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read -n1 -rsp $'Press Ctrl+C to skip screen...\n' | |
screen -Rx | |
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## .screenrc | |
# backspace throws an error, so fix it | |
bindkey -d ^? stuff ^H | |
bindkey -d ^@ stuff ^H | |
# to be able to attach to the same screen session | |
# from different computers without logging out: | |
multiuser on |
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# to reproduce | |
# The biospecimen_analyte_combined file can be downloaded from Synapse.org under the id: `syn7499603` | |
library(tidyverse) | |
biospecimen_values=read_tsv("~/Documents/Dropbox/ucsc/operations/registry/TCGA biospecimen_analyted_combined.tsv") | |
biospecimen_values %>% | |
mutate( | |
rinNumeric=as.numeric(rinvalue), | |
a260_a280_ratioNumeric=as.numeric(a260_a280_ratio), | |
source=gsub("^([A-Z]*)[-_].*$", "\\1", bcr_sample_barcode) |
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# definitions of calculations | |
# sensitivity is the ability of test to detect the disease when it is present; it is defined as # true positives/# of samples with disease or condition | |
# specificity is the ability of a test to exclude the disease when it is absent, it is defined as the number of true negatives/# without the disease or condition | |
# positive predictive value (PPV) - the likelihood that a positive test truly represents the presence of the disease or condition; it is defined as # true positives/# all positives. A test has a high PPV if a large percentage of prople who get a positive test result actually have the disease or condition. | |
# negative predictive value (NPV) - the likelihood that a negative test truly represents the absence of the disease or condition; it is defined as # true negatives/# all negatives. A test has a high NPV if a large percentage of prople who get a negative test result really don't have the disease or condition. |
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## these are functions that I sometimes use in my code | |
## they are intended to be able to be run on any computer | |
## with R installed. | |
################################# | |
### | |
### load libraries | |
### |
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for i in *.bam ; do echo -n $i; samtools view -h $i | head -1 ; done 2>&1 | grep '\[' | |
# for malformed bams, the output is "EGAD00001001620_ICGC_MB110.sorted.bam[bam_header_read] EOF marker is | |
absent. The input is probably truncated." |
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################################# | |
### | |
### Cautiously RENAME a comma delim list of files | |
### | |
################################# | |
### ASSIGN variable to input file | |
thisKey="Key_Renaming_26Aug2016_hb2.txt" | |
### All functions require a file containing renaming information |
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# File-Name: twitter_word_cloud.R | |
# Date: 2011-01-30 | |
# Author: Drew Conway | |
# Email: drew.conway@nyu.edu | |
# Purpose: Create a comparative word cloud of two twitter hashtags | |
# Data Used: | |
# Packages Used: twitteR, tm, ggplot2 | |
# Output File: Hashtag word cloud | |
# Data Output: | |
# Machine: Drew Conway's MacBook Pro |