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Lecture 04.docx
Lecture_04.docx
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Lecture 04.docx-Lecture 04 Foreach Command o
Lecture_04.docx-Lecture 04 Foreach Command o
Lecture 04.docx-Lecture 04 Foreac...
Lecture_04.docx-Lecture 04 Foreach Command o
Page 1
Lecture 04
Foreach Command
o
Can run the same command on multiple files using foreach
o
Not sure why, but need to use tcsh
o
EXAMPLE:
tcsh
foreach i (*.fastq)
grep “@” $i | wc -l
echo $i
echo “”
end
Homework 1
o
There were 1919 unique sequences in v19 and ~2200 in v20
o
In terms of naming, let’s say we have a miRNA named let-7
o
If there are multiple identical instances, they would be let-7-1, let-7-2, etc.
o
If there are multiple sequences, but they vary slightly, they would be let-7a, let-
7b, etc.
Homework 2
o
We looked at micrornaseq data and started to tie it together
o
We counted the seeds in the micrornaseq files
Homework 3
o
Pretty much same as micrornaseq exploration of HW2, but now with mrnaseq
o
Max # mismatches is the -n argument
Page 2
o
Number of match sites is the -m argument
o
bowtie -n 3 -m 1
Do a bowtie search with 3 mismatches allowed and 1 match site
o
-quiet only shows matches
o
Seed size: -l
We might want to use smaller seed sizes because, if our mRNA sequence
goes over a splice site, part of the mRNA will be in one part of the
genome and another would be elsewhere
Homework 4
o
The main goal is to get a feel for amounts of data vs. quality of the data
Specifically, we will look at mRNAseq data
o
If I get s1 = 10,000,000 mRNA reads and 5,000,000 of them map, that’s one
sense of mRNAseq quality
Let’s say I then do s2 = 20,000,000 mRNA reads and 15,000,000 of them
map
o
For any given gene, its length is the exon bases per gene
K
=
exon bases per gene
1000
o
M = # Maps, R = # Reads, K is already defined
S1: M = 5; K = 7; R (reads) = 102
S2: M = 15; K = 7; R = 1507
o
However, we need to normalize for M
RPKM = Reads Per 1000 Maps
Page 3
RPKM
=
R
K
M
=
RM
K
FPKM = Fragments Per 1000 Maps
Here we will deal with mRNAseq with single reads, so we will see RPKM
o
Our comparisons will be a ratio of the RPKMs, so values will be between 0 and 1
for down-regulation, and between 1 and infinity for up-regulation
To compensate, we can use a log scale (we want to use base-2)
o
Therefore,
Comparison
=
log
2
(
ratio
)
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