chasemc

Create directory ./tmp
easy-cluster fail.fasta mmseqs2_fail ./tmp --threads 24 

MMseqs Version:                     	13.45111
Substitution matrix                 	nucl:nucleotide.out,aa:blosum62.out
Seed substitution matrix            	nucl:nucleotide.out,aa:VTML80.out
Sensitivity                         	4
k-mer length                        	0
k-score                             	2147483647
Alphabet size                       	nucl:5,aa:21

chasemc

Contributor Covenant Code of Conduct

Our Pledge

We as members, contributors, and leaders pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, or sexual

chasemc

library(remotes)
remotes::install_github("chasemc/IDBacApp@prioritizer")
library(IDBacApp)
library(here)

# connect_to_idbac_database
pool <- IDBacApp::idbac_connect('VNBacterialLibrary_db-2_0_0', # name of sqlite database
                                here::here('data')) # directory containing sqlite database

# get_protein_peaks

chasemc

pfam_df <- readLines("pfamscan_out.txt")

pfam_df <- lapply(pfam_df, function(x){
  x <- scan(text = x, what = "text", comment.char = "#", quiet = T)
  if (!identical(x,character(0))){
    return(x)
  }
})
pfam_df <- do.call(rbind.data.frame, pfam_df)

chasemc

## Emacs, make this -*- mode: sh; -*-

FROM r-base:latest

LABEL org.label-schema.license="GPL-2.0" \
      org.label-schema.vcs-url="https://github.com/rocker-org/rocker" \
      maintainer="Dirk Eddelbuettel <[email protected]>"

RUN apt-get update \
	&& apt-get install -y --no-install-recommends \

chasemc

for i in *.pdf; do
    inkscape --export-background-opacity=0 --export-dpi=300 --export-type=png $i
done

chasemc

---
title: "Display code language in Rmarkdown"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(eval = TRUE, include = TRUE, python.reticulate=FALSE)
```

```{r results="asis", echo=FALSE}

chasemc

# Code is very loosely based on https://www.r-bloggers.com/r-cade-games-simulating-the-legendary-game-of-pong/

library(shiny)
library(ggvis)
library(dplyr)

# Playing field boundary lines
boundaries <- tibble(x = c(0, 50, 50, 0), y = c(0, 0, 50, 50))
paddleHeight <- tibble(x = c(0, 0), y = c(10, 20))

chasemc

library(data.table)
library(ggplot2)
library(lubridate)

df <- fread("Shootings.csv")

df$hour = lubridate::hour(lubridate::mdy_hms(df$Date))

new_df <- df[, list(arrest = sum(Arrest), no_arrest = sum(!Arrest), total_reports = length(Arrest)), Year]

chasemc

[Main]
seed=632741178
phase=0
max_processors=24
dataset_id=RL
output_directory=out
temp_directory=/tmp
gsa=True
pooled_gsa=True