path to the path you want your data to go
REF_DIR="/Users/$USER/Desktop/Genomic_Data_Analysis/Reference"
# make that directory if it doesn't already
mkdir -p $REF_DIR
# Define the URL of reference transcriptome
# (latest from ensembl)
url="ftp://ftp.ensembl.org/pub/release-110/fasta/saccharomyces_cerevisiae/cdna/Saccharomyces_cerevisiae.R64-1-1.cdna.all.fa.gz"
# Check if the file already exists at the destination location
if [ ! -f "$REF_DIR/Saccharomyces_cerevisiae.R64-1-1.cdna.all.fa.gz" ]; then
echo "Reference transcriptome not found, downloading..."
# If the file does not exist, download it using curl
curl -o "$REF_DIR/Saccharomyces_cerevisiae.R64-1-1.cdna.all.fa.gz" "$url"
echo "Downloading finished"
else
echo "File already exists at $REF_DIR Skipping download."
fi## File already exists at /Users/clstacy/Desktop/Genomic_Data_Analysis/Reference Skipping download.4.4.3 Building the Salmon index
Salmon can index by using the command salmon index. A recent feature update to Salmon includes an option to map to decoys, we will use the entire genome as the decoy for our index, because the S. cerevesiae genome is small. You can read more at: https://salmon.readthedocs.io/en/latest/salmon.html#preparing-transcriptome-indices-mapping-based-mode.
# We need to set a variable for where the transcriptome file is
REF_DIR="/Users/$USER/Desktop/Genomic_Data_Analysis/Reference"
TRANSCRIPTOME="/Users/$USER/Desktop/Genomic_Data_Analysis/Reference/Saccharomyces_cerevisiae.R64-1-1.cdna.all.fa.gz"
GENOME="/Users/$USER/Desktop/Genomic_Data_Analysis/Reference/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa.gz"
# Activate conda salmon environment
conda activate salmon
# Run a script that generates a decoy.txt file from the genome we downloaded
grep "^>" <(gunzip -c $GENOME) | cut -d " " -f 1 > $REF_DIR/decoys.txt
sed -i.bak -e 's/>//g' $REF_DIR/decoys.txt
# Combine the transcriptome and genome into a single file for indexing
cat $TRANSCRIPTOME $GENOME > $REF_DIR/gentrome.fasta.gz
# We will use the yeast, but it needs to be indexed by salmon
salmon index -t $REF_DIR/gentrome.fasta.gz -d $REF_DIR/decoys.txt -p 4 -i $REF_DIR/index_salmon_Saccharomyces_cerevisiae.R64-1-1
conda deactivate## Version Info: This is the most recent version of salmon.
## [2023-10-26 12:12:52.539] [jLog] [info] building index
## out : /Users/clstacy/Desktop/Genomic_Data_Analysis/Reference/index_salmon_Saccharomyces_cerevisiae.R64-1-1
## [2023-10-26 12:12:52.540] [puff::index::jointLog] [info] Running fixFasta
##
## [Step 1 of 4] : counting k-mers
##
## [2023-10-26 12:12:53.052] [puff::index::jointLog] [warning] Removed 41 transcripts that were sequence duplicates of indexed transcripts.
## [2023-10-26 12:12:53.052] [puff::index::jointLog] [warning] If you wish to retain duplicate transcripts, please use the `--keepDuplicates` flag
## [2023-10-26 12:12:53.053] [puff::index::jointLog] [info] Replaced 0 non-ATCG nucleotides
## [2023-10-26 12:12:53.053] [puff::index::jointLog] [info] Clipped poly-A tails from 0 transcripts
## wrote 6588 cleaned references
## [2023-10-26 12:12:53.150] [puff::index::jointLog] [info] Filter size not provided; estimating from number of distinct k-mers
## [2023-10-26 12:12:53.603] [puff::index::jointLog] [info] ntHll estimated 11513300 distinct k-mers, setting filter size to 2^28
## Threads = 4
## Vertex length = 31
## Hash functions = 5
## Filter size = 268435456
## Capacity = 2
## Files:
## /Users/clstacy/Desktop/Genomic_Data_Analysis/Reference/index_salmon_Saccharomyces_cerevisiae.R64-1-1/ref_k31_fixed.fa
## --------------------------------------------------------------------------------
## Round 0, 0:268435456
## Pass Filling Filtering
## 1 2 3
## 2 1 0
## True junctions count = 20631
## False junctions count = 49701
## Hash table size = 70332
## Candidate marks count = 194448
## --------------------------------------------------------------------------------
## Reallocating bifurcations time: 0
## True marks count: 93214
## Edges construction time: 1
## --------------------------------------------------------------------------------
## Distinct junctions = 20631
##
## TwoPaCo::buildGraphMain:: allocated with scalable_malloc; freeing.
## TwoPaCo::buildGraphMain:: Calling scalable_allocation_command(TBBMALLOC_CLEAN_ALL_BUFFERS, 0);
## allowedIn: 14
## Max Junction ID: 20809
## seen.size():166481 kmerInfo.size():20810
## approximateContigTotalLength: 11070364
## counters for complex kmers:
## (prec>1 & succ>1)=327 | (succ>1 & isStart)=7 | (prec>1 & isEnd)=7 | (isStart & isEnd)=2
## contig count: 25029 element count: 12321058 complex nodes: 343
## # of ones in rank vector: 25028
## [2023-10-26 12:13:01.661] [puff::index::jointLog] [info] Starting the Pufferfish indexing by reading the GFA binary file.
## [2023-10-26 12:13:01.664] [puff::index::jointLog] [info] Setting the index/BinaryGfa directory /Users/clstacy/Desktop/Genomic_Data_Analysis/Reference/index_salmon_Saccharomyces_cerevisiae.R64-1-1
## size = 12321058
## -----------------------------------------
## | Loading contigs | Time = 5.9218 ms
## -----------------------------------------
## size = 12321058
## -----------------------------------------
## | Loading contig boundaries | Time = 3.1299 ms
## -----------------------------------------
## Number of ones: 25028
## Number of ones per inventory item: 512
## Inventory entries filled: 49
## 25028
## [2023-10-26 12:13:01.699] [puff::index::jointLog] [info] Done wrapping the rank vector with a rank9sel structure.
## [2023-10-26 12:13:01.700] [puff::index::jointLog] [info] contig count for validation: 25,028
## [2023-10-26 12:13:01.708] [puff::index::jointLog] [info] Total # of Contigs : 25,028
## [2023-10-26 12:13:01.708] [puff::index::jointLog] [info] Total # of numerical Contigs : 25,028
## [2023-10-26 12:13:01.708] [puff::index::jointLog] [info] Total # of contig vec entries: 88,496
## [2023-10-26 12:13:01.708] [puff::index::jointLog] [info] bits per offset entry 17
## [2023-10-26 12:13:01.709] [puff::index::jointLog] [info] Done constructing the contig vector. 25029
## [2023-10-26 12:13:01.721] [puff::index::jointLog] [info] # segments = 25,028
## [2023-10-26 12:13:01.721] [puff::index::jointLog] [info] total length = 12,321,058
## [2023-10-26 12:13:01.723] [puff::index::jointLog] [info] Reading the reference files ...
## [2023-10-26 12:13:01.849] [puff::index::jointLog] [info] positional integer width = 24
## [2023-10-26 12:13:01.849] [puff::index::jointLog] [info] seqSize = 12,321,058
## [2023-10-26 12:13:01.849] [puff::index::jointLog] [info] rankSize = 12,321,058
## [2023-10-26 12:13:01.849] [puff::index::jointLog] [info] edgeVecSize = 0
## [2023-10-26 12:13:01.849] [puff::index::jointLog] [info] num keys = 11,570,218
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## [2023-10-26 12:13:02.402] [puff::index::jointLog] [info] mphf size = 7.22767 MB
## [2023-10-26 12:13:02.411] [puff::index::jointLog] [info] chunk size = 3,080,265
## [2023-10-26 12:13:02.411] [puff::index::jointLog] [info] chunk 0 = [0, 3,080,282)
## [2023-10-26 12:13:02.411] [puff::index::jointLog] [info] chunk 1 = [3,080,282, 6,160,547)
## [2023-10-26 12:13:02.411] [puff::index::jointLog] [info] chunk 2 = [6,160,547, 9,240,812)
## [2023-10-26 12:13:02.411] [puff::index::jointLog] [info] chunk 3 = [9,240,812, 12,321,028)
## [2023-10-26 12:13:02.916] [puff::index::jointLog] [info] finished populating pos vector
## [2023-10-26 12:13:02.916] [puff::index::jointLog] [info] writing index components
## [2023-10-26 12:13:03.170] [puff::index::jointLog] [info] finished writing dense pufferfish index
## [2023-10-26 12:13:03.174] [jLog] [info] done building index
## for info, total work write each : 2.331 total work inram from level 3 : 4.322 total work raw : 25.000
## Bitarray 60630080 bits (100.00 %) (array + ranks )
## final hash 0 bits (0.00 %) (nb in final hash 0)Notice that we combined the fasta file of the transcriptome with the fasta file of the entire genome (in that order) into the gentrome.fasta.gz file which was then indexed.
Salmon is a pseudomapper, so it doesn’t create sam/bam files and is instead able to count directly from the fastq files. We will do the pseudomapping and counting all in one step in the next activity.
4.5 Questions
4.5.1 With Rsubread:
Question 1: Try aligning the fastq files allowing multi-mapping reads (set unique = FALSE), allowing for up to 6 “best” locations to be reported (nBestLocations = 6), and allow reads to be fractionally counted (fraction = TRUE). Specify the output file names (bam_files_multi) by substituting “.fastq.gz” with “.multi.bam” so we don’t overwrite our unique alignment bam files.
# Define the pattern and replacement
pattern <- "\\.fastq\\.gz$"
replacement <- "subread.multi.bam"
# Create the new file names
bam_files_multi <- gsub(pattern, replacement, trimmed_fastq_files)
# update this code to run with Rsubread multimapping, as described above.
align(index=index_reference_genome,
readfile1=trimmed_fastq_files,
output_file = ___________,
type = "rna",
input_format = "gzFASTQ",
output_format = "BAM",
unique = ____,
nBestLocations = ____,
nthreads=6
)Question 2: Look at the proportion of reads mapped and see if we get any more reads mapping by specifying a less stringent criteria.
4.5.2 With Salmon:
Question 3: What are the pros and cons of using Salmon vs subread for mapping reads?
Be sure to knit this file into a pdf or html file once you’re finished.
System information for reproducibility:
R version 4.3.1 (2023-06-16)
Platform: aarch64-apple-darwin20 (64-bit)
locale: en_US.UTF-8||en_US.UTF-8||en_US.UTF-8||C||en_US.UTF-8||en_US.UTF-8
attached base packages: stats4, stats, graphics, grDevices, utils, datasets, methods and base
other attached packages: Rsubread(v.2.14.2), ShortRead(v.1.58.0), GenomicAlignments(v.1.36.0), SummarizedExperiment(v.1.30.2), MatrixGenerics(v.1.12.3), matrixStats(v.1.0.0), Rsamtools(v.2.16.0), GenomicRanges(v.1.52.1), Biostrings(v.2.68.1), GenomeInfoDb(v.1.36.4), XVector(v.0.40.0), BiocParallel(v.1.34.2), Rfastp(v.1.10.0), org.Sc.sgd.db(v.3.17.0), AnnotationDbi(v.1.62.2), IRanges(v.2.34.1), S4Vectors(v.0.38.2), Biobase(v.2.60.0), BiocGenerics(v.0.46.0), clusterProfiler(v.4.8.2), ggVennDiagram(v.1.2.3), tidytree(v.0.4.5), igraph(v.1.5.1), janitor(v.2.2.0), BiocManager(v.1.30.22), pander(v.0.6.5), knitr(v.1.44), here(v.1.0.1), lubridate(v.1.9.3), forcats(v.1.0.0), stringr(v.1.5.0), dplyr(v.1.1.3), purrr(v.1.0.2), readr(v.2.1.4), tidyr(v.1.3.0), tibble(v.3.2.1), ggplot2(v.3.4.4), tidyverse(v.2.0.0) and pacman(v.0.5.1)
loaded via a namespace (and not attached): RColorBrewer(v.1.1-3), rstudioapi(v.0.15.0), jsonlite(v.1.8.7), magrittr(v.2.0.3), farver(v.2.1.1), rmarkdown(v.2.25), fs(v.1.6.3), zlibbioc(v.1.46.0), vctrs(v.0.6.4), memoise(v.2.0.1), RCurl(v.1.98-1.12), ggtree(v.3.8.2), S4Arrays(v.1.0.6), htmltools(v.0.5.6.1), gridGraphics(v.0.5-1), sass(v.0.4.7), bslib(v.0.5.1), plyr(v.1.8.9), cachem(v.1.0.8), lifecycle(v.1.0.3), pkgconfig(v.2.0.3), Matrix(v.1.6-1.1), R6(v.2.5.1), fastmap(v.1.1.1), gson(v.0.1.0), GenomeInfoDbData(v.1.2.10), snakecase(v.0.11.1), digest(v.0.6.33), aplot(v.0.2.2), enrichplot(v.1.20.0), colorspace(v.2.1-0), patchwork(v.1.1.3), rprojroot(v.2.0.3), RSQLite(v.2.3.1), hwriter(v.1.3.2.1), fansi(v.1.0.5), timechange(v.0.2.0), abind(v.1.4-5), httr(v.1.4.7), polyclip(v.1.10-6), compiler(v.4.3.1), bit64(v.4.0.5), withr(v.2.5.1), downloader(v.0.4), viridis(v.0.6.4), DBI(v.1.1.3), ggforce(v.0.4.1), MASS(v.7.3-60), DelayedArray(v.0.26.7), rjson(v.0.2.21), HDO.db(v.0.99.1), tools(v.4.3.1), ape(v.5.7-1), scatterpie(v.0.2.1), glue(v.1.6.2), nlme(v.3.1-163), GOSemSim(v.2.26.1), grid(v.4.3.1), shadowtext(v.0.1.2), reshape2(v.1.4.4), fgsea(v.1.26.0), generics(v.0.1.3), gtable(v.0.3.4), tzdb(v.0.4.0), data.table(v.1.14.8), hms(v.1.1.3), tidygraph(v.1.2.3), utf8(v.1.2.3), ggrepel(v.0.9.4), pillar(v.1.9.0), yulab.utils(v.0.1.0), splines(v.4.3.1), tweenr(v.2.0.2), treeio(v.1.24.3), lattice(v.0.21-9), deldir(v.1.0-9), bit(v.4.0.5), tidyselect(v.1.2.0), GO.db(v.3.17.0), gridExtra(v.2.3), bookdown(v.0.36), xfun(v.0.40), graphlayouts(v.1.0.1), stringi(v.1.7.12), lazyeval(v.0.2.2), ggfun(v.0.1.3), yaml(v.2.3.7), evaluate(v.0.22), codetools(v.0.2-19), interp(v.1.1-4), ggraph(v.2.1.0), qvalue(v.2.32.0), RVenn(v.1.1.0), ggplotify(v.0.1.2), cli(v.3.6.1), munsell(v.0.5.0), jquerylib(v.0.1.4), Rcpp(v.1.0.11), png(v.0.1-8), parallel(v.4.3.1), blob(v.1.2.4), jpeg(v.0.1-10), latticeExtra(v.0.6-30), DOSE(v.3.26.1), bitops(v.1.0-7), viridisLite(v.0.4.2), scales(v.1.2.1), crayon(v.1.5.2), rlang(v.1.1.1), cowplot(v.1.1.1), fastmatch(v.1.1-4) and KEGGREST(v.1.40.1)