genomewalker

--- pvec.h	2018-12-09 12:08:14.727171805 +0100
+++ pvec_mod.h	2018-12-09 12:09:36.186071505 +0100
@@ -539,22 +539,26 @@
 
 
     static inline double gap_posterior( double v1, double v2 ) {
-    	assert( pgap_model.is_valid_ptr() );
-    	//return v1 / (v1 + v2);
+        assert( pgap_model.is_valid_ptr() );
+        //return v1 / (v1 + v2);

genomewalker

cat SRC_sample_ids.txt | parallel -j 16 esearch -db sra -query {} | efetch -format runinfo > stats

genomewalker

processor	: 0
vendor_id	: GenuineIntel
cpu family	: 6
model		: 60
model name	: Intel Core Processor (Haswell, no TSX, IBRS)
stepping	: 1
microcode	: 0x1
cpu MHz		: 2294.684
cache size	: 16384 KB
physical id	: 0

genomewalker

Program call:
search QUERY DB results tmp --num-iterations 2 -e 1e-5 -c 0.4

MMseqs Version:                                                           	199d9b81f8cd6af9e66f97ef4dc0bd53c8fce12b
Sub Matrix                                                                	blosum62.out
Add backtrace                                                             	true
Alignment mode                                                            	2
E-value threshold                                                         	1e-05
Seq. Id Threshold                                                         	0
Seq. Id. Mode                                                             	0

genomewalker

library(Nonpareil)
library(tidyverse)
f <- list.files(path="/scratch/antonio/nonpareil/out/", pattern = "npo")
f <- list.files(path="~/tara_nonpareil/", pattern = "npo")
sample.names <- sapply(strsplit(f, ".npo"), `[`, 1)

Nonpareil.curve(f[[1]])

results_np_tara <- lapply(file.path("~/tara_nonpareil/",f), Nonpareil.curve)

genomewalker

# Let’s get the non-merged reads ------------------------------------------
purrr::map_df(merged, tidyr::extract, col = "sequence", into = "sequence" ) %>%
  filter(accept == FALSE) %>%
  select(nmatch, nmismatch, nindel) %>%
  skimr::skim()

concat <- mergePairs(dada_forward, derep_forward, dada_reverse, derep_reverse, justConcatenate = TRUE)

get_nonmerged <- function(X, merg = merg, conc = conc, fn = fn){
  m <- merg[[X]]

genomewalker

18S magicblast

	dada2_input	filtered	denoised	merged	table	no_chimeras	perc_reads_survived
ERR1018543	6525	4002	3727	3629	3629	3076	47.1
ERR1018546	2421	1513	1276	1229	1229	1095	45.2

Total counts: 4,171

|Kingdom | n|

genomewalker

detachAllPackages <- function() {
basic.packages <- c("package:stats","package:graphics","package:grDevices","package:utils","package:datasets","package:methods","package:base")
package.list <- search()[ifelse(unlist(gregexpr("package:",search()))==1,TRUE,FALSE)]
package.list <- setdiff(package.list,basic.packages)
if (length(package.list)>0)  for (package in package.list) detach(package, character.only=TRUE)
}

genomewalker

Exploration of the ubiquitous EUs

Not related to the niche breadth analysis, we just use those that are found everywhere.

Exporting the clusters belonging to the components found in all samples

super_cl <- read_tsv("/Users/ufo/Downloads/all_cluster_components.tsv", col_names = TRUE, trim_ws = TRUE) %>%
  filter(component %in% clstrs_comp_eu_ubi) %>%
  select(clstr_name) %>%

genomewalker

#!/bin/bash

# 1. We read a folder and take all fastq files
# 2. We quality trim and remove short sequences
# 3. Run kaiju and generate output

#. "${MODULESHOME}"/init/bash
set -x
set -e
main(){